Model comparison
Mistral Small vs Qwen2.5 14B Instruct
Mistral Small has enough public results to be ranked (#243); Qwen2.5 14B Instruct does not yet, so treat this comparison as directional.
Last verified . 3 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. Mistral Small scores higher in 0 categories and Qwen2.5 14B Instruct in 1 category; one gap is clear of the uncertainty.
- The widest gap is in coding, where Qwen2.5 14B Instruct leads 37.7 to 34.0.
- The biggest single-benchmark swing is BigCodeBench Complete: 46.6% for Mistral Small and 52.2% for Qwen2.5 14B Instruct.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.35 / $1.40 for Qwen2.5 14B Instruct.
- Mistral Small accepts more context: 262K tokens versus 131K.
Side by side
| Mistral Small | Qwen2.5 14B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 33.4 | 38.7 |
| Released | 2024-02-26 | 2024-09 |
| 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 | 3 |
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Category by category
Coding Qwen2.5 14B Instruct leads
Mistral Small: 34.0 (#247), Qwen2.5 14B Instruct: 37.7 (#191)
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| BigCodeBench Instruct | 36.1% | 39.8% |
| BigCodeBench Complete | 46.6% | 52.2% |
| SciCode | 26.5% | — |
| LiveBench Coding | 36.2% | — |
| LMArena Coding | 1362 | — |
| ALE-Bench | 497.62 | — |
Agentic & Tool Use Not comparable
Mistral Small: 28.1 (#93), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.1% | — |
Reasoning Not comparable
Mistral Small: 19.8 (#250), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 37.8% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | 44.8% | — |
| LMArena Hard Prompts | 1335 | — |
| DTBench | 70.9% | — |
| LiveBench Data Analysis | 53.7% | — |
| LMCA | 20.6% | — |
| LiveBench | 44% | — |
Math Not comparable
Mistral Small: 16.4 (#293), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.8% | — |
| LiveBench Math | 39.9% | — |
| LMArena Math | 1341 | — |
| MATH Level 5 | 46.8% | — |
Knowledge Not comparable
Mistral Small: 31.0 (#222), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| MMLU | 68.7% | 79.9% |
| GPQA Diamond | 47.5% | — |
| Vectara Hallucination Rate | 5.1% | — |
| LMArena Expert | 1291 | — |
Multimodal Not comparable
Mistral Small: 33.5 (#96), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Vision | 1142 | — |
Multilingual Not comparable
Mistral Small: 45.5 (#169), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| 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), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| LiveBench Instruction Following | 63.7% | — |
| LMArena Instruction Following | 1310 | — |
Long Context Not comparable
Mistral Small: 40.4 (#156), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Longer Query | 1327 | — |
Writing & Preference Not comparable
Mistral Small: 52.5 (#171), Qwen2.5 14B Instruct: —
| Benchmark | Mistral Small | Qwen2.5 14B Instruct |
|---|---|---|
| LMArena Text | 1338 | — |
| LMArena Creative Writing | 1305 | — |
| LMArena Multi-Turn | 1344 | — |
| LiveBench Language | 30.5% | — |
Frequently asked questions
Is Mistral Small better than Qwen2.5 14B Instruct?
Mistral Small has enough public results to be ranked (#243); Qwen2.5 14B Instruct does not yet, so treat this comparison as directional.
Which is cheaper, Mistral Small or Qwen2.5 14B Instruct?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen2.5 14B Instruct lists at $0.35 and $1.40.
Is Mistral Small or Qwen2.5 14B Instruct better for coding?
Qwen2.5 14B Instruct scores higher on coding benchmarks: 37.7 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 Qwen2.5 14B Instruct share?
3 benchmarks have published results for both models. Mistral Small has 39 scored results on Noometry and Qwen2.5 14B Instruct has 3.