# Mistral 7B vs o3

> o3 is the stronger model overall, scoring 47.5 to 23.0 on the Noometry Index. Mistral 7B costs 14× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/mistral-7b-vs-o3
- Last updated: 2026-10-11
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Mistral 7B scores higher in 0 categories and o3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o3 leads 54.6 to 7.4.
- The biggest single-benchmark swing is MATH Level 5: 3.7% for Mistral 7B and 97.8% for o3.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $2 / $8 for o3.
- o3 accepts more context: 200K tokens versus 8K.
- Mistral 7B has downloadable open weights; the other is API-only.

## Snapshot

| | Mistral 7B | o3 |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 23.0 | 47.5 |
| Rank | 351 | 61 |
| Context | 8K | 200K |
| Input $/M | $0.25 | $2 |
| Output $/M | $0.25 | $8 |
| Weights | Open | Proprietary |

## Coding

- Mistral 7B: 26.4 (#326)
- o3: 46.8 (#64)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Coding | 1082 | 1408 |
| SWE-bench Verified | — | 62.3% |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| BigCodeBench Instruct | 19.5% | — |
| BigCodeBench Complete | 27.3% | — |
| CadEval | — | 74% |
| ALE-Bench | — | 933.55 |
| HumanEval+ | 36% | — |
| MBPP+ | 42.1% | — |

## Agentic & Tool Use

- Mistral 7B: —
- o3: 34.5 (#44)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |

## Reasoning

- Mistral 7B: 13.1 (#336)
- o3: 32.0 (#78)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| Chess Puzzles | 0% | 38% |
| LMArena Hard Prompts | 1067 | 1402 |
| DTBench | 42.5% | 84.8% |
| Epoch Capabilities Index | 112.21 | 146.86 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| LMCA | — | 39.7% |
| Adversarial NLI | 47.1% | — |
| BIG-Bench Hard | 56.1% | — |
| ForecastBench | — | 62.5 |
| HellaSwag | 81% | — |
| PIQA | 83% | — |
| WinoGrande | 75.3% | — |

## Math

- Mistral 7B: 8.1 (#325)
- o3: 50.2 (#58)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.3% | 84.4% |
| LMArena Math | 1085 | 1426 |
| MATH Level 5 | 3.7% | 97.8% |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| Omni-MATH | — | 71.4% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
| GSM8K | 54.4% | — |

## Knowledge

- Mistral 7B: 7.4 (#311)
- o3: 54.6 (#52)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| GPQA Diamond | 15.2% | 81.8% |
| LMArena Expert | 1036 | 1402 |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
| ARC (AI2) Challenge | 78.6% | — |
| BoolQ | 87.4% | — |
| MMLU | 62.5% | — |
| OpenBookQA | 79.8% | — |
| TriviaQA | 75.2% | — |

## Multimodal

- Mistral 7B: —
- o3: 41.4 (#36)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |

## Multilingual

- Mistral 7B: 25.8 (#283)
- o3: 51.7 (#105)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Non-English | 1012 | 1401 |
| LMArena Chinese | 1009 | 1437 |
| LMArena French | 1037 | 1430 |
| LMArena German | 987 | 1420 |
| LMArena Japanese | 878 | 1403 |
| LMArena Russian | 1018 | 1406 |
| LMArena Spanish | 1026 | 1395 |
| LMArena Korean | — | 1370 |

## Instruction Following

- Mistral 7B: 54.2 (#280)
- o3: 72.8 (#127)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Instruction Following | 1060 | 1368 |
| IFEval | — | 86.9% |

## Long Context

- Mistral 7B: 32.2 (#271)
- o3: 53.3 (#6)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Longer Query | 1060 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |

## Writing & Preference

- Mistral 7B: 30.7 (#286)
- o3: 63.5 (#64)

| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Text | 1090 | 1410 |
| LMArena Creative Writing | 1068 | 1359 |
| LMArena Multi-Turn | 1062 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |

## FAQ

### Is Mistral 7B better than o3?

o3 is the stronger model overall, scoring 47.5 to 23.0 on the Noometry Index. Mistral 7B costs 14× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.

### Which is cheaper, Mistral 7B or o3?

Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; o3 lists at $2 and $8.

### Is Mistral 7B or o3 better for coding?

o3 scores higher on coding benchmarks: 46.8 versus 26.4 in the Noometry coding category.

### Which has the bigger context window?

o3 does, with 200K tokens against 8K.

### How many benchmarks do Mistral 7B and o3 share?

22 benchmarks have published results for both models. Mistral 7B has 37 scored results on Noometry and o3 has 63.