Model comparison
Magistral Small vs Qwen3 14B
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.2 on the Noometry Index.
Last verified . 8 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 8 benchmarks with published results for both. Magistral Small scores higher in 1 category and Qwen3 14B in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 14B leads 38.6 to 26.2.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 6.3% for Magistral Small and 49.1% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $0.50 / $1.50 for Magistral Small.
- Qwen3 14B accepts more context: 131K tokens versus 128K.
Side by side
| Magistral Small | Qwen3 14B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 30.2 | 35.5 |
| Released | 2025-06-10 | 2025-04 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 40K | 8K |
| Input $ / M tokens | $0.50 | $0.35 |
| Output $ / M tokens | $1.50 | $1.40 |
| Results tracked | 10 | 12 |
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Category by category
Coding Magistral Small leads
Magistral Small: 38.4 (#176), Qwen3 14B: 37.3 (#195)
| Benchmark | Magistral Small | Qwen3 14B |
|---|---|---|
| SciCode | 35.2% | 31.6% |
Agentic & Tool Use Not comparable
Magistral Small: —, Qwen3 14B: 29.6 (#83)
| Benchmark | Magistral Small | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41% |
Reasoning Qwen3 14B leads
Magistral Small: 6.8 (#350), Qwen3 14B: 18.5 (#280)
| Benchmark | Magistral Small | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 6.3% | 49.1% |
| CritPt | 0.3% | 0% |
| Chess Puzzles | 3% | 4% |
| DTBench | 61.3% | 64% |
| Epoch Capabilities Index | 133.19 | 138.23 |
| ARC-AGI-2 | 0% | — |
| ARC-AGI-1 | 5% | — |
| LMCA | — | 18.2% |
Math Qwen3 14B leads
Magistral Small: 26.2 (#261), Qwen3 14B: 38.6 (#133)
| Benchmark | Magistral Small | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 30% | 66.4% |
Knowledge Qwen3 14B leads
Magistral Small: 30.9 (#223), Qwen3 14B: 39.3 (#134)
| Benchmark | Magistral Small | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 56.1% | 63.8% |
| Vectara Hallucination Rate | — | 5.4% |
Long Context Not comparable
Magistral Small: —, Qwen3 14B: 38.1 (#204)
| Benchmark | Magistral Small | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
Frequently asked questions
Is Magistral Small better than Qwen3 14B?
Qwen3 14B is the stronger model overall, scoring 35.5 to 30.2 on the Noometry Index.
Which is cheaper, Magistral Small or Qwen3 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Magistral Small lists at $0.50 and $1.50.
Is Magistral Small or Qwen3 14B better for coding?
Magistral Small scores higher on coding benchmarks: 38.4 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3 14B does, with 131K tokens against 128K.
How many benchmarks do Magistral Small and Qwen3 14B share?
8 benchmarks have published results for both models. Magistral Small has 10 scored results on Noometry and Qwen3 14B has 12.