Model comparison
Mistral Medium vs Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 36.3 on the Noometry Index.
Last verified . 19 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 19 benchmarks with published results for both. Mistral Medium scores higher in 4 categories and Qwen3-Next 80B-A3B Instruct in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-Next 80B-A3B Instruct leads 41.8 to 25.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 50% for Mistral Medium and 66.7% for Qwen3-Next 80B-A3B Instruct.
- Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 / $2 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
- Mistral Medium accepts more context: 262K tokens versus 131K.
Side by side
| Mistral Medium | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 36.3 | 43.0 |
| Released | 2023-12-11 | 2025-09 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 33K |
| Input $ / M tokens | $1.50 | $0.50 |
| Output $ / M tokens | $7.50 | $2 |
| Results tracked | 36 | 25 |
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Category by category
Coding Qwen3-Next 80B-A3B Instruct leads
Mistral Medium: 34.2 (#243), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1434 | 1440 |
| FrontierCode | 8% | — |
| SciCode | 40.2% | — |
| WeirdML | 43.7% | — |
| ALE-Bench | 763.98 | — |
Agentic & Tool Use Not comparable
Mistral Medium: 28.3 (#90), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.7% | — |
Reasoning Qwen3-Next 80B-A3B Instruct leads
Mistral Medium: 24.0 (#167), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 50% | 66.7% |
| LMArena Hard Prompts | 1426 | 1428 |
| CritPt | 0% | — |
| DTBench | 75.5% | — |
| LMCA | 26.1% | — |
| Surface Evolver Bench | 26.9% | — |
Math Qwen3-Next 80B-A3B Instruct leads
Mistral Medium: 28.1 (#245), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Math | 1408 | 1440 |
| OTIS Mock AIME 2024-2025 | 32.2% | — |
| ProofBench | 9% | — |
| Omni-MATH | — | 46.7% |
| MATH Level 5 | 81.6% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Qwen3-Next 80B-A3B Instruct leads
Mistral Medium: 25.0 (#265), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Vectara Hallucination Rate | 22.7% | 9.3% |
| LMArena Expert | 1408 | 1417 |
| GPQA Diamond | 59.5% | — |
| Humanity's Last Exam | 4.5% | — |
| MMLU-Pro | — | 78.6% |
| GPQA (HELM) | — | 63% |
Multimodal Not comparable
Mistral Medium: 35.3 (#88), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Vision | 1172 | — |
Multilingual Too close to call
Mistral Medium: 52.1 (#91), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1408 | 1407 |
| LMArena Chinese | 1447 | 1460 |
| LMArena French | 1459 | 1413 |
| LMArena German | 1432 | 1417 |
| LMArena Japanese | 1378 | 1395 |
| LMArena Korean | 1380 | 1364 |
| LMArena Russian | 1411 | 1404 |
| LMArena Spanish | 1433 | 1435 |
Instruction Following Mistral Medium leads
Mistral Medium: 73.7 (#116), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Instruction Following | 1398 | 1389 |
| IFEval | — | 81% |
Long Context Mistral Medium leads
Mistral Medium: 42.9 (#114), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Longer Query | 1406 | 1403 |
| Fiction.LiveBench | — | 55.6% |
Writing & Preference Mistral Medium leads
Mistral Medium: 60.0 (#103), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | Mistral Medium | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1424 | 1417 |
| LMArena Creative Writing | 1391 | 1334 |
| LMArena Multi-Turn | 1418 | 1416 |
| Short-Story Creative Writing | 77.3% | — |
| WildBench | — | 80.7% |
Frequently asked questions
Is Mistral Medium better than Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 36.3 on the Noometry Index.
Which is cheaper, Mistral Medium or Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is cheaper. It lists at $0.50 per million input tokens and $2 per million output tokens; Mistral Medium lists at $1.50 and $7.50.
Is Mistral Medium or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3-Next 80B-A3B Instruct scores higher on coding benchmarks: 42.5 versus 34.2 in the Noometry coding category.
Which has the bigger context window?
Mistral Medium does, with 262K tokens against 131K.
How many benchmarks do Mistral Medium and Qwen3-Next 80B-A3B Instruct share?
19 benchmarks have published results for both models. Mistral Medium has 36 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.