Model comparison
GPT-6.1 Sol vs Mistral Small 3.2
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 30× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Mistral AISummary
- They share 4 benchmarks with published results for both. GPT-6.1 Sol scores higher in 4 categories and Mistral Small 3.2 in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6.1 Sol leads 93.7 to 26.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 100% for GPT-6.1 Sol and 30.3% for Mistral Small 3.2.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $2 / $10 for GPT-6.1 Sol.
- GPT-6.1 Sol accepts more context: 1.05M tokens versus 256K.
- Mistral Small 3.2 has downloadable open weights; the other is API-only.
Side by side
| GPT-6.1 Sol | Mistral Small 3.2 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 65.6 | 31.2 |
| Released | 2026-09-29 | 2025-06-20 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 256K |
| Max output | 128K | 16K |
| Input $ / M tokens | $2 | $0.0938 |
| Output $ / M tokens | $10 | $0.25 |
| Results tracked | 34 | 6 |
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Category by category
Coding Not comparable
GPT-6.1 Sol: 63.2 (#8), Mistral Small 3.2: —
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| DeepSWE | 75.2% | — |
| FrontierCode | 50.2% | — |
| LMArena WebDev | 1755 | — |
| SciCode | 55.8% | — |
| LMArena Coding | 1487 | — |
Agentic & Tool Use Not comparable
GPT-6.1 Sol: 39.6 (#26), Mistral Small 3.2: —
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| APEX-Agents | 60% | — |
| GDP.pdf | 32% | — |
Reasoning GPT-6.1 Sol leads
GPT-6.1 Sol: 81.9 (#2), Mistral Small 3.2: 18.1 (#287)
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| Chess Puzzles | 61% | 1% |
| Epoch Capabilities Index | 166.09 | 131.74 |
| ARC-AGI-2 | 94.2% | — |
| Kagi LLM Benchmark | — | 40.4% |
| NYT Connections (extended) | 95.5% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| EBR-Bench | 54.3% | — |
| LMArena Hard Prompts | 1466 | — |
| Mystery Game Puzzles | 80% | — |
Math GPT-6.1 Sol leads
GPT-6.1 Sol: 93.7 (#1), Mistral Small 3.2: 26.3 (#260)
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 30.3% |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 100% | — |
| ProofBench | 99% | — |
| LMArena Math | 1464 | — |
Knowledge GPT-6.1 Sol leads
GPT-6.1 Sol: 71.8 (#4), Mistral Small 3.2: 26.7 (#256)
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | 95.4% | 49.1% |
| SimpleQA Verified | 73.9% | — |
| LMArena Expert | 1502 | — |
Multimodal Not comparable
GPT-6.1 Sol: 52.7 (#5), Mistral Small 3.2: —
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| LMArena Vision | 1288 | — |
| Furniture Assembly | 80% | — |
Multilingual Not comparable
GPT-6.1 Sol: 54.3 (#46), Mistral Small 3.2: —
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| LMArena Non-English | 1438 | — |
| LMArena Chinese | 1477 | — |
| LMArena Russian | 1455 | — |
Instruction Following Not comparable
GPT-6.1 Sol: 77.0 (#29), Mistral Small 3.2: —
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| LMArena Instruction Following | 1468 | — |
Long Context Not comparable
GPT-6.1 Sol: 44.9 (#54), Mistral Small 3.2: —
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| LMArena Longer Query | 1465 | — |
Writing & Preference GPT-6.1 Sol leads
GPT-6.1 Sol: 63.6 (#63), Mistral Small 3.2: 45.0 (#224)
| Benchmark | GPT-6.1 Sol | Mistral Small 3.2 |
|---|---|---|
| LMArena Text | 1447 | — |
| LMArena Creative Writing | 1432 | — |
| EQ-Bench Creative Writing | — | 1255 |
| LMArena Multi-Turn | 1449 | — |
Frequently asked questions
Is GPT-6.1 Sol better than Mistral Small 3.2?
GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 30× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-6.1 Sol or Mistral Small 3.2?
Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; GPT-6.1 Sol lists at $2 and $10.
Which has the bigger context window?
GPT-6.1 Sol does, with 1.05M tokens against 256K.
How many benchmarks do GPT-6.1 Sol and Mistral Small 3.2 share?
4 benchmarks have published results for both models. GPT-6.1 Sol has 34 scored results on Noometry and Mistral Small 3.2 has 6.