Model comparison
Mistral Medium vs Qwen3-Coder 480B-A35B Instruct
Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 36.3 on the Noometry Index.
Last verified . 20 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 20 benchmarks with published results for both. Mistral Medium scores higher in 5 categories and Qwen3-Coder 480B-A35B Instruct in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-Coder 480B-A35B Instruct leads 37.0 to 25.0.
- Both cost about the same: $1.50 input and $7.50 output per million tokens.
Side by side
| Mistral Medium | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 36.3 | 38.1 |
| Released | 2023-12-11 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 262K | 66K |
| Input $ / M tokens | $1.50 | $1.50 |
| Output $ / M tokens | $7.50 | $7.50 |
| Results tracked | 36 | 25 |
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Category by category
Coding Qwen3-Coder 480B-A35B Instruct leads
Mistral Medium: 34.2 (#243), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 43.7% | 41.2% |
| LMArena Coding | 1434 | 1412 |
| ALE-Bench | 763.98 | 461.45 |
| FrontierCode | 8% | — |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| SciCode | 40.2% | — |
| GSO | — | 4.9% |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Mistral Medium leads
Mistral Medium: 28.3 (#90), Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| Berkeley Function Calling Leaderboard | 37.7% | — |
Reasoning Qwen3-Coder 480B-A35B Instruct leads
Mistral Medium: 24.0 (#167), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 50% | 49.5% |
| LMArena Hard Prompts | 1426 | 1372 |
| CritPt | 0% | — |
| DTBench | 75.5% | — |
| LMCA | 26.1% | — |
| Surface Evolver Bench | 26.9% | — |
Math Qwen3-Coder 480B-A35B Instruct leads
Mistral Medium: 28.1 (#245), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1408 | 1365 |
| OTIS Mock AIME 2024-2025 | 32.2% | — |
| ProofBench | 9% | — |
| MATH Level 5 | 81.6% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Qwen3-Coder 480B-A35B Instruct leads
Mistral Medium: 25.0 (#265), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1408 | 1338 |
| GPQA Diamond | 59.5% | — |
| Humanity's Last Exam | 4.5% | — |
| Vectara Hallucination Rate | 22.7% | — |
Multimodal Not comparable
Mistral Medium: 35.3 (#88), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1172 | — |
Multilingual Mistral Medium leads
Mistral Medium: 52.1 (#91), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1408 | 1346 |
| LMArena Chinese | 1447 | 1357 |
| LMArena French | 1459 | 1398 |
| LMArena German | 1432 | 1325 |
| LMArena Japanese | 1378 | 1310 |
| LMArena Korean | 1380 | 1305 |
| LMArena Russian | 1411 | 1366 |
| LMArena Spanish | 1433 | 1360 |
Instruction Following Mistral Medium leads
Mistral Medium: 73.7 (#116), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1398 | 1355 |
Long Context Too close to call
Mistral Medium: 42.9 (#114), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1406 | 1378 |
Writing & Preference Mistral Medium leads
Mistral Medium: 60.0 (#103), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | Mistral Medium | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1424 | 1357 |
| LMArena Creative Writing | 1391 | 1333 |
| LMArena Multi-Turn | 1418 | 1365 |
| Short-Story Creative Writing | 77.3% | — |
Frequently asked questions
Is Mistral Medium better than Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 36.3 on the Noometry Index.
Which is cheaper, Mistral Medium or Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; Mistral Medium lists at $1.50 and $7.50.
Is Mistral Medium or Qwen3-Coder 480B-A35B Instruct better for coding?
Qwen3-Coder 480B-A35B Instruct scores higher on coding benchmarks: 35.5 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Mistral Medium and Qwen3-Coder 480B-A35B Instruct share?
20 benchmarks have published results for both models. Mistral Medium has 36 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.