# Claude Opus 4.8 vs Mistral Large

> Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.9 on the Noometry Index. Mistral Large costs 3.3× less per token, which makes it the better buy when Claude Opus 4.8's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-8-vs-mistral-large
- Last updated: 2026-10-11
- Shared benchmarks: 29

## Summary

- They share 29 benchmarks with published results for both. Claude Opus 4.8 scores higher in 9 categories and Mistral Large in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Opus 4.8 leads 78.4 to 18.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 98.3% for Claude Opus 4.8 and 8.5% for Mistral Large.
- Mistral Large is cheaper at $2 / $6 per million input/output tokens, against $5 / $25 for Claude Opus 4.8.
- Claude Opus 4.8 accepts more context: 1M tokens versus 131K.
- Mistral Large has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 60.7 | 31.9 |
| Rank | 13 | 263 |
| Context | 1M | 131K |
| Input $/M | $5 | $2 |
| Output $/M | $25 | $6 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.8: 59.9 (#12)
- Mistral Large: 34.3 (#240)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| SciCode | 53.5% | 36.2% |
| LMArena Coding | 1490 | 1277 |
| ALE-Bench | 1,564 | 264.7 |
| DeepSWE | 59% | — |
| FrontierCode | 46.5% | — |
| LMArena WebDev | 1556 | — |
| GSO | 47.1% | — |
| WeirdML | 82.9% | — |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | — | 38.3% |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |

## Agentic & Tool Use

- Claude Opus 4.8: 47.6 (#11)
- Mistral Large: 28.6 (#89)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| APEX-Agents | 48.9% | — |
| Berkeley Function Calling Leaderboard | — | 38.4% |
| 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: 64.7 (#16)
- Mistral Large: 15.8 (#310)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| SimpleBench | 64.8% | 22.5% |
| CritPt | 20.9% | 0% |
| LMArena Hard Prompts | 1482 | 1257 |
| DTBench | 94.9% | 65.1% |
| LMCA | 57.5% | 16.7% |
| Epoch Capabilities Index | 158.21 | 128.52 |
| ForecastBench | 59.9 | 57.1 |
| ARC-AGI-2 | 72.1% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 91.1% | — |
| ARC-AGI-1 | 92.5% | — |
| Chess Puzzles | 34% | — |
| EnigmaEval | 23.5% | — |
| EBR-Bench | 28.6% | — |
| LiveBench Reasoning | — | 43.5% |
| Mystery Game Puzzles | 36% | — |
| LiveBench Data Analysis | — | 50.1% |
| Surface Evolver Bench | 87.5% | — |
| Bench to the Future 3 | 0.14 | — |
| LiveBench | — | 48.4% |

## Math

- Claude Opus 4.8: 78.4 (#13)
- Mistral Large: 18.2 (#291)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 98.3% | 8.5% |
| LMArena Math | 1487 | 1262 |
| FrontierMath (Feb 2025 set) | 47.2% | 0.3% |
| FrontierMath (Tiers 1-3) | 80% | — |
| FrontierMath Tier 4 | 56.1% | — |
| MathArena Final-Answer Competitions | 91.8% | — |
| ProofBench | 69% | — |
| Omni-MATH | — | 28.1% |
| LiveBench Math | — | 42.5% |
| MATH Level 5 | — | 50.3% |
| FrontierMath Tier 4 (v1) | 31.3% | — |

## Knowledge

- Claude Opus 4.8: 61.3 (#29)
- Mistral Large: 30.1 (#230)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| GPQA Diamond | 91% | 51.3% |
| LMArena Expert | 1502 | 1232 |
| SimpleQA Verified | 53% | — |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| GPQA (HELM) | — | 43.5% |
| MMLU | — | 80% |

## Multimodal

- Claude Opus 4.8: 42.9 (#26)
- Mistral Large: —

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| LMArena Vision | 1294 | — |
| Blueprint-Bench 2 | 14.5% | — |
| Furniture Assembly | 42.5% | — |
| LMArena Document | 1475 | — |

## Multilingual

- Claude Opus 4.8: 55.2 (#33)
- Mistral Large: 40.0 (#219)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| LMArena Non-English | 1450 | 1237 |
| LMArena Chinese | 1507 | 1240 |
| LMArena French | 1481 | 1325 |
| LMArena German | 1472 | 1254 |
| LMArena Japanese | 1440 | 1188 |
| LMArena Korean | 1432 | 1202 |
| LMArena Russian | 1474 | 1257 |
| LMArena Spanish | 1466 | 1268 |

## Instruction Following

- Claude Opus 4.8: 77.4 (#24)
- Mistral Large: 67.9 (#191)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| LMArena Instruction Following | 1476 | 1249 |
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |

## Long Context

- Claude Opus 4.8: 45.4 (#35)
- Mistral Large: 38.3 (#199)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1483 | 1261 |

## Writing & Preference

- Claude Opus 4.8: 72.0 (#16)
- Mistral Large: 40.7 (#242)

| Benchmark | Claude Opus 4.8 | Mistral Large |
|---|---|---|
| LMArena Text | 1461 | 1266 |
| LMArena Creative Writing | 1454 | 1243 |
| EQ-Bench Creative Writing | 1840 | 985 |
| LMArena Multi-Turn | 1476 | 1260 |
| Short-Story Creative Writing | — | 69% |
| WildBench | — | 80.1% |
| EQ-Bench 4 | 1281 | — |
| LiveBench Language | — | 39.4% |

## FAQ

### Is Claude Opus 4.8 better than Mistral Large?

Claude Opus 4.8 is the stronger model overall, scoring 60.7 to 31.9 on the Noometry Index. Mistral Large costs 3.3× 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 Large?

Mistral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Claude Opus 4.8 lists at $5 and $25.

### Is Claude Opus 4.8 or Mistral Large better for coding?

Claude Opus 4.8 scores higher on coding benchmarks: 59.9 versus 34.3 in the Noometry coding category.

### 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 Large share?

29 benchmarks have published results for both models. Claude Opus 4.8 has 65 scored results on Noometry and Mistral Large has 51.