Model comparison
Mistral Large vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 31.9 on the Noometry Index.
Last verified . 9 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 9 benchmarks with published results for both. Mistral Large scores higher in 1 category and Qwen3 14B in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 14B leads 38.6 to 18.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 8.5% for Mistral Large and 66.4% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $2 / $6 for Mistral Large.
Side by side
| Mistral Large | Qwen3 14B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.9 | 35.5 |
| Released | 2024-02-26 | 2025-04 |
| Weights | Open | Open |
| Context window | 131K | 131K |
| Max output | 16K | 8K |
| Input $ / M tokens | $2 | $0.35 |
| Output $ / M tokens | $6 | $1.40 |
| Results tracked | 51 | 12 |
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Category by category
Coding Qwen3 14B leads
Mistral Large: 34.3 (#240), Qwen3 14B: 37.3 (#195)
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| SciCode | 36.2% | 31.6% |
| BigCodeBench Instruct | 30% | — |
| LiveBench Coding | 47.1% | — |
| LMArena Coding | 1277 | — |
| BigCodeBench Complete | 38.3% | — |
| ALE-Bench | 264.7 | — |
| HumanEval+ | 62.2% | — |
| MBPP+ | 59.5% | — |
Agentic & Tool Use Qwen3 14B leads
Mistral Large: 28.6 (#89), Qwen3 14B: 29.6 (#83)
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 38.4% | 41% |
Reasoning Qwen3 14B leads
Mistral Large: 15.8 (#310), Qwen3 14B: 18.5 (#280)
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| CritPt | 0% | 0% |
| DTBench | 65.1% | 64% |
| LMCA | 16.7% | 18.2% |
| Epoch Capabilities Index | 128.52 | 138.23 |
| SimpleBench | 22.5% | — |
| Kagi LLM Benchmark | — | 49.1% |
| Chess Puzzles | — | 4% |
| LiveBench Reasoning | 43.5% | — |
| LMArena Hard Prompts | 1257 | — |
| LiveBench Data Analysis | 50.1% | — |
| ForecastBench | 57.1 | — |
| LiveBench | 48.4% | — |
Math Qwen3 14B leads
Mistral Large: 18.2 (#291), Qwen3 14B: 38.6 (#133)
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 8.5% | 66.4% |
| Omni-MATH | 28.1% | — |
| LiveBench Math | 42.5% | — |
| LMArena Math | 1262 | — |
| MATH Level 5 | 50.3% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Qwen3 14B leads
Mistral Large: 30.1 (#230), Qwen3 14B: 39.3 (#134)
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 51.3% | 63.8% |
| Vectara Hallucination Rate | 4.5% | 5.4% |
| MMLU-Pro | 59.9% | — |
| Confabulations | 21.4% | — |
| GPQA (HELM) | 43.5% | — |
| LMArena Expert | 1232 | — |
| MMLU | 80% | — |
Multilingual Not comparable
Mistral Large: 40.0 (#219), Qwen3 14B: —
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1237 | — |
| LMArena Chinese | 1240 | — |
| LMArena French | 1325 | — |
| LMArena German | 1254 | — |
| LMArena Japanese | 1188 | — |
| LMArena Korean | 1202 | — |
| LMArena Russian | 1257 | — |
| LMArena Spanish | 1268 | — |
Instruction Following Not comparable
Mistral Large: 67.9 (#191), Qwen3 14B: —
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| LiveBench Instruction Following | 67.9% | — |
| IFEval | 87.7% | — |
| LMArena Instruction Following | 1249 | — |
Long Context Too close to call
Mistral Large: 38.3 (#199), Qwen3 14B: 38.1 (#204)
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1261 | — |
Writing & Preference Not comparable
Mistral Large: 40.7 (#242), Qwen3 14B: —
| Benchmark | Mistral Large | Qwen3 14B |
|---|---|---|
| LMArena Text | 1266 | — |
| LMArena Creative Writing | 1243 | — |
| Short-Story Creative Writing | 69% | — |
| EQ-Bench Creative Writing | 985 | — |
| WildBench | 80.1% | — |
| LMArena Multi-Turn | 1260 | — |
| LiveBench Language | 39.4% | — |
Frequently asked questions
Is Mistral Large better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 31.9 on the Noometry Index.
Which is cheaper, Mistral Large or Qwen3 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Mistral Large lists at $2 and $6.
Is Mistral Large or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 34.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 131K tokens.
How many benchmarks do Mistral Large and Qwen3 14B share?
9 benchmarks have published results for both models. Mistral Large has 51 scored results on Noometry and Qwen3 14B has 12.