Mistral
Mistral Small 3
Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed...
Cost / 1M tokens
Very low usage$0.05
input
—
cached input
$0.08
output
Context Window
33K
Up to 16K max output
Modalities
text → text
Mistral tokenizer
Quickstart & API
mistralai/mistral-small-24b-instruct-2501Best for & Strengths
Key Strengths
Recommended Workloads in ChatOSS
- Open-source AI workflows
Verified Evaluations
Benchmarks & Frontier Comparison
How Mistral Small 3 compares against leading open-weight and proprietary frontier models across independent agentic coding and reasoning suites.
| Benchmark (Metric) | Mistral Small 3 | DeepSeek V4.1 Flash | GLM 5.3 | Kimi K3.1 Pro | Claude Opus 5.5 |
|---|---|---|---|---|---|
| Agentic & Software Engineering | |||||
| ChatOSS Agentic Coding Index (%) | — | 63.2% | 58.3% | 65% | 74.1% |
| SWE-Bench Verified (%) | — | 91.5% | 95.4% | 94.8% | 97% |
| DeepSWE v1.1 (Pass@1 %) | — | 77% | 69% | 73.5% | 74.2% |
| Vibe Code Bench v1.1 (%) | — | 87.7% | 78.1% | 88.4% | 90.3% |
| Terminal-Bench 4.0 (%) | — | 42.3% | 42% | 46.2% | 65.2% |
| Code Migration (%) | — | 45.6% | 44.2% | 52% | 66.7% |
| Intelligence & Token Economics | |||||
| Artificial Analysis Intelligence Index (0–100) | 6.7 | 39.5 | 44.8 | 55.1 | 57.6 |
| Input Price (/ 1M tokens) | $0.05 | $0.15 | $1.40 | $2.00 | $4.00 |
| Output Price (/ 1M tokens) | $0.08 | $0.60 | $4.40 | $10.00 | $20.00 |
Artificial Analysis Intelligence Index
Artificial Analysis
Active Provider Endpoints (1)
Upstream inference providers serving Mistral Small 3, with per-provider pricing, context limits, quantization, and 24-hour uptime.
| Provider | Input / 1M | Output / 1M | Cache Read / 1M | Context | Max Output | Quantization | Uptime (24h) |
|---|---|---|---|---|---|---|---|
DeepInfra deepinfra/fp8 | $0.05 | $0.08 | — | 33K | 16K | fp8 | 100.0% |
Supported API Parameters
Parameters accepted by this model when called through ChatOSS or OpenRouter.
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