Model comparison
Mistral vs Qwen1.5 4b Chat
Mistral is the stronger model overall, scoring 29.9 to 28.8 on the Noometry Index.
Last verified . 13 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. Mistral scores higher in 6 categories and Qwen1.5 4b Chat in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral leads 37.0 to 23.8.
- Qwen1.5 4b Chat has downloadable open weights; the other is API-only.
Side by side
| Mistral | Qwen1.5 4b Chat | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 29.9 | 28.8 |
| Released | — | — |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 22 | 13 |
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Category by category
Coding Mistral leads
Mistral: 33.8 (#250), Qwen1.5 4b Chat: 29.1 (#308)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Coding | 1162 | 999 |
Reasoning Mistral leads
Mistral: 22.2 (#200), Qwen1.5 4b Chat: 18.5 (#279)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Hard Prompts | 1149 | 976 |
Math Qwen1.5 4b Chat leads
Mistral: 22.3 (#278), Qwen1.5 4b Chat: 30.4 (#234)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Math | 1180 | 1026 |
| Omni-MATH | 7.2% | — |
Knowledge Qwen1.5 4b Chat leads
Mistral: 16.6 (#288), Qwen1.5 4b Chat: 26.7 (#255)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Expert | 1125 | 980 |
| MMLU-Pro | 27.7% | — |
| GPQA (HELM) | 30.3% | — |
Multilingual Mistral leads
Mistral: 32.8 (#254), Qwen1.5 4b Chat: 24.1 (#290)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Non-English | 1129 | 979 |
| LMArena Chinese | 1109 | 1024 |
| LMArena German | 1155 | 902 |
| LMArena Russian | 1168 | 952 |
| LMArena French | 1180 | — |
| LMArena Japanese | 1013 | — |
| LMArena Korean | 1032 | — |
| LMArena Spanish | 1143 | — |
Instruction Following Mistral leads
Mistral: 52.6 (#288), Qwen1.5 4b Chat: 49.0 (#300)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Instruction Following | 1152 | 978 |
| IFEval | 56.8% | — |
Long Context Mistral leads
Mistral: 35.0 (#245), Qwen1.5 4b Chat: 30.1 (#290)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Longer Query | 1153 | 988 |
Writing & Preference Mistral leads
Mistral: 37.0 (#260), Qwen1.5 4b Chat: 23.8 (#309)
| Benchmark | Mistral | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Text | 1165 | 997 |
| LMArena Creative Writing | 1158 | 969 |
| LMArena Multi-Turn | 1147 | 977 |
| WildBench | 66% | — |
Frequently asked questions
Is Mistral better than Qwen1.5 4b Chat?
Mistral is the stronger model overall, scoring 29.9 to 28.8 on the Noometry Index.
Is Mistral or Qwen1.5 4b Chat better for coding?
Mistral scores higher on coding benchmarks: 33.8 versus 29.1 in the Noometry coding category.
How many benchmarks do Mistral and Qwen1.5 4b Chat share?
13 benchmarks have published results for both models. Mistral has 22 scored results on Noometry and Qwen1.5 4b Chat has 13.