Specifications
Context Window
—
Input Price/1M
$1.00
Output Price/1M
$3.00
Parameters
—
Speed
171 tok/s
Latency (TTFT)
504ms
Benchmarks
Mistral Small (Feb '24) results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SciCode | 13.0 | 100.0 | — |
| LiveCodeBench | 11.0 | 100.0 | — |
Knowledge
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 42.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 9.0 | 100.0 | — |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 30.0 | 100.0 | — |
| HLE | 4.0 | 100.0 | — |
Information
- Release date
- February 26, 2024
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Mistral Small (Feb '24)
What is Mistral Small (Feb '24)?
Mistral Small (Feb '24) is an AI model developed by Mistral, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via Mistral's cloud API.
Pricing & Costs in 2026
Mistral Small (Feb '24) is usage-based, priced at $1/1M input tokens and $3/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The mid-range pricing balances quality and cost for most professional applications.
Benchmarks & Performance
Mistral Small (Feb '24) was evaluated on 6 different benchmarks, covering categories like Coding, Knowledge, overall, Reasoning. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Mistral Small (Feb '24) specializes in text, offering advanced capabilities for creating and processing text content.
Comparison with Alternatives
In the 2026 AI model ecosystem, Mistral Small (Feb '24) competes directly with similarly capable models. Mistral competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Mistral Small (Feb '24)?
Mistral Small (Feb '24) is an AI model developed by Mistral. It is a text model.
How much does Mistral Small (Feb '24) cost?
Mistral Small (Feb '24) costs $1/1M input tokens and $3/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Mistral Small (Feb '24) compare with other models?
In available benchmarks, Mistral Small (Feb '24) scored: SciCode: 13/100, LiveCodeBench: 11/100, MMLU-Pro: 42/100. See the full table above for a detailed comparison.
Is Mistral Small (Feb '24) open source?
No, Mistral Small (Feb '24) is a proprietary model from Mistral. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is Mistral Small (Feb '24) best for?
Mistral Small (Feb '24) excels at general-purpose language tasks.
Last updated: June 01, 2026 • View methodology →