Model comparison
Mistral 7B vs Qwen3-30B-A3B
Qwen3-30B-A3B is the stronger model overall, scoring 38.5 to 22.9 on the Noometry Index.
Last verified . 21 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 21 benchmarks with published results for both. Mistral 7B scores higher in 1 category and Qwen3-30B-A3B in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-30B-A3B leads 41.7 to 7.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.3% for Mistral 7B and 70.3% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.25 / $0.25 for Mistral 7B.
- Qwen3-30B-A3B accepts more context: 41K tokens versus 8K.
Side by side
| Mistral 7B | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 22.9 | 38.5 |
| Released | 2023-09-27 | 2025-04-28 |
| Weights | Open | Open |
| Context window | 8K | 41K |
| Max output | 8K | 16K |
| Input $ / M tokens | $0.25 | $0.12 |
| Output $ / M tokens | $0.25 | $0.50 |
| Results tracked | 37 | 32 |
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Category by category
Coding Qwen3-30B-A3B leads
Mistral 7B: 25.9 (#321), Qwen3-30B-A3B: 37.0 (#188)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Coding | 1082 | 1416 |
| SciCode | — | 33.3% |
| WeirdML | — | 29.8% |
| BigCodeBench Instruct | 19.5% | — |
| BigCodeBench Complete | 27.3% | — |
| HumanEval+ | 36% | — |
| MBPP+ | 42.1% | — |
Agentic & Tool Use Not comparable
Mistral 7B: —, Qwen3-30B-A3B: 29.5 (#75)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
Reasoning Qwen3-30B-A3B leads
Mistral 7B: 12.6 (#331), Qwen3-30B-A3B: 21.6 (#193)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| Chess Puzzles | 0% | 8% |
| LMArena Hard Prompts | 1067 | 1398 |
| DTBench | 42.5% | 69.3% |
| Epoch Capabilities Index | 111.97 | 139.63 |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| LMCA | — | 22.4% |
| Adversarial NLI | 47.1% | — |
| BIG-Bench Hard | 56.1% | — |
| HellaSwag | 81% | — |
| PIQA | 83% | — |
| WinoGrande | 75.3% | — |
Math Qwen3-30B-A3B leads
Mistral 7B: 7.6 (#319), Qwen3-30B-A3B: 36.0 (#133)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.3% | 70.3% |
| LMArena Math | 1085 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
| MATH Level 5 | 3.7% | — |
| GSM8K | 54.4% | — |
Knowledge Qwen3-30B-A3B leads
Mistral 7B: 7.3 (#306), Qwen3-30B-A3B: 41.7 (#96)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 15.2% | 70.1% |
| LMArena Expert | 1036 | 1395 |
| Confabulations | — | 12.3% |
| ARC (AI2) Challenge | 78.6% | — |
| BoolQ | 87.4% | — |
| MMLU | 62.5% | — |
| OpenBookQA | 79.8% | — |
| TriviaQA | 75.2% | — |
Multilingual Qwen3-30B-A3B leads
Mistral 7B: 26.0 (#278), Qwen3-30B-A3B: 49.8 (#126)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1012 | 1372 |
| LMArena Chinese | 1009 | 1434 |
| LMArena French | 1036 | 1419 |
| LMArena German | 987 | 1379 |
| LMArena Japanese | 878 | 1338 |
| LMArena Russian | 1018 | 1369 |
| LMArena Spanish | 1026 | 1403 |
| LMArena Korean | — | 1333 |
Instruction Following Qwen3-30B-A3B leads
Mistral 7B: 54.5 (#275), Qwen3-30B-A3B: 72.2 (#137)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1060 | 1364 |
Long Context Mistral 7B leads
Mistral 7B: 32.2 (#266), Qwen3-30B-A3B: 31.0 (#278)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1060 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Qwen3-30B-A3B leads
Mistral 7B: 30.9 (#281), Qwen3-30B-A3B: 55.9 (#138)
| Benchmark | Mistral 7B | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1090 | 1384 |
| LMArena Creative Writing | 1068 | 1318 |
| LMArena Multi-Turn | 1062 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
Frequently asked questions
Is Mistral 7B better than Qwen3-30B-A3B?
Qwen3-30B-A3B is the stronger model overall, scoring 38.5 to 22.9 on the Noometry Index.
Which is cheaper, Mistral 7B or Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; Mistral 7B lists at $0.25 and $0.25.
Is Mistral 7B or Qwen3-30B-A3B better for coding?
Qwen3-30B-A3B scores higher on coding benchmarks: 37.0 versus 25.9 in the Noometry coding category.
Which has the bigger context window?
Qwen3-30B-A3B does, with 41K tokens against 8K.
How many benchmarks do Mistral 7B and Qwen3-30B-A3B share?
21 benchmarks have published results for both models. Mistral 7B has 37 scored results on Noometry and Qwen3-30B-A3B has 32.