Model comparison
Mistral 7B vs Qwen2.5 7B Instruct
Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 23.0 on the Noometry Index.
Last verified . 8 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 8 benchmarks with published results for both. Mistral 7B scores higher in 0 categories and Qwen2.5 7B Instruct in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen2.5 7B Instruct leads 48.8 to 30.7.
- The biggest single-benchmark swing is GPQA Diamond: 15.2% for Mistral 7B and 35.5% for Qwen2.5 7B Instruct.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $0.17 / $0.70 for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct accepts more context: 131K tokens versus 8K.
Side by side
| Mistral 7B | Qwen2.5 7B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 23.0 | 29.0 |
| Released | 2023-09-27 | 2024-09 |
| Weights | Open | Open |
| Context window | 8K | 131K |
| Max output | 8K | 8K |
| Input $ / M tokens | $0.25 | $0.17 |
| Output $ / M tokens | $0.25 | $0.70 |
| Results tracked | 37 | 15 |
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Category by category
Coding Qwen2.5 7B Instruct leads
Mistral 7B: 26.4 (#326), Qwen2.5 7B Instruct: 36.5 (#208)
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| BigCodeBench Instruct | 19.5% | 37.6% |
| BigCodeBench Complete | 27.3% | 46.1% |
| LMArena Coding | 1082 | — |
| HumanEval+ | 36% | — |
| MBPP+ | 42.1% | — |
Agentic & Tool Use Not comparable
Mistral 7B: —, Qwen2.5 7B Instruct: 23.8 (#124)
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| BALROG | — | 7.8% |
Reasoning Qwen2.5 7B Instruct leads
Mistral 7B: 13.1 (#336), Qwen2.5 7B Instruct: 14.8 (#322)
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| DTBench | 42.5% | 47.7% |
| Epoch Capabilities Index | 112.21 | 118.51 |
| LMArena Hard Prompts | 1067 | — |
| LMCA | — | 6.4% |
| Adversarial NLI | 47.1% | — |
| BIG-Bench Hard | 56.1% | — |
| HellaSwag | 81% | — |
| PIQA | 83% | — |
| WinoGrande | 75.3% | — |
Math Qwen2.5 7B Instruct leads
Mistral 7B: 8.1 (#325), Qwen2.5 7B Instruct: 12.6 (#306)
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.3% | 2.5% |
| Omni-MATH | — | 29.4% |
| LMArena Math | 1085 | — |
| MATH Level 5 | 3.7% | — |
| GSM8K | 54.4% | — |
Knowledge Qwen2.5 7B Instruct leads
Mistral 7B: 7.4 (#311), Qwen2.5 7B Instruct: 17.0 (#286)
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 15.2% | 35.5% |
| MMLU | 62.5% | 72.9% |
| MMLU-Pro | — | 53.9% |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1036 | — |
| ARC (AI2) Challenge | 78.6% | — |
| BoolQ | 87.4% | — |
| OpenBookQA | 79.8% | — |
| TriviaQA | 75.2% | — |
Multilingual Not comparable
Mistral 7B: 25.8 (#283), Qwen2.5 7B Instruct: —
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1012 | — |
| LMArena Chinese | 1009 | — |
| LMArena French | 1037 | — |
| LMArena German | 987 | — |
| LMArena Japanese | 878 | — |
| LMArena Russian | 1018 | — |
| LMArena Spanish | 1026 | — |
Instruction Following Qwen2.5 7B Instruct leads
Mistral 7B: 54.2 (#280), Qwen2.5 7B Instruct: 63.2 (#231)
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1060 | — |
Long Context Not comparable
Mistral 7B: 32.2 (#271), Qwen2.5 7B Instruct: —
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1060 | — |
Writing & Preference Qwen2.5 7B Instruct leads
Mistral 7B: 30.7 (#286), Qwen2.5 7B Instruct: 48.8 (#195)
| Benchmark | Mistral 7B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1090 | — |
| LMArena Creative Writing | 1068 | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1062 | — |
Frequently asked questions
Is Mistral 7B better than Qwen2.5 7B Instruct?
Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 23.0 on the Noometry Index.
Which is cheaper, Mistral 7B or Qwen2.5 7B Instruct?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; Qwen2.5 7B Instruct lists at $0.17 and $0.70.
Is Mistral 7B or Qwen2.5 7B Instruct better for coding?
Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 26.4 in the Noometry coding category.
Which has the bigger context window?
Qwen2.5 7B Instruct does, with 131K tokens against 8K.
How many benchmarks do Mistral 7B and Qwen2.5 7B Instruct share?
8 benchmarks have published results for both models. Mistral 7B has 37 scored results on Noometry and Qwen2.5 7B Instruct has 15.