Model comparison
GPT-5.5 vs Grok-3 mini
GPT-5.5 is the stronger model overall, scoring 63.4 to 41.2 on the Noometry Index.
Last verified . 25 shared benchmarks.
Summary
- They share 25 benchmarks with published results for both. GPT-5.5 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-5.5 leads 72.8 to 13.6.
- The biggest single-benchmark swing is ARC-AGI-2: 85% for GPT-5.5 and 0.4% for Grok-3 mini.
Side by side
| GPT-5.5 | Grok-3 mini | |
|---|---|---|
| Provider | OpenAI | xAI |
| Noometry Index | 63.4 | 41.2 |
| Released | 2026-04-23 | 2025-04-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $5 | — |
| Output $ / M tokens | $30 | — |
| Results tracked | 71 | 35 |
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Category by category
Coding GPT-5.5 leads
GPT-5.5: 58.2 (#17), Grok-3 mini: 40.8 (#131)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| WeirdML | 84.9% | 42.6% |
| LMArena Coding | 1494 | 1379 |
| SWE-bench Verified | 80.6% | — |
| DeepSWE | 67% | — |
| FrontierCode | 43% | — |
| Aider Polyglot | — | 49.3% |
| LMArena WebDev | 1513 | — |
| SciCode | 56.1% | — |
| GSO | 40.2% | — |
| MirrorCode | 10% | — |
| ALE-Bench | 1,943 | — |
Agentic & Tool Use Not comparable
GPT-5.5: 50.7 (#6), Grok-3 mini: —
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| Terminal-Bench | 84.7% | — |
| APEX-Agents | 55.1% | — |
| OSWorld 2.0 | 13% | — |
| Remote Labor Index | 6.3% | — |
| τ²-bench Banking | 44.6% | — |
| DeepResearch Bench | 54% | — |
| PostTrainBench | 27.2% | — |
| ExploitBench | 47.4% | — |
| GBAEval | 53.2% | — |
| GDP.pdf | 26% | — |
| LMArena Search | 1242 | — |
| Vending-Bench 2 | 7,524 | — |
Reasoning GPT-5.5 leads
GPT-5.5: 72.8 (#11), Grok-3 mini: 13.6 (#334)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| ARC-AGI-2 | 85% | 0.4% |
| Kagi LLM Benchmark | 88.8% | 61.3% |
| ARC-AGI-1 | 95% | 16.5% |
| LMArena Hard Prompts | 1489 | 1375 |
| Epoch Capabilities Index | 159.1 | 140.35 |
| SimpleBench | 69% | — |
| NYT Connections (extended) | 96.2% | — |
| CritPt | 27.1% | — |
| Chess Puzzles | 54% | — |
| EBR-Bench | 34.3% | — |
| Mystery Game Puzzles | 56% | — |
| DTBench | 96% | — |
| LMCA | 54.3% | — |
| Surface Evolver Bench | 88.1% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 60.6 | — |
Math GPT-5.5 leads
GPT-5.5: 81.7 (#11), Grok-3 mini: 42.1 (#85)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 77.8% |
| LMArena Math | 1486 | 1386 |
| FrontierMath (Feb 2025 set) | 51.7% | 5.9% |
| FrontierMath (Tiers 1-3) | 85.3% | — |
| FrontierMath Tier 4 | 72.5% | — |
| MathArena Final-Answer Competitions | 94.3% | — |
| ProofBench | 50% | — |
| Omni-MATH | — | 31.8% |
| MATH Level 5 | — | 90.9% |
| FrontierMath Erdős | 0% | — |
| FrontierMath Tier 4 (v1) | 35.4% | — |
Knowledge GPT-5.5 leads
GPT-5.5: 64.4 (#17), Grok-3 mini: 46.4 (#81)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| GPQA Diamond | 94% | 76.3% |
| LMArena Expert | 1508 | 1395 |
| SimpleQA Verified | 63% | — |
| MMLU-Pro | — | 79.9% |
| Confabulations | — | 10.8% |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | — | 67.5% |
Multimodal Not comparable
GPT-5.5: 46.9 (#12), Grok-3 mini: —
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| LMArena Vision | 1297 | — |
| Blueprint-Bench 2 | 36.2% | — |
| Furniture Assembly | 44.2% | — |
| LMArena Document | 1486 | — |
Multilingual GPT-5.5 leads
GPT-5.5: 56.4 (#20), Grok-3 mini: 48.1 (#145)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| LMArena Non-English | 1467 | 1352 |
| LMArena Chinese | 1533 | 1387 |
| LMArena French | 1486 | 1357 |
| LMArena German | 1480 | 1349 |
| LMArena Japanese | 1498 | 1342 |
| LMArena Korean | 1460 | 1335 |
| LMArena Russian | 1473 | 1353 |
| LMArena Spanish | 1468 | 1381 |
Instruction Following Too close to call
GPT-5.5: 77.5 (#18), Grok-3 mini: 78.5 (#9)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| LMArena Instruction Following | 1479 | 1357 |
| IFEval | — | 95.1% |
Long Context GPT-5.5 leads
GPT-5.5: 48.3 (#12), Grok-3 mini: 41.0 (#147)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| LMArena Longer Query | 1484 | 1372 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench Life | 22.2% | — |
Writing & Preference GPT-5.5 leads
GPT-5.5: 72.7 (#13), Grok-3 mini: 52.5 (#169)
| Benchmark | GPT-5.5 | Grok-3 mini |
|---|---|---|
| LMArena Text | 1472 | 1370 |
| LMArena Creative Writing | 1455 | 1342 |
| LMArena Multi-Turn | 1476 | 1355 |
| Short-Story Creative Writing | — | 73.5% |
| EQ-Bench Creative Writing | 1844 | — |
| WildBench | — | 65.1% |
| EQ-Bench 4 | 1315 | — |
Frequently asked questions
Is GPT-5.5 better than Grok-3 mini?
GPT-5.5 is the stronger model overall, scoring 63.4 to 41.2 on the Noometry Index.
Is GPT-5.5 or Grok-3 mini better for coding?
GPT-5.5 scores higher on coding benchmarks: 58.2 versus 40.8 in the Noometry coding category.
How many benchmarks do GPT-5.5 and Grok-3 mini share?
25 benchmarks have published results for both models. GPT-5.5 has 71 scored results on Noometry and Grok-3 mini has 35.