Model comparison
GPT-5.6 Sol vs Yi-Large
GPT-5.6 Sol has enough public results to be ranked (#6); Yi-Large does not yet, so treat this comparison as directional.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in coding, where GPT-5.6 Sol leads 61.1 to 36.1.
Side by side
| GPT-5.6 Sol | Yi-Large | |
|---|---|---|
| Provider | OpenAI | 01.AI |
| Noometry Index | 64.4 | 37.6 |
| Released | 2026-07-09 | 2024-05-13 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $4 | — |
| Output $ / M tokens | $20 | — |
| Results tracked | 64 | 3 |
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Category by category
Coding GPT-5.6 Sol leads
GPT-5.6 Sol: 61.1 (#7), Yi-Large: 36.1 (#201)
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| DeepSWE | 72.7% | — |
| FrontierCode | 47.5% | — |
| CursorBench | 41.7% | — |
| LMArena WebDev | 1619 | — |
| FrontierSWE | 32.2% | — |
| SciCode | 57.1% | — |
| WeirdML | 89.4% | — |
| BigCodeBench Instruct | — | 37.7% |
| LMArena Coding | 1493 | — |
| MirrorCode | 20% | — |
| BigCodeBench Complete | — | 47.2% |
| ALE-Bench | 2,177 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Sol: 50.2 (#7), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| APEX-Agents | 51.4% | — |
| OSWorld 2.0 | 27.3% | — |
| τ²-bench Banking | 46.9% | — |
| PostTrainBench | 36.2% | — |
| BALROG | 60% | — |
| GBAEval | 52.6% | — |
| GDP.pdf | 30.7% | — |
| LMArena Search | 1257 | — |
| Vending-Bench 2 | 9,619 | — |
Reasoning Not comparable
GPT-5.6 Sol: 74.7 (#6), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| ARC-AGI-2 | 92.5% | — |
| SimpleBench | 71.7% | — |
| Kagi LLM Benchmark | 67% | — |
| NYT Connections (extended) | 93.8% | — |
| ARC-AGI-1 | 97.5% | — |
| CritPt | 32.3% | — |
| Chess Puzzles | 64% | — |
| EnigmaEval | 37.1% | — |
| EBR-Bench | 44.8% | — |
| LMArena Hard Prompts | 1481 | — |
| Mystery Game Puzzles | 58% | — |
| DTBench | 96% | — |
| LMCA | 59.2% | — |
| Surface Evolver Bench | 93.1% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 161.99 | — |
Math Not comparable
GPT-5.6 Sol: 85.5 (#7), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| FrontierMath (Tiers 1-3) | 89.1% | — |
| FrontierMath Tier 4 | 82.9% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| LMArena Math | 1472 | — |
| FrontierMath Erdős | 0% | — |
Knowledge Not comparable
GPT-5.6 Sol: 64.3 (#16), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| GPQA Diamond | 93.5% | — |
| SimpleQA Verified | 69.7% | — |
| Vectara Hallucination Rate | 12.4% | — |
| LMArena Expert | 1517 | — |
| MMLU | — | 79.3% |
Multimodal Not comparable
GPT-5.6 Sol: 48.9 (#8), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| LMArena Vision | 1281 | — |
| Blueprint-Bench 2 | 33.6% | — |
| Furniture Assembly | 56.7% | — |
| LMArena Document | 1483 | — |
Multilingual Not comparable
GPT-5.6 Sol: 55.4 (#32), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| LMArena Non-English | 1450 | — |
| LMArena Chinese | 1523 | — |
| LMArena French | 1475 | — |
| LMArena German | 1476 | — |
| LMArena Japanese | 1475 | — |
| LMArena Korean | 1434 | — |
| LMArena Russian | 1466 | — |
| LMArena Spanish | 1449 | — |
Instruction Following Not comparable
GPT-5.6 Sol: 77.8 (#16), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| LMArena Instruction Following | 1480 | — |
Long Context Not comparable
GPT-5.6 Sol: 45.3 (#42), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| LMArena Longer Query | 1479 | — |
Writing & Preference Not comparable
GPT-5.6 Sol: 73.5 (#12), Yi-Large: —
| Benchmark | GPT-5.6 Sol | Yi-Large |
|---|---|---|
| LMArena Text | 1456 | — |
| LMArena Creative Writing | 1450 | — |
| EQ-Bench Creative Writing | 1972 | — |
| EQ-Bench 4 | 1250 | — |
| LMArena Multi-Turn | 1456 | — |
Frequently asked questions
Is GPT-5.6 Sol better than Yi-Large?
GPT-5.6 Sol has enough public results to be ranked (#6); Yi-Large does not yet, so treat this comparison as directional.
Is GPT-5.6 Sol or Yi-Large better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 61.1 versus 36.1 in the Noometry coding category.
How many benchmarks do GPT-5.6 Sol and Yi-Large share?
0 benchmarks have published results for both models. GPT-5.6 Sol has 64 scored results on Noometry and Yi-Large has 3.