Model comparison
GPT-6 Sol vs Mistral Medium 3.5
GPT-6 Sol is the stronger model overall, scoring 61.8 to 40.2 on the Noometry Index.
Last verified . 20 shared benchmarks.
Mistral AISummary
- They share 20 benchmarks with published results for both. GPT-6 Sol scores higher in 6 categories and Mistral Medium 3.5 in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Sol leads 74.0 to 17.3.
- The biggest single-benchmark swing is NYT Connections (extended): 90.1% for GPT-6 Sol and 12.9% for Mistral Medium 3.5.
- Mistral Medium 3.5 is cheaper at $1.50 / $7.50 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 262K.
- Mistral Medium 3.5 has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Sol | Mistral Medium 3.5 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 61.8 | 40.2 |
| Released | 2026-09-22 | — |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 128K | 210K |
| Input $ / M tokens | $2 | $1.50 |
| Output $ / M tokens | $10 | $7.50 |
| Results tracked | 45 | 22 |
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Category by category
Coding GPT-6 Sol leads
GPT-6 Sol: 60.1 (#11), Mistral Medium 3.5: 36.0 (#213)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena WebDev | 1688 | 1264 |
| LMArena Coding | 1447 | 1461 |
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| SciCode | 57.6% | — |
| ALE-Bench | 2,462 | — |
Agentic & Tool Use Not comparable
GPT-6 Sol: 37.2 (#36), Mistral Medium 3.5: —
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| APEX-Agents | 54.3% | — |
| GDP.pdf | 26.4% | — |
| Vending-Bench 2 | 14,428 | — |
Reasoning GPT-6 Sol leads
GPT-6 Sol: 74.0 (#9), Mistral Medium 3.5: 17.3 (#295)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| NYT Connections (extended) | 90.1% | 12.9% |
| LMArena Hard Prompts | 1418 | 1436 |
| Epoch Capabilities Index | 162.72 | 141.35 |
| ARC-AGI-2 | 89.6% | — |
| Kagi LLM Benchmark | — | 41.4% |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 30.9% | — |
| EBR-Bench | 53.3% | — |
| Mystery Game Puzzles | 56% | — |
| DTBench | 97.3% | — |
| LMCA | 59.1% | — |
Math GPT-6 Sol leads
GPT-6 Sol: 87.2 (#7), Mistral Medium 3.5: 39.1 (#113)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena Math | 1402 | 1431 |
| FrontierMath (Tiers 1-3) | 89.8% | — |
| FrontierMath Tier 4 | 90% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
Knowledge GPT-6 Sol leads
GPT-6 Sol: 64.8 (#15), Mistral Medium 3.5: 40.0 (#126)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena Expert | 1439 | 1432 |
| GPQA Diamond | 94.3% | — |
| SimpleQA Verified | 60.7% | — |
| Vectara Hallucination Rate | 6.5% | — |
Multimodal GPT-6 Sol leads
GPT-6 Sol: 47.6 (#10), Mistral Medium 3.5: 38.3 (#65)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena Vision | 1245 | 1223 |
| Blueprint-Bench 2 | 36.9% | — |
| Furniture Assembly | 58.3% | — |
Multilingual Mistral Medium 3.5 leads
GPT-6 Sol: 50.5 (#118), Mistral Medium 3.5: 51.9 (#100)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena Non-English | 1385 | 1404 |
| LMArena Chinese | 1405 | 1442 |
| LMArena French | 1410 | 1448 |
| LMArena German | 1390 | 1451 |
| LMArena Korean | 1341 | 1385 |
| LMArena Russian | 1401 | 1395 |
| LMArena Spanish | 1384 | 1409 |
| LMArena Japanese | 1385 | — |
Instruction Following Too close to call
GPT-6 Sol: 74.5 (#94), Mistral Medium 3.5: 74.6 (#90)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena Instruction Following | 1412 | 1415 |
Long Context Too close to call
GPT-6 Sol: 43.1 (#108), Mistral Medium 3.5: 43.2 (#103)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena Longer Query | 1411 | 1415 |
Writing & Preference GPT-6 Sol leads
GPT-6 Sol: 71.9 (#18), Mistral Medium 3.5: 58.5 (#117)
| Benchmark | GPT-6 Sol | Mistral Medium 3.5 |
|---|---|---|
| LMArena Text | 1395 | 1421 |
| LMArena Creative Writing | 1378 | 1374 |
| LMArena Multi-Turn | 1412 | 1423 |
| EQ-Bench Creative Writing | 2125 | — |
| EQ-Bench 4 | — | 993 |
Frequently asked questions
Is GPT-6 Sol better than Mistral Medium 3.5?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 40.2 on the Noometry Index.
Which is cheaper, GPT-6 Sol or Mistral Medium 3.5?
Mistral Medium 3.5 is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is GPT-6 Sol or Mistral Medium 3.5 better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 36.0 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 262K.
How many benchmarks do GPT-6 Sol and Mistral Medium 3.5 share?
20 benchmarks have published results for both models. GPT-6 Sol has 45 scored results on Noometry and Mistral Medium 3.5 has 22.