Model comparison
GPT-6 Sol vs Mistral Nemo
GPT-6 Sol is the stronger model overall, scoring 61.8 to 26.4 on the Noometry Index. Mistral Nemo costs 27× less per token, which makes it the better buy when GPT-6 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 Sol scores higher in 5 categories and Mistral Nemo in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Sol leads 87.2 to 25.5.
- The biggest single-benchmark swing is GPQA Diamond: 94.3% for GPT-6 Sol and 29.9% for Mistral Nemo.
- Mistral Nemo is cheaper at $0.15 / $0.15 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 128K.
- Mistral Nemo has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Sol | Mistral Nemo | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 61.8 | 26.4 |
| Released | 2026-09-22 | 2024-07-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 128K |
| Max output | 128K | 128K |
| Input $ / M tokens | $2 | $0.15 |
| Output $ / M tokens | $10 | $0.15 |
| Results tracked | 45 | 10 |
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Category by category
Coding Not comparable
GPT-6 Sol: 60.1 (#11), Mistral Nemo: —
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| LMArena WebDev | 1688 | — |
| SciCode | 57.6% | — |
| LMArena Coding | 1447 | — |
| ALE-Bench | 2,462 | — |
Agentic & Tool Use GPT-6 Sol leads
GPT-6 Sol: 37.2 (#36), Mistral Nemo: 23.5 (#125)
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| APEX-Agents | 54.3% | — |
| Berkeley Function Calling Leaderboard | — | 27.6% |
| BALROG | — | 17.6% |
| GDP.pdf | 26.4% | — |
| Vending-Bench 2 | 14,428 | — |
Reasoning GPT-6 Sol leads
GPT-6 Sol: 74.0 (#9), Mistral Nemo: 20.7 (#232)
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| DTBench | 97.3% | 48.6% |
| Epoch Capabilities Index | 162.72 | 118.68 |
| ARC-AGI-2 | 89.6% | — |
| NYT Connections (extended) | 90.1% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 30.9% | — |
| EBR-Bench | 53.3% | — |
| LMArena Hard Prompts | 1418 | — |
| Mystery Game Puzzles | 56% | — |
| LMCA | 59.1% | — |
| PIQA | — | 83.5% |
Math GPT-6 Sol leads
GPT-6 Sol: 87.2 (#7), Mistral Nemo: 25.5 (#268)
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| FrontierMath (Tiers 1-3) | 89.8% | — |
| FrontierMath Tier 4 | 90% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| LMArena Math | 1402 | — |
| MATH Level 5 | — | 10.8% |
| GSM8K | — | 84.2% |
Knowledge GPT-6 Sol leads
GPT-6 Sol: 64.8 (#15), Mistral Nemo: 12.3 (#298)
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| GPQA Diamond | 94.3% | 29.9% |
| SimpleQA Verified | 60.7% | — |
| Vectara Hallucination Rate | 6.5% | — |
| LMArena Expert | 1439 | — |
| BoolQ | — | 82.5% |
Multimodal Not comparable
GPT-6 Sol: 47.6 (#10), Mistral Nemo: —
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| LMArena Vision | 1245 | — |
| Blueprint-Bench 2 | 36.9% | — |
| Furniture Assembly | 58.3% | — |
Multilingual Not comparable
GPT-6 Sol: 50.5 (#118), Mistral Nemo: —
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| LMArena Non-English | 1385 | — |
| LMArena Chinese | 1405 | — |
| LMArena French | 1410 | — |
| LMArena German | 1390 | — |
| LMArena Japanese | 1385 | — |
| LMArena Korean | 1341 | — |
| LMArena Russian | 1401 | — |
| LMArena Spanish | 1384 | — |
Instruction Following Not comparable
GPT-6 Sol: 74.5 (#94), Mistral Nemo: —
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| LMArena Instruction Following | 1412 | — |
Long Context Not comparable
GPT-6 Sol: 43.1 (#108), Mistral Nemo: —
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| LMArena Longer Query | 1411 | — |
Writing & Preference GPT-6 Sol leads
GPT-6 Sol: 71.9 (#18), Mistral Nemo: 28.5 (#296)
| Benchmark | GPT-6 Sol | Mistral Nemo |
|---|---|---|
| EQ-Bench Creative Writing | 2125 | 881 |
| LMArena Text | 1395 | — |
| LMArena Creative Writing | 1378 | — |
| LMArena Multi-Turn | 1412 | — |
Frequently asked questions
Is GPT-6 Sol better than Mistral Nemo?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 26.4 on the Noometry Index. Mistral Nemo costs 27× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Sol or Mistral Nemo?
Mistral Nemo is cheaper. It lists at $0.15 per million input tokens and $0.15 per million output tokens; GPT-6 Sol lists at $2 and $10.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 128K.
How many benchmarks do GPT-6 Sol and Mistral Nemo share?
4 benchmarks have published results for both models. GPT-6 Sol has 45 scored results on Noometry and Mistral Nemo has 10.