Mistral AIMagistral Small
Magistral Small is a Mistral AI open-weights reasoning model, released 10 Jun 2025. Its best configuration ranks #727 of 785 on the BenchLeader Index at 37.6 ±5.8, in the lower half. The ± is the point: 227 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in knowledge (42) and lowest in long context (23). At $0.262 per million tokens blended it is cheaper than most ranked models. Last measured 10 Jun 2025.stale: no new result in six months
- Blended price
- $0.262/M
- $0.150 in · $0.600 out
- Output speed
- –
- First answer
- –
- Context
- 262k
- Full answer
- –
- Cost per run
- –
- Released
- 10 Jun 2025
- Overall index38
- Reasoning33
- Agents & tools38
- Maths37
- Knowledge42
- Instruction following30
- Long context23
- Composite39
Versions
Mistral AI has shipped 3 models under this name. Each is ranked on its own results; a newer version often has fewer results so far, which holds its index nearer the average until more arrive.
| Model | Released | Index | Rank |
|---|---|---|---|
| Magistral Small 1.2 | 18 Sept 2025 | 40.3 | #659 |
| Magistral Smallthis page | 10 Jun 2025 | 37.6 | #727 |
| Magistral Small 1.0 | – | – | – |
How its index has moved
8 Sept 2026 to 23 Oct 2026The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.
Benchmark results
See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.
Reasoning
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| GPQA Diamond | 56.1%#200 | Epoch AI Benchmarking Hub | |
| GPQA Diamond (AA)not in index | 64.1%#350 | Artificial Analysis | |
| Humanity's Last Exam (AA)not in index | 7.5%#362 | Artificial Analysis | |
| Kagi LLM Benchmark | 6.3%#136 | Kagi LLM Benchmark | |
| ARC-AGI-1 | 5.0%#247 | ARC Prize | |
| ARC-AGI-2 | 0.0%#242 | ARC Prize | |
| CritPt | 0.0%#315 | Artificial Analysis |
Agents & tools
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| Terminal-Bench Hard | 4.5%#284 | Artificial Analysis | |
| τ²-Bench Telecom (AA)not in index | 26.6%#280 | Artificial Analysis |
Maths
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| OTIS Mock AIME | 30.0%#208 | Epoch AI Benchmarking Hub |
Knowledge
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| AA-Omniscience | -44.4#348 | Artificial Analysis | |
| AA-Omniscience: accuracynot in index | 18.0%#346 | Artificial Analysis | |
| AA-Omniscience: non-hallucinationnot in index | 23.9%#252 | Artificial Analysis |
Instruction following
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| IFBench | 24.8%#394 | Artificial Analysis |
Long context
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| AA-LCR | 0.0%#493 | Artificial Analysis |
Composite
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| AA Intelligence Index v4.3.2 | 8.2#442 | Artificial Analysis |
Price history
The price above, per 1M tokens, every day it changed.
What a task costs
Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0002 | – | – |
| Summarize a 30-page report | 12,000 / 600 | $0.0022 | – | – |
| Code edit | 6,000 / 1,500 | $0.0018 | – | – |
| Agentic coding session | 60,000 / 4,000 | $0.011 | – | – |
| Structured extraction | 2,000 / 200 | $0.0004 | – | – |
More from Mistral AI
See also
Questions people ask
- What are Magistral Small's benchmark scores?
- As of 25 Oct 2026, Magistral Small scores 37.6 ±5.8 on the BenchLeader Index, strongest in knowledge (42) and weakest in long context (23). That rests on 11 independent benchmark results, and every score on this page links to its publisher.
- How does Magistral Small rank?
- Magistral Small is #727 of 785 ranked configurations on 25 Oct 2026. 227 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.
- How much does Magistral Small cost per 1M tokens?
- As of 25 Oct 2026, Magistral Small costs $0.150 per 1M input tokens and $0.600 per 1M output tokens, $0.262 blended (three input tokens per output token). The list price last changed on 29 Sept 2026.
- When was Magistral Small released?
- Mistral AI released Magistral Small on 10 Jun 2025.
Data as of 25 Oct 2026. Compare with another model.
Cite as: BenchLeader, “Magistral Small: benchmarks, pricing, speed and rank”, data as of 25 Oct 2026, https://www.benchleader.com/models/magistral-small.