Model comparison
GPT-5.6 Sol vs Grok 4
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 47.8 on the Noometry Index.
Last verified . 29 shared benchmarks.
Summary
- They share 29 benchmarks with published results for both. GPT-5.6 Sol scores higher in 8 categories and Grok 4 in 2 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Sol leads 85.5 to 46.5.
- The biggest single-benchmark swing is ARC-AGI-2: 92.5% for GPT-5.6 Sol and 16% for Grok 4.
Side by side
| GPT-5.6 Sol | Grok 4 | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 64.4 | 47.8 |
| Released | 2026-07-09 | 2025-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $4 | — |
| Output $ / M tokens | $20 | — |
| Results tracked | 64 | 48 |
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Category by category
Coding GPT-5.6 Sol leads
GPT-5.6 Sol: 61.1 (#7), Grok 4: 49.9 (#44)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| WeirdML | 89.4% | 45.7% |
| LMArena Coding | 1493 | 1408 |
| DeepSWE | 72.7% | — |
| FrontierCode | 47.5% | — |
| Aider Polyglot | — | 79.6% |
| CursorBench | 41.7% | — |
| LMArena WebDev | 1619 | — |
| FrontierSWE | 32.2% | — |
| SciCode | 57.1% | — |
| MirrorCode | 20% | — |
| ALE-Bench | 2,177 | — |
Agentic & Tool Use GPT-5.6 Sol leads
GPT-5.6 Sol: 50.2 (#7), Grok 4: 32.1 (#62)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| BALROG | 60% | 43.6% |
| LMArena Search | 1257 | 1142 |
| Terminal-Bench | — | 27.2% |
| APEX-Agents | 51.4% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| OSWorld 2.0 | 27.3% | — |
| GDPval | — | 21.1% |
| τ²-bench Banking | 46.9% | — |
| Cybench | — | 43% |
| DeepResearch Bench | — | 47.3% |
| PostTrainBench | 36.2% | — |
| GBAEval | 52.6% | — |
| GDP.pdf | 30.7% | — |
| METR Time Horizons | — | 66.6% |
| Vending-Bench 2 | 9,619 | — |
Reasoning GPT-5.6 Sol leads
GPT-5.6 Sol: 74.7 (#6), Grok 4: 36.9 (#59)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| ARC-AGI-2 | 92.5% | 16% |
| SimpleBench | 71.7% | 60.5% |
| Kagi LLM Benchmark | 67% | 73.6% |
| ARC-AGI-1 | 97.5% | 66.7% |
| Chess Puzzles | 64% | 28% |
| LMArena Hard Prompts | 1481 | 1409 |
| Epoch Capabilities Index | 161.99 | 146.46 |
| NYT Connections (extended) | 93.8% | — |
| CritPt | 32.3% | — |
| EnigmaEval | 37.1% | — |
| EBR-Bench | 44.8% | — |
| Mystery Game Puzzles | 58% | — |
| DTBench | 96% | — |
| LMCA | 59.2% | — |
| Surface Evolver Bench | 93.1% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | — | 60.9 |
Math GPT-5.6 Sol leads
GPT-5.6 Sol: 85.5 (#7), Grok 4: 46.5 (#58)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 84% |
| LMArena Math | 1472 | 1422 |
| FrontierMath (Tiers 1-3) | 89.1% | — |
| FrontierMath Tier 4 | 82.9% | — |
| ProofBench | 83% | — |
| Omni-MATH | — | 60.3% |
| FrontierMath (Feb 2025 set) | — | 19.7% |
| FrontierMath Erdős | 0% | — |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge GPT-5.6 Sol leads
GPT-5.6 Sol: 64.3 (#16), Grok 4: 53.7 (#50)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| GPQA Diamond | 93.5% | 87% |
| LMArena Expert | 1517 | 1417 |
| SimpleQA Verified | 69.7% | — |
| MMLU-Pro | — | 85.1% |
| Confabulations | — | 12.4% |
| Vectara Hallucination Rate | 12.4% | — |
| GPQA (HELM) | — | 72.7% |
Multimodal GPT-5.6 Sol leads
GPT-5.6 Sol: 48.9 (#8), Grok 4: 33.1 (#89)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| LMArena Vision | 1281 | 1211 |
| GeoBench | — | 45% |
| Blueprint-Bench 2 | 33.6% | — |
| Furniture Assembly | 56.7% | — |
| LMArena Document | 1483 | — |
Multilingual GPT-5.6 Sol leads
GPT-5.6 Sol: 55.4 (#32), Grok 4: 52.0 (#98)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| LMArena Non-English | 1450 | 1403 |
| LMArena Chinese | 1523 | 1428 |
| LMArena French | 1475 | 1418 |
| LMArena German | 1476 | 1429 |
| LMArena Japanese | 1475 | 1396 |
| LMArena Korean | 1434 | 1376 |
| LMArena Russian | 1466 | 1409 |
| LMArena Spanish | 1449 | 1419 |
Instruction Following Grok 4 leads
GPT-5.6 Sol: 77.8 (#16), Grok 4: 79.4 (#4)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| LMArena Instruction Following | 1480 | 1387 |
| IFEval | — | 94.9% |
Long Context Grok 4 leads
GPT-5.6 Sol: 45.3 (#42), Grok 4: 63.1 (#4)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| LMArena Longer Query | 1479 | 1409 |
| Fiction.LiveBench | — | 94.4% |
Writing & Preference GPT-5.6 Sol leads
GPT-5.6 Sol: 73.5 (#12), Grok 4: 58.7 (#111)
| Benchmark | GPT-5.6 Sol | Grok 4 |
|---|---|---|
| LMArena Text | 1456 | 1412 |
| LMArena Creative Writing | 1450 | 1397 |
| LMArena Multi-Turn | 1456 | 1416 |
| Short-Story Creative Writing | — | 76.9% |
| EQ-Bench Creative Writing | 1972 | — |
| WildBench | — | 79.7% |
| EQ-Bench 4 | 1250 | — |
Frequently asked questions
Is GPT-5.6 Sol better than Grok 4?
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 47.8 on the Noometry Index.
Is GPT-5.6 Sol or Grok 4 better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 61.1 versus 49.9 in the Noometry coding category.
How many benchmarks do GPT-5.6 Sol and Grok 4 share?
29 benchmarks have published results for both models. GPT-5.6 Sol has 64 scored results on Noometry and Grok 4 has 48.