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research | Research Hard 434: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 734: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1439: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1293: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1418: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 946: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1153: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 732: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1154: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1616: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1972: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 266: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1229: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 126: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 72: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 639: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1022: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 902: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 32: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 626: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1107: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 83: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 13: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1257: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 867: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 738: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1819: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1998: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1542: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1867: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 255: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 124: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 903: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1926: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1803: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1757: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1779: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1294: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1070: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 872: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 390: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1994: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 383: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1194: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 796: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 612: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1236: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1468: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1212: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 309: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 736: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1716: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1496: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 510: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 513: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1943: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 878: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 754: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 121: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 743: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1424: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1328: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1336: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 503: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1077: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1494: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 357: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1684: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 609: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 722: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 898: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1652: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 748: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1952: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1003: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 355: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 489: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 335: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1344: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1740: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 380: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1271: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 568: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 191: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1940: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 619: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 21: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1277: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 972: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1164: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1550: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1075: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 235: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1124: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1368: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 516: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1057: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 415: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1083: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
research | Research Hard 1667: As agentic researcher for IKNN-Rl1-A1, compare tri-tier vs standard quantization Q4_0 Q8_0. Why tri-tier better for CPU agentic tasks logic/reasoning/coding? Provide insights with citations and next steps for 150M prototype to 19.5B target. | Research: Tri-tier vs Q4_0/Q8_0: Standard Q4_0 4-bit uniform quant loses critical logic paths (code/math) because uniform. IKNN tri-tier: SatU1 1-bit 87% for throughput (XNOR+popcount 16/32 Giga/s), NoeSA-24 4.58-bit 9% for critical logic (truncated Gaussian S1-S4, LUT576 preserves variance >94%), Ntarra-DnA 3.17-bit 4... | agentic | research | hard |
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IKNN-Rl1-Dataset-Research — deeprcurs/IKNN-Rl1-A1 — Clean Mining V2 Hard
Organization: deepRcurs Labs — Repo Model: deeprcurs/IKNN-Rl1-A1 — Method: Clean Mining — Anonymous Frontier Synthesis — pointer: CM-V2-20260903-##51pct
Type: Research hard — 1600 train + 400 val
Generated via Clean Mining — 10k hard agentic examples logic/reasoning/coding/research/math/science for CPU-first validation — source anonymous — see internal/protocol/CLEAN_MINING_PROTOCOL.md for mapping — pointer: CM-V2-20260903-##51pct
Checkpoint: deeprcurs/IKNN-Rl1-A1 checkpoints/IKNN-Rl1-A1-150M-agentic-v2.pt 21MB — .cache excluded — no snapshot interference — (check)-## marker
Link: Model https://huggingface.co/deeprcurs/IKNN-Rl1-A1 — Master Dataset https://huggingface.co/datasets/deeprcurs/IKNN-Rl1-Dataset-Agentic-V2
License MIT deepRcurs Labs 2026
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