Mistral AI • LLM
A 7.3B parameter model that outperforms Llama 2 13B on all benchmarks, with optimizations for speed and context length.
Context Window
3K tokens
Input Price/1M
$0.11
Output Price/1M
$0.19
Parameters
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Mistral: Mistral 7B Instruct v0.1 results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 4.6 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 12.1 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 7.4 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 24.5 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 17.7 | 100.0 | Artificial Analysis official API |
Mistral: Mistral 7B Instruct v0.1 is an AI model developed by Mistral AI, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 3K tokens, it is suitable for processing short documents and direct prompts.
Mistral: Mistral 7B Instruct v0.1 is usage-based, priced at $0.11/1M input tokens and $0.19/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Mistral: Mistral 7B Instruct v0.1 was evaluated on 5 different benchmarks, covering categories like Coding, Math, 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.
Mistral: Mistral 7B Instruct v0.1 is suitable for a wide range of AI applications: high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
In the 2026 AI model ecosystem, Mistral: Mistral 7B Instruct v0.1 competes directly with similarly capable models. Mistral AI 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.
A 7.3B parameter model that outperforms Llama 2 13B on all benchmarks, with optimizations for speed and context length.
Mistral: Mistral 7B Instruct v0.1 costs $0.11/1M input tokens and $0.19/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, Mistral: Mistral 7B Instruct v0.1 scored: LiveCodeBench: 4.6/100, MATH-500: 12.1/100, AA Intelligence Index: 7.4/100. See the full table above for a detailed comparison.
Yes, Mistral: Mistral 7B Instruct v0.1 is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
Mistral: Mistral 7B Instruct v0.1 excels at general-purpose language tasks.
Last updated: May 15, 2026 • View methodology →