BenchLeader
Mistral AIAuto-detected

Mistral Small 3.1

Best configuration ranks #524 of 610 on the BenchLeader Index at 39.7 ±3.5. Last measured 17 Mar 2025stale: no new result in six months. Released 17 Mar 2025.

Blended price
$0.150/M
$0.100 in · $0.300 out
Output speed
150 tok/s
First answer
0.72 s
first token 0.72 s
Context
128k
How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.
  1. Overall index40
  2. Reasoning33
  3. Agents & tools40
  4. Maths26
  5. Knowledge40
  6. Instruction following34
  7. Long context36
  8. Composite38

Benchmark results

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

Coding

BenchmarkdefaultSource
SciCode (AA)not in index27.8%#150Artificial Analysis

Agents & tools

Maths

BenchmarkdefaultSource
OTIS Mock AIME3.9%#231Epoch AI Benchmarking Hub

Knowledge

BenchmarkdefaultSource
AA-Omniscience-50.8#321Artificial Analysis

Instruction following

BenchmarkdefaultSource
IFBench29.9%#346Artificial Analysis

Long context

BenchmarkdefaultSource
AA-LCR22.3%#350Artificial Analysis

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.

WorkloadTokens in / outCostWith cachingTime
Chat reply400 / 300$0.00012.7 s
Summarise a 30-page report12,000 / 600$0.00144.7 s
Code edit6,000 / 1,500$0.001110.7 s
Agentic coding session60,000 / 4,000$0.007227.5 s
Structured extraction2,000 / 200$0.00032.1 s

See also

Data as of 9 Sept 2026. Compare with another model.