Mistral Small
Mistral AILarge Language ModelOpen SourceMistral's cost-efficient open-weight model optimized for simple tasks and high-throughput applications. Apache 2.0 license.
Abilities
Use Cases
Available in Tools
Availability
How to Use
Pros
- Fully open with Apache 2.0 license — unrestricted commercial use
- Extremely cost-efficient at $0.10/1M input — excellent for batch processing
- Fast response times — suitable for real-time applications
- Can run on a single consumer GPU (24GB VRAM) with quantization
- Good multilingual support, especially European languages
Cons
- Significantly less capable than Large on complex reasoning and analysis
- 32K context window — much shorter than competitors
- Not suitable for hard coding or complex math tasks
- Limited multimodal capabilities — text only
What to Use It For
Perfect For
At $0.10/1M input tokens it is one of the cheapest open model APIs — ideal for high-volume simple tasks
Fast and cheap enough for real-time text classification without overkill model capabilities
24B parameters fit on a single consumer GPU (24GB VRAM) with quantization — easy self-hosting
Good For
Good enough quality for straightforward summarization and structured Q&A at minimal cost
Reliable at pulling structured data from documents without needing frontier model intelligence
Not Recommended
24B model lacks the depth for multi-step reasoning and nuanced analytical tasks
Try instead: Mistral Large, Claude Sonnet 4
32K context window is too short for processing large documents or codebases
Try instead: Gemini 2.5 Pro
Do Not Use For
Produces too many bugs on complex code — not reliable enough for serious development work
Try instead: Codestral, Claude Sonnet 4
Text-only model with no vision, audio, or image capabilities at all
Try instead: GPT-4o