Model comparison
Mistral Small vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 33.4 on the Noometry Index. Mistral Small costs 2.3× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Last verified . 9 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 9 benchmarks with published results for both. Mistral Small scores higher in 2 categories and Qwen3 14B in 4 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 14B leads 38.6 to 16.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 5.8% for Mistral Small and 66.4% for Qwen3 14B.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
- Mistral Small accepts more context: 262K tokens versus 131K.
Side by side
| Mistral Small | Qwen3 14B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 33.4 | 35.5 |
| Released | 2024-02-26 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 256K | 8K |
| Input $ / M tokens | $0.15 | $0.35 |
| Output $ / M tokens | $0.60 | $1.40 |
| Results tracked | 39 | 12 |
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Category by category
Coding Qwen3 14B leads
Mistral Small: 34.0 (#247), Qwen3 14B: 37.3 (#195)
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| SciCode | 26.5% | 31.6% |
| BigCodeBench Instruct | 36.1% | — |
| LiveBench Coding | 36.2% | — |
| LMArena Coding | 1362 | — |
| BigCodeBench Complete | 46.6% | — |
| ALE-Bench | 497.62 | — |
Agentic & Tool Use Qwen3 14B leads
Mistral Small: 28.1 (#93), Qwen3 14B: 29.6 (#83)
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.1% | 41% |
Reasoning Mistral Small leads
Mistral Small: 19.8 (#250), Qwen3 14B: 18.5 (#280)
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 37.8% | 49.1% |
| CritPt | 0% | 0% |
| DTBench | 70.9% | 64% |
| LMCA | 20.6% | 18.2% |
| Chess Puzzles | — | 4% |
| LiveBench Reasoning | 44.8% | — |
| LMArena Hard Prompts | 1335 | — |
| LiveBench Data Analysis | 53.7% | — |
| Epoch Capabilities Index | — | 138.23 |
| LiveBench | 44% | — |
Math Qwen3 14B leads
Mistral Small: 16.4 (#293), Qwen3 14B: 38.6 (#133)
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.8% | 66.4% |
| LiveBench Math | 39.9% | — |
| LMArena Math | 1341 | — |
| MATH Level 5 | 46.8% | — |
Knowledge Qwen3 14B leads
Mistral Small: 31.0 (#222), Qwen3 14B: 39.3 (#134)
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 47.5% | 63.8% |
| Vectara Hallucination Rate | 5.1% | 5.4% |
| LMArena Expert | 1291 | — |
| MMLU | 68.7% | — |
Multimodal Not comparable
Mistral Small: 33.5 (#96), Qwen3 14B: —
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| LMArena Vision | 1142 | — |
Multilingual Not comparable
Mistral Small: 45.5 (#169), Qwen3 14B: —
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1315 | — |
| LMArena Chinese | 1340 | — |
| LMArena French | 1337 | — |
| LMArena German | 1340 | — |
| LMArena Japanese | 1275 | — |
| LMArena Korean | 1259 | — |
| LMArena Russian | 1324 | — |
| LMArena Spanish | 1346 | — |
Instruction Following Not comparable
Mistral Small: 66.4 (#209), Qwen3 14B: —
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| LiveBench Instruction Following | 63.7% | — |
| LMArena Instruction Following | 1310 | — |
Long Context Mistral Small leads
Mistral Small: 40.4 (#156), Qwen3 14B: 38.1 (#204)
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1327 | — |
Writing & Preference Not comparable
Mistral Small: 52.5 (#171), Qwen3 14B: —
| Benchmark | Mistral Small | Qwen3 14B |
|---|---|---|
| LMArena Text | 1338 | — |
| LMArena Creative Writing | 1305 | — |
| LMArena Multi-Turn | 1344 | — |
| LiveBench Language | 30.5% | — |
Frequently asked questions
Is Mistral Small better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 33.4 on the Noometry Index. Mistral Small costs 2.3× less per token, which makes it the better buy when Qwen3 14B's lead doesn't matter for your workload.
Which is cheaper, Mistral Small or Qwen3 14B?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.
Is Mistral Small or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
Mistral Small does, with 262K tokens against 131K.
How many benchmarks do Mistral Small and Qwen3 14B share?
9 benchmarks have published results for both models. Mistral Small has 39 scored results on Noometry and Qwen3 14B has 12.