Model comparison
Claude Opus 4.8 vs Mistral Medium 3.1
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.9 on the Noometry Index. Mistral Medium 3.1 costs 13× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Mistral AISummary
- They share 2 benchmarks with published results for both. Claude Opus 4.8 scores higher in 2 categories and Mistral Medium 3.1 in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.8 leads 64.7 to 10.6.
- The biggest single-benchmark swing is NYT Connections (extended): 91.1% for Claude Opus 4.8 and 6.5% for Mistral Medium 3.1.
- Mistral Medium 3.1 is cheaper at $0.40 / $2 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- Claude Opus 4.8 accepts more context: 1M tokens versus 131K.
Side by side
| Claude Opus 4.8 | Mistral Medium 3.1 | |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 60.7 | 31.9 |
| Released | 2026-05-28 | — |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 131K |
| Max output | 128K | 105K |
| Input $ / M tokens | $5 | $0.40 |
| Output $ / M tokens | $25 | $2 |
| Results tracked | 65 | 3 |
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Category by category
Coding Not comparable
Claude Opus 4.8: 59.9 (#12), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| LMArena WebDev | 1556 | — |
| SciCode | 53.5% | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| LMArena Coding | 1490 | — |
| ALE-Bench | 1,564 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.8: 47.6 (#11), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| APEX-Agents | 48.9% | — |
| OSWorld 2.0 | 20.6% | — |
| Remote Labor Index | 8.3% | — |
| τ²-bench Banking | 39.7% | — |
| DeepResearch Bench | 50.2% | — |
| PostTrainBench | 33.8% | — |
| GBAEval | 70.9% | — |
| GDP.pdf | 24% | — |
| LMArena Search | 1204 | — |
| Vending-Bench 2 | 5,787 | — |
Reasoning Claude Opus 4.8 leads
Claude Opus 4.8: 64.7 (#16), Mistral Medium 3.1: 10.6 (#341)
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| NYT Connections (extended) | 91.1% | 6.5% |
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 64.8% | — |
| Kagi LLM Benchmark | 88.8% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 20.9% | — |
| Chess Puzzles | 34% | — |
| EnigmaEval | 23.5% | — |
| Thematic Generalization | — | 20.3% |
| EBR-Bench | 28.6% | — |
| LMArena Hard Prompts | 1482 | — |
| Mystery Game Puzzles | 36% | — |
| DTBench | 94.9% | — |
| LMCA | 57.5% | — |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 158.21 | — |
| ForecastBench | 59.9 | — |
Math Not comparable
Claude Opus 4.8: 78.4 (#13), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 80% | — |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 69% | — |
| LMArena Math | 1487 | — |
| FrontierMath (Feb 2025 set) | 47.2% | — |
| FrontierMath Tier 4 (v1) | 31.3% | — |
Knowledge Not comparable
Claude Opus 4.8: 61.3 (#29), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| GPQA Diamond | 91% | — |
| SimpleQA Verified | 53% | — |
| LMArena Expert | 1502 | — |
Multimodal Not comparable
Claude Opus 4.8: 42.9 (#26), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |
Multilingual Not comparable
Claude Opus 4.8: 55.2 (#33), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| LMArena Non-English | 1450 | — |
| LMArena Chinese | 1507 | — |
| LMArena French | 1481 | — |
| LMArena German | 1472 | — |
| LMArena Japanese | 1440 | — |
| LMArena Korean | 1432 | — |
| LMArena Russian | 1474 | — |
| LMArena Spanish | 1466 | — |
Instruction Following Not comparable
Claude Opus 4.8: 77.4 (#24), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| LMArena Instruction Following | 1476 | — |
Long Context Not comparable
Claude Opus 4.8: 45.4 (#35), Mistral Medium 3.1: —
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| LMArena Longer Query | 1483 | — |
Writing & Preference Claude Opus 4.8 leads
Claude Opus 4.8: 72.0 (#16), Mistral Medium 3.1: 55.5 (#145)
| Benchmark | Claude Opus 4.8 | Mistral Medium 3.1 |
|---|---|---|
| EQ-Bench Creative Writing | 1840 | 1476 |
| LMArena Text | 1461 | — |
| LMArena Creative Writing | 1454 | — |
| EQ-Bench 4 | 1281 | — |
| LMArena Multi-Turn | 1476 | — |
Frequently asked questions
Is Claude Opus 4.8 better than Mistral Medium 3.1?
Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.9 on the Noometry Index. Mistral Medium 3.1 costs 13× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.8 or Mistral Medium 3.1?
Mistral Medium 3.1 is cheaper. It lists at $0.40 per million input tokens and $2 per million output tokens; Claude Opus 4.8 lists at $5 and $25.
Which has the bigger context window?
Claude Opus 4.8 does, with 1M tokens against 131K.
How many benchmarks do Claude Opus 4.8 and Mistral Medium 3.1 share?
2 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Mistral Medium 3.1 has 3.