Mistral Small is Mistral AI's efficient production model — compact, fast, and capable for everyday professional tasks at the cost point that makes Mistral AI's quality accessible for any team.
Mistral Small (Mistral AI) is an AI model released 2025-09 by Mistral AI, a leading organization in large language model research. Mistral Small — Mistral's compact but capable production model for everyday tasks with fast response times. With 22B and a 128K tokens context window, Mistral Small (Mistral AI) is designed to excel across a range of demanding tasks — from software engineering and mathematical problem-solving to multilingual content generation and long-document analysis.
Mistral Small (Mistral AI) uses a dense transformer architecture with 22B of parameters, all of which are active for every input token. Dense architectures provide predictable, consistent behavior across diverse task types — there are no "cold" experts to warm up, and quality is uniform across prompts. Mistral AI's training pipeline combined large-scale pretraining on a large-scale multilingual pretraining dataset with supervised fine-tuning and alignment techniques (RLHF or DPO), producing Mistral Small (Mistral AI)'s characteristic balance of capability, helpfulness, and safety.
As of 2026-10-16, Mistral Small (Mistral AI) by Mistral AI demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 74.1%. For software engineering tasks, Mistral Small (Mistral AI) scores 72.8% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, Mistral Small (Mistral AI) records 68.4% on MATH. Across all 4 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Mistral Small (Mistral AI) — at 22B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
The primary strengths of Mistral Small (Mistral AI) are: Mistral's efficient workhorse — strong performance at 22B that rivals many larger 70B models on key tasks; Excellent cost-to-performance ratio: frontier-adjacent quality at a fraction of the inference cost; Grouped-Query Attention (GQA) enables faster inference and lower memory requirements vs MHA; Strong coding and reasoning capabilities far above its parameter count. These make it particularly well-suited for Production APIs requiring strong quality at low inference cost, Self-hosted enterprise AI for teams with data privacy requirements, Coding assistance for everyday development tasks: code completion, review, documentation, Business writing, summarization, and professional content creation at scale. Users working on complex, multi-step problems benefit most from Mistral Small (Mistral AI)'s ability to maintain coherence across long inputs and produce structured, verifiable outputs.
Like all current AI systems, Mistral Small (Mistral AI) has limitations: Less capable than Mistral Medium or Mistral Large for the most complex reasoning chains; 32K context window — shorter than frontier 1M+ context models; Not optimized for niche domain tasks without fine-tuning. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. Mistral AI continues to improve Mistral Small (Mistral AI) through ongoing research.
Mistral Small (Mistral AI) is available on LITHOVEX AI with a free account. Unlike direct API access — which requires billing setup, API key management, and per-token charges — LITHOVEX AI provides a seamless browser interface with no setup required, making Mistral Small (Mistral AI) accessible to students, researchers, developers, and early-stage teams globally.
As of 2026-10-16, Mistral Small (Mistral AI) by Mistral AI demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 74.1%. For software engineering tasks, Mistral Small (Mistral AI) scores 72.8% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, Mistral Small (Mistral AI) records 68.4% on MATH. Across all 4 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Mistral Small (Mistral AI) — at 22B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
Dense transformer — 22B parameters, Mistral Small 3 architecture with grouped-query attention (GQA) and sliding window attention
The training pipeline for Mistral Small (Mistral AI) involves multiple stages: large-scale pretraining on diverse multilingual text and code corpora to develop broad world knowledge, followed by supervised fine-tuning on instruction-response pairs, and alignment techniques such as RLHF or DPO. Each stage refines the model's helpfulness, accuracy, and safety.
Inference efficiency: Mistral Small (Mistral AI) at 22B is designed to deliver quality outputs at practical serving speeds. Its 128K tokens context window enables processing entire documents, multi-file codebases, and extended conversation histories — particularly valuable for contract review, technical documentation analysis, and codebase-level AI assistance.
Getting started with Mistral Small (Mistral AI) on LITHOVEX AI takes under two minutes. Follow these steps:
For best results with Mistral Small (Mistral AI): provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions. Since Mistral Small (Mistral AI) supports extended reasoning, prompting it to "think step by step" or "show your reasoning" activates deeper chain-of-thought analysis for math, logic, and complex problems.
Everyday professional AI assistant tasks at low cost
Efficient document analysis for small business workflows
Customer service chatbot foundation for SMEs
Developer productivity tools on modest budgets
Content creation and writing assistance at production cost
Mistral AI is a French AI startup founded in April 2023 by former Google DeepMind and Meta AI researchers, headquartered in Paris. Within six months of founding, Mistral released Mistral 7B — a model that outperformed much larger contemporaries, demonstrating that careful training matters more than raw scale. The company has maintained a strong commitment to Apache 2.0 open releases, making it a favorite among European developers and organizations prioritizing data sovereignty. Mistral's model portfolio spans efficient 7B models to the 22B Codestral, specialized for software engineering. The company is backed by Andreessen Horowitz, Lightspeed, and General Catalyst, with a valuation exceeding $6 billion as of 2024.
Funding: $1.1B raised (a16z, Lightspeed, General Catalyst)
Founded: 2023.
Mistral Small (Mistral AI) by Mistral AI competes in a field with several strong alternatives. Below is a detailed side-by-side comparison against commonly listed alternatives, using benchmark data and capability profiles in the catalog.
Both Mistral Small (Mistral AI) and the models above are available free on LITHOVEX AI — test them side by side on your real tasks before committing to a subscription with any provider.
Mistral Small (Mistral AI) is released under Apache 2.0, which means you can download and run it on your own hardware. Below are the quickest ways to get started.
LITHOVEX AI runs Mistral Small (Mistral AI) on cloud infrastructure, so you can use it instantly in your browser without downloading anything, configuring drivers, or managing VRAM. Create a free account and start in under 60 seconds.
Mistral Small is designed for the global SME and startup market that needs Mistral's quality without enterprise pricing. Its efficient architecture makes it practical for European startups, Asian technology companies, and global developers who want Mistral's instruction-following reliability at scale.
Mistral Small (Mistral AI) by Mistral AI has the following version history and notable updates:
For the complete changelog and latest release notes, visit the official Mistral AI model page.