Model comparison
Mistral Large vs Qwen1.5 4b Chat
Mistral Large is the stronger model overall, scoring 31.9 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 Large 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 instruction following, where Mistral Large leads 67.9 to 49.0.
Side by side
| Mistral Large | Qwen1.5 4b Chat | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.9 | 28.8 |
| Released | 2024-02-26 | — |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 16K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $6 | — |
| Results tracked | 51 | 13 |
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Category by category
Coding Mistral Large leads
Mistral Large: 34.3 (#240), Qwen1.5 4b Chat: 29.1 (#308)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Coding | 1277 | 999 |
| SciCode | 36.2% | — |
| BigCodeBench Instruct | 30% | — |
| LiveBench Coding | 47.1% | — |
| BigCodeBench Complete | 38.3% | — |
| ALE-Bench | 264.7 | — |
| HumanEval+ | 62.2% | — |
| MBPP+ | 59.5% | — |
Agentic & Tool Use Not comparable
Mistral Large: 28.6 (#89), Qwen1.5 4b Chat: —
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| Berkeley Function Calling Leaderboard | 38.4% | — |
Reasoning Qwen1.5 4b Chat leads
Mistral Large: 15.8 (#310), Qwen1.5 4b Chat: 18.5 (#279)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Hard Prompts | 1257 | 976 |
| SimpleBench | 22.5% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | 43.5% | — |
| DTBench | 65.1% | — |
| LiveBench Data Analysis | 50.1% | — |
| LMCA | 16.7% | — |
| Epoch Capabilities Index | 128.52 | — |
| ForecastBench | 57.1 | — |
| LiveBench | 48.4% | — |
Math Qwen1.5 4b Chat leads
Mistral Large: 18.2 (#291), Qwen1.5 4b Chat: 30.4 (#234)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Math | 1262 | 1026 |
| OTIS Mock AIME 2024-2025 | 8.5% | — |
| Omni-MATH | 28.1% | — |
| LiveBench Math | 42.5% | — |
| MATH Level 5 | 50.3% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Mistral Large leads
Mistral Large: 30.1 (#230), Qwen1.5 4b Chat: 26.7 (#255)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Expert | 1232 | 980 |
| GPQA Diamond | 51.3% | — |
| MMLU-Pro | 59.9% | — |
| Confabulations | 21.4% | — |
| Vectara Hallucination Rate | 4.5% | — |
| GPQA (HELM) | 43.5% | — |
| MMLU | 80% | — |
Multilingual Mistral Large leads
Mistral Large: 40.0 (#219), Qwen1.5 4b Chat: 24.1 (#290)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Non-English | 1237 | 979 |
| LMArena Chinese | 1240 | 1024 |
| LMArena German | 1254 | 902 |
| LMArena Russian | 1257 | 952 |
| LMArena French | 1325 | — |
| LMArena Japanese | 1188 | — |
| LMArena Korean | 1202 | — |
| LMArena Spanish | 1268 | — |
Instruction Following Mistral Large leads
Mistral Large: 67.9 (#191), Qwen1.5 4b Chat: 49.0 (#300)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Instruction Following | 1249 | 978 |
| LiveBench Instruction Following | 67.9% | — |
| IFEval | 87.7% | — |
Long Context Mistral Large leads
Mistral Large: 38.3 (#199), Qwen1.5 4b Chat: 30.1 (#290)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Longer Query | 1261 | 988 |
Writing & Preference Mistral Large leads
Mistral Large: 40.7 (#242), Qwen1.5 4b Chat: 23.8 (#309)
| Benchmark | Mistral Large | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Text | 1266 | 997 |
| LMArena Creative Writing | 1243 | 969 |
| LMArena Multi-Turn | 1260 | 977 |
| Short-Story Creative Writing | 69% | — |
| EQ-Bench Creative Writing | 985 | — |
| WildBench | 80.1% | — |
| LiveBench Language | 39.4% | — |
Frequently asked questions
Is Mistral Large better than Qwen1.5 4b Chat?
Mistral Large is the stronger model overall, scoring 31.9 to 28.8 on the Noometry Index.
Is Mistral Large or Qwen1.5 4b Chat better for coding?
Mistral Large scores higher on coding benchmarks: 34.3 versus 29.1 in the Noometry coding category.
How many benchmarks do Mistral Large and Qwen1.5 4b Chat share?
13 benchmarks have published results for both models. Mistral Large has 51 scored results on Noometry and Qwen1.5 4b Chat has 13.