Model comparison
GPT-5.6 Sol vs Grok-3 mini
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 41.0 on the Noometry Index.
Last verified . 24 shared benchmarks.
Summary
- They share 24 benchmarks with published results for both. GPT-5.6 Sol scores higher in 7 categories and Grok-3 mini in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.6 Sol leads 74.7 to 13.8.
- The biggest single-benchmark swing is ARC-AGI-2: 92.5% for GPT-5.6 Sol and 0.4% for Grok-3 mini.
Side by side
| GPT-5.6 Sol | Grok-3 mini | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 64.4 | 41.0 |
| Released | 2026-07-09 | 2025-04-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $4 | — |
| Output $ / M tokens | $20 | — |
| Results tracked | 64 | 35 |
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Category by category
Coding GPT-5.6 Sol leads
GPT-5.6 Sol: 61.1 (#7), Grok-3 mini: 40.4 (#126)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| WeirdML | 89.4% | 42.6% |
| LMArena Coding | 1493 | 1380 |
| DeepSWE | 72.7% | — |
| FrontierCode | 47.5% | — |
| Aider Polyglot | — | 49.3% |
| CursorBench | 41.7% | — |
| LMArena WebDev | 1619 | — |
| FrontierSWE | 32.2% | — |
| SciCode | 57.1% | — |
| MirrorCode | 20% | — |
| ALE-Bench | 2,177 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Sol: 50.2 (#7), Grok-3 mini: —
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| 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 GPT-5.6 Sol leads
GPT-5.6 Sol: 74.7 (#6), Grok-3 mini: 13.8 (#323)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| ARC-AGI-2 | 92.5% | 0.4% |
| Kagi LLM Benchmark | 67% | 61.3% |
| ARC-AGI-1 | 97.5% | 16.5% |
| LMArena Hard Prompts | 1481 | 1374 |
| Epoch Capabilities Index | 161.99 | 140.35 |
| SimpleBench | 71.7% | — |
| NYT Connections (extended) | 93.8% | — |
| CritPt | 32.3% | — |
| Chess Puzzles | 64% | — |
| 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 | — |
Math GPT-5.6 Sol leads
GPT-5.6 Sol: 85.5 (#7), Grok-3 mini: 40.3 (#78)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 77.8% |
| LMArena Math | 1472 | 1386 |
| FrontierMath (Tiers 1-3) | 89.1% | — |
| FrontierMath Tier 4 | 82.9% | — |
| ProofBench | 83% | — |
| Omni-MATH | — | 31.8% |
| MATH Level 5 | — | 90.9% |
| FrontierMath (Feb 2025 set) | — | 5.9% |
| FrontierMath Erdős | 0% | — |
Knowledge GPT-5.6 Sol leads
GPT-5.6 Sol: 64.3 (#16), Grok-3 mini: 46.3 (#75)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| GPQA Diamond | 93.5% | 76.3% |
| LMArena Expert | 1517 | 1395 |
| SimpleQA Verified | 69.7% | — |
| MMLU-Pro | — | 79.9% |
| Confabulations | — | 10.8% |
| Vectara Hallucination Rate | 12.4% | — |
| GPQA (HELM) | — | 67.5% |
Multimodal Not comparable
GPT-5.6 Sol: 48.9 (#8), Grok-3 mini: —
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| LMArena Vision | 1281 | — |
| 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-3 mini: 48.3 (#141)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| LMArena Non-English | 1450 | 1352 |
| LMArena Chinese | 1523 | 1387 |
| LMArena French | 1475 | 1357 |
| LMArena German | 1476 | 1350 |
| LMArena Japanese | 1475 | 1343 |
| LMArena Korean | 1434 | 1336 |
| LMArena Russian | 1466 | 1352 |
| LMArena Spanish | 1449 | 1379 |
Instruction Following Too close to call
GPT-5.6 Sol: 77.8 (#16), Grok-3 mini: 78.7 (#8)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| LMArena Instruction Following | 1480 | 1356 |
| IFEval | — | 95.1% |
Long Context GPT-5.6 Sol leads
GPT-5.6 Sol: 45.3 (#42), Grok-3 mini: 41.0 (#142)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| LMArena Longer Query | 1479 | 1372 |
| Fiction.LiveBench | — | 66.7% |
Writing & Preference GPT-5.6 Sol leads
GPT-5.6 Sol: 73.5 (#12), Grok-3 mini: 52.7 (#163)
| Benchmark | GPT-5.6 Sol | Grok-3 mini |
|---|---|---|
| LMArena Text | 1456 | 1370 |
| LMArena Creative Writing | 1450 | 1342 |
| LMArena Multi-Turn | 1456 | 1355 |
| Short-Story Creative Writing | — | 73.5% |
| EQ-Bench Creative Writing | 1972 | — |
| WildBench | — | 65.1% |
| EQ-Bench 4 | 1250 | — |
Frequently asked questions
Is GPT-5.6 Sol better than Grok-3 mini?
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 41.0 on the Noometry Index.
Is GPT-5.6 Sol or Grok-3 mini better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 61.1 versus 40.4 in the Noometry coding category.
How many benchmarks do GPT-5.6 Sol and Grok-3 mini share?
24 benchmarks have published results for both models. GPT-5.6 Sol has 64 scored results on Noometry and Grok-3 mini has 35.