Model comparison
Claude Sonnet 4.6 vs Mistral 7B
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 23.0 on the Noometry Index. Mistral 7B costs 24× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 8 categories and Mistral 7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Sonnet 4.6 leads 52.9 to 8.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 85.8% for Claude Sonnet 4.6 and 0.3% for Mistral 7B.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.6.
- Claude Sonnet 4.6 accepts more context: 1M tokens versus 8K.
- Mistral 7B has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4.6 | Mistral 7B | |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 50.3 | 23.0 |
| Released | 2026-02-17 | 2023-09-27 |
| Weights | Proprietary | Open |
| Context window | 1M | 8K |
| Max output | 128K | 8K |
| Input $ / M tokens | $3 | $0.25 |
| Output $ / M tokens | $15 | $0.25 |
| Results tracked | 57 | 37 |
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Category by category
Coding Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.3 (#67), Mistral 7B: 26.4 (#326)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| LMArena Coding | 1504 | 1082 |
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| LMArena WebDev | 1522 | — |
| SciCode | 46.8% | — |
| WeirdML | 66.1% | — |
| BigCodeBench Instruct | — | 19.5% |
| BigCodeBench Complete | — | 27.3% |
| ALE-Bench | 1,327 | — |
| HumanEval+ | — | 36% |
| MBPP+ | — | 42.1% |
Agentic & Tool Use Not comparable
Claude Sonnet 4.6: 39.1 (#28), Mistral 7B: —
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#45), Mistral 7B: 13.1 (#336)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| Chess Puzzles | 13% | 0% |
| LMArena Hard Prompts | 1484 | 1067 |
| DTBench | 89.9% | 42.5% |
| Epoch Capabilities Index | 152.24 | 112.21 |
| ARC-AGI-2 | 60.4% | — |
| NYT Connections (extended) | 80.9% | — |
| ARC-AGI-1 | 86.5% | — |
| CritPt | 3.1% | — |
| Thematic Generalization | 76.3% | — |
| Mystery Game Puzzles | 16% | — |
| LMCA | 46.5% | — |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| ForecastBench | 62 | — |
| HellaSwag | — | 81% |
| PIQA | — | 83% |
| WinoGrande | — | 75.3% |
Math Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 52.9 (#49), Mistral 7B: 8.1 (#325)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 85.8% | 0.3% |
| LMArena Math | 1462 | 1085 |
| ProofBench | 45% | — |
| MATH Level 5 | — | 3.7% |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |
| GSM8K | — | 54.4% |
Knowledge Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 51.7 (#65), Mistral 7B: 7.4 (#311)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| GPQA Diamond | 87.4% | 15.2% |
| LMArena Expert | 1500 | 1036 |
| SimpleQA Verified | 35.5% | — |
| Vectara Hallucination Rate | 10.6% | — |
| ARC (AI2) Challenge | — | 78.6% |
| BoolQ | — | 87.4% |
| MMLU | — | 62.5% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |
Multimodal Not comparable
Claude Sonnet 4.6: 38.0 (#68), Mistral 7B: —
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| LMArena Vision | 1283 | — |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 54.4 (#41), Mistral 7B: 25.8 (#283)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| LMArena Non-English | 1440 | 1012 |
| LMArena Chinese | 1491 | 1009 |
| LMArena French | 1465 | 1037 |
| LMArena German | 1428 | 987 |
| LMArena Japanese | 1420 | 878 |
| LMArena Russian | 1440 | 1018 |
| LMArena Spanish | 1464 | 1026 |
| LMArena Korean | 1411 | — |
Instruction Following Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 77.4 (#25), Mistral 7B: 54.2 (#280)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | 1475 | 1060 |
Long Context Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 45.3 (#44), Mistral 7B: 32.2 (#271)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| LMArena Longer Query | 1479 | 1060 |
Writing & Preference Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 70.2 (#22), Mistral 7B: 30.7 (#286)
| Benchmark | Claude Sonnet 4.6 | Mistral 7B |
|---|---|---|
| LMArena Text | 1458 | 1090 |
| LMArena Creative Writing | 1435 | 1068 |
| LMArena Multi-Turn | 1464 | 1062 |
| EQ-Bench Creative Writing | 1810 | — |
| EQ-Bench 4 | 1207 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than Mistral 7B?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 23.0 on the Noometry Index. Mistral 7B costs 24× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 4.6 or Mistral 7B?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; Claude Sonnet 4.6 lists at $3 and $15.
Is Claude Sonnet 4.6 or Mistral 7B better for coding?
Claude Sonnet 4.6 scores higher on coding benchmarks: 46.3 versus 26.4 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 4.6 does, with 1M tokens against 8K.
How many benchmarks do Claude Sonnet 4.6 and Mistral 7B share?
21 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and Mistral 7B has 37.