Model comparison
Magistral Small vs Qwen2.5 72B Instruct
Qwen2.5 72B Instruct is the stronger model overall, scoring 31.9 to 30.2 on the Noometry Index. Magistral Small costs 3.3× less per token, which makes it the better buy when Qwen2.5 72B Instruct's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. Magistral Small scores higher in 3 categories and Qwen2.5 72B Instruct in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen2.5 72B Instruct leads 22.3 to 6.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 30% for Magistral Small and 8.1% for Qwen2.5 72B Instruct.
- Magistral Small is cheaper at $0.50 / $1.50 per million input/output tokens, against $1.40 / $5.60 for Qwen2.5 72B Instruct.
- Qwen2.5 72B Instruct accepts more context: 131K tokens versus 128K.
Side by side
| Magistral Small | Qwen2.5 72B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 30.2 | 31.9 |
| Released | 2025-06-10 | 2024-09 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 40K | 8K |
| Input $ / M tokens | $0.50 | $1.40 |
| Output $ / M tokens | $1.50 | $5.60 |
| Results tracked | 10 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Magistral Small leads
Magistral Small: 38.4 (#176), Qwen2.5 72B Instruct: 33.2 (#260)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| SciCode | 35.2% | — |
| WeirdML | — | 16% |
| BigCodeBench Instruct | — | 45.8% |
| LMArena Coding | — | 1292 |
| BigCodeBench Complete | — | 55.9% |
Agentic & Tool Use Not comparable
Magistral Small: —, Qwen2.5 72B Instruct: 22.1 (#133)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| TheAgentCompany | — | 5.7% |
| BALROG | — | 16.2% |
| METR Time Horizons | — | 35.8% |
Reasoning Qwen2.5 72B Instruct leads
Magistral Small: 6.8 (#350), Qwen2.5 72B Instruct: 22.3 (#199)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| DTBench | 61.3% | 62.9% |
| Epoch Capabilities Index | 133.19 | 129 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 6.3% | — |
| ARC-AGI-1 | 5% | — |
| CritPt | 0.3% | — |
| Chess Puzzles | 3% | — |
| LMArena Hard Prompts | — | 1271 |
| LMCA | — | 13.4% |
| BIG-Bench Hard | — | 79.8% |
| ForecastBench | — | 57.5 |
| HellaSwag | — | 84.8% |
| PIQA | — | 82.6% |
| WinoGrande | — | 82.3% |
Math Magistral Small leads
Magistral Small: 26.2 (#261), Qwen2.5 72B Instruct: 19.3 (#287)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 30% | 8.1% |
| Omni-MATH | — | 33% |
| LMArena Math | — | 1283 |
| MATH Level 5 | — | 63.2% |
Knowledge Magistral Small leads
Magistral Small: 30.9 (#223), Qwen2.5 72B Instruct: 27.0 (#253)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| GPQA Diamond | 56.1% | 49.1% |
| MMLU-Pro | — | 63.1% |
| Confabulations | — | 19.1% |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1245 |
| ARC (AI2) Challenge | — | 94.5% |
| MMLU | — | 85.3% |
| TriviaQA | — | 71.9% |
Multilingual Not comparable
Magistral Small: —, Qwen2.5 72B Instruct: 41.0 (#213)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Non-English | — | 1252 |
| LMArena Chinese | — | 1272 |
| LMArena French | — | 1280 |
| LMArena German | — | 1234 |
| LMArena Japanese | — | 1180 |
| LMArena Korean | — | 1188 |
| LMArena Russian | — | 1264 |
| LMArena Spanish | — | 1256 |
Instruction Following Not comparable
Magistral Small: —, Qwen2.5 72B Instruct: 65.5 (#221)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| IFEval | — | 80.6% |
| LMArena Instruction Following | — | 1254 |
Long Context Not comparable
Magistral Small: —, Qwen2.5 72B Instruct: 38.9 (#188)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Longer Query | — | 1282 |
Writing & Preference Not comparable
Magistral Small: —, Qwen2.5 72B Instruct: 46.7 (#215)
| Benchmark | Magistral Small | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Text | — | 1269 |
| LMArena Creative Writing | — | 1221 |
| WildBench | — | 80.2% |
| LMArena Multi-Turn | — | 1272 |
Frequently asked questions
Is Magistral Small better than Qwen2.5 72B Instruct?
Qwen2.5 72B Instruct is the stronger model overall, scoring 31.9 to 30.2 on the Noometry Index. Magistral Small costs 3.3× less per token, which makes it the better buy when Qwen2.5 72B Instruct's lead doesn't matter for your workload.
Which is cheaper, Magistral Small or Qwen2.5 72B Instruct?
Magistral Small is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; Qwen2.5 72B Instruct lists at $1.40 and $5.60.
Is Magistral Small or Qwen2.5 72B Instruct better for coding?
Magistral Small scores higher on coding benchmarks: 38.4 versus 33.2 in the Noometry coding category.
Which has the bigger context window?
Qwen2.5 72B Instruct does, with 131K tokens against 128K.
How many benchmarks do Magistral Small and Qwen2.5 72B Instruct share?
4 benchmarks have published results for both models. Magistral Small has 10 scored results on Noometry and Qwen2.5 72B Instruct has 43.