Model comparison
Mistral Medium 3.5 vs Qwen2.5-Coder-32B
Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 4.0× less per token, which makes it the better buy when Mistral Medium 3.5's lead doesn't matter for your workload.
Last verified . 13 shared benchmarks.
Summary
- They share 13 benchmarks with published results for both. Mistral Medium 3.5 scores higher in 7 categories and Qwen2.5-Coder-32B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mistral Medium 3.5 leads 58.5 to 41.6.
- Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
- Mistral Medium 3.5 accepts more context: 262K tokens versus 33K.
Side by side
| Mistral Medium 3.5 | Qwen2.5-Coder-32B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 40.2 | 33.4 |
| Released | — | 2024-09-18 |
| Weights | Open | Open |
| Context window | 262K | 33K |
| Max output | 210K | 29K |
| Input $ / M tokens | $1.50 | $0.66 |
| Output $ / M tokens | $7.50 | $1 |
| Results tracked | 22 | 31 |
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Category by category
Coding Mistral Medium 3.5 leads
Mistral Medium 3.5: 36.0 (#213), Qwen2.5-Coder-32B: 22.6 (#333)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Coding | 1461 | 1276 |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| LMArena WebDev | 1264 | — |
| BigCodeBench Instruct | — | 49% |
| LiveBench Coding | — | 56.9% |
| BigCodeBench Complete | — | 58% |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |
Reasoning Qwen2.5-Coder-32B leads
Mistral Medium 3.5: 17.3 (#295), Qwen2.5-Coder-32B: 21.2 (#225)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Hard Prompts | 1436 | 1251 |
| Epoch Capabilities Index | 141.35 | 119.49 |
| Kagi LLM Benchmark | 41.4% | — |
| NYT Connections (extended) | 12.9% | — |
| LiveBench Reasoning | — | 42.1% |
| LiveBench Data Analysis | — | 49.9% |
| HellaSwag | — | 83% |
| LiveBench | — | 46.2% |
| WinoGrande | — | 80.8% |
Math Mistral Medium 3.5 leads
Mistral Medium 3.5: 39.1 (#113), Qwen2.5-Coder-32B: 33.3 (#204)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Math | 1431 | 1251 |
| LiveBench Math | — | 46.6% |
| GSM8K | — | 93% |
Knowledge Mistral Medium 3.5 leads
Mistral Medium 3.5: 40.0 (#126), Qwen2.5-Coder-32B: 33.4 (#203)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1432 | 1221 |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |
Multimodal Not comparable
Mistral Medium 3.5: 38.3 (#65), Qwen2.5-Coder-32B: —
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1223 | — |
Multilingual Mistral Medium 3.5 leads
Mistral Medium 3.5: 51.9 (#100), Qwen2.5-Coder-32B: 37.8 (#235)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1404 | 1205 |
| LMArena Chinese | 1442 | 1222 |
| LMArena Russian | 1395 | 1228 |
| LMArena French | 1448 | — |
| LMArena German | 1451 | — |
| LMArena Korean | 1385 | — |
| LMArena Spanish | 1409 | — |
Instruction Following Mistral Medium 3.5 leads
Mistral Medium 3.5: 74.6 (#90), Qwen2.5-Coder-32B: 61.4 (#245)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Instruction Following | 1415 | 1223 |
| LiveBench Instruction Following | — | 58.7% |
Long Context Mistral Medium 3.5 leads
Mistral Medium 3.5: 43.2 (#103), Qwen2.5-Coder-32B: 38.0 (#208)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1415 | 1251 |
Writing & Preference Mistral Medium 3.5 leads
Mistral Medium 3.5: 58.5 (#117), Qwen2.5-Coder-32B: 41.6 (#240)
| Benchmark | Mistral Medium 3.5 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1421 | 1230 |
| LMArena Creative Writing | 1374 | 1174 |
| LMArena Multi-Turn | 1423 | 1222 |
| EQ-Bench 4 | 993 | — |
| LiveBench Language | — | 23.3% |
Frequently asked questions
Is Mistral Medium 3.5 better than Qwen2.5-Coder-32B?
Mistral Medium 3.5 is the stronger model overall, scoring 40.2 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 4.0× less per token, which makes it the better buy when Mistral Medium 3.5's lead doesn't matter for your workload.
Which is cheaper, Mistral Medium 3.5 or Qwen2.5-Coder-32B?
Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.
Is Mistral Medium 3.5 or Qwen2.5-Coder-32B better for coding?
Mistral Medium 3.5 scores higher on coding benchmarks: 36.0 versus 22.6 in the Noometry coding category.
Which has the bigger context window?
Mistral Medium 3.5 does, with 262K tokens against 33K.
How many benchmarks do Mistral Medium 3.5 and Qwen2.5-Coder-32B share?
13 benchmarks have published results for both models. Mistral Medium 3.5 has 22 scored results on Noometry and Qwen2.5-Coder-32B has 31.