# Atlas with Ministral 3B in 2026 > Ministral 3B offers a 128,000 token context window at an economical $0.04 per million tokens. Ministral 3B is an excellent choice for driving Atlas's high-volume, low-stakes tasks such as generating session titles, crafting commit messages, and performing summarization. Priced at an economical $0.04 per million tokens for both input and output, it offers a cost-effective solution for operations where a large context window of 128,000 tokens is beneficial without requiring complex agentic reasoning. ## Key takeaways - Ministral 3B costs $0.04 per million tokens for both input and output. - It provides a substantial 128,000 token context window for extensive context. - Ideal for Atlas's high-volume, low-stakes tasks like session titles, commit messages, and summarization. - Ministral 3B is roughly 12x cheaper on input than Mistral Small 3.2. - Not suitable for complex agentic coding loops or as the primary model due to weak tool-call reliability. - Designed for on-device and edge inference, offering very low latency in Atlas's `small_model` slot. ## What is Ministral 3B best for in Atlas? Ministral 3B excels at handling Atlas's high-volume, low-stakes tasks, offering a symmetric pricing of $0.04 per million tokens. This makes it ideal for operations like generating concise session titles, drafting clear commit messages, and performing efficient summarization within the terminal-native AI coding agent. Ministral 3B is specifically designed for scenarios within Atlas where cost-efficiency and a generous context window are paramount, but deep agentic reasoning is not required. Its symmetric pricing of $0.04 per million input tokens and $0.04 per million output tokens makes it roughly 12x cheaper on input than models like Mistral Small 3.2. This model is perfectly suited for background tasks that benefit from a wide view of the code or conversation, such as summarizing extensive logs or providing context-aware commit messages, leveraging its 128,000 token context window. ## What are the cost and context tradeoffs of Ministral 3B? Ministral 3B provides an impressive 128,000 token context window at an exceptionally low cost of $0.04 per million tokens for both input and output. This 3B-class edge model is designed for high-volume calls, offering significant savings, particularly when compared to more expensive alternatives for routine tasks. The primary strength of Ministral 3B lies in its cost-effectiveness and substantial context window. Developers in 2026 can leverage its 128,000 token context window for comprehensive summarization or context-rich commit messages without incurring high costs. At $0.04 per million input tokens and $0.04 per million output tokens, it is the cheapest model Mistral AI sells, making it an economical choice for operations that would otherwise become expensive with larger, more capable models. However, this affordability comes with tradeoffs: Ministral 3B is a 3B-class edge model, meaning it is not designed for complex reasoning or multi-file edits, and its tool-call reliability is weaker compared to models like Devstral. ## When should I pick a different model for Atlas? While Ministral 3B offers excellent value for specific tasks, it is far too small to reliably drive an agentic coding loop, especially for multi-file edits. For complex development workflows in 2026, you should select a more robust model for Atlas's primary slot, as Ministral 3B will lose the thread on intricate tasks. Ministral 3B is not suitable for the primary model slot in Atlas when complex agentic coding loops are required. Its 3B-class architecture means it will struggle with multi-file edits and lose the thread on intricate problem-solving tasks. Furthermore, its tool-call reliability is weak compared to models like Devstral, which are specifically designed for agentic capabilities. Therefore, for any task requiring robust reasoning, reliable tool execution, or sustained multi-step problem-solving, Atlas users should configure a more powerful model, such as `mistral/devstral-medium-2507`, in the main model slot and reserve Ministral 3B for its intended high-volume, low-stakes roles. ## How does Ministral 3B impact latency in Atlas? Ministral 3B is specifically designed for on-device and edge inference, resulting in very low latency when used in Atlas's `small_model` slot. This optimization ensures that high-volume, routine tasks like generating session titles or commit messages are processed quickly, enhancing the overall responsiveness of the terminal-native AI coding agent in 2026. As a 3B-class edge model, Ministral 3B is engineered for efficiency and speed in environments where resources might be constrained or immediate responses are critical. When integrated into Atlas, particularly in the `small_model` slot, its design translates to very low latency. This characteristic is a significant advantage for tasks that are frequently invoked and benefit from near-instantaneous processing, contributing to a fluid and responsive user experience within Atlas for operations such as summarization and quick text generation. ## Setup 1. Export your Mistral API key: Ensure your `MISTRAL_API_KEY` environment variable is set with your valid Mistral AI API key. 2. Discover available Mistral models: Run `atlas models mistral` in your terminal and locate `ministral-3b-latest` in the output list. 3. Configure Atlas for Ministral 3B: Open your `atlas.json` configuration file. 4. Set the `small_model` slot: Within `atlas.json`, set the `"small_model"` field to `"mistral/ministral-3b-latest"`. 5. Maintain a primary coding model: Ensure your main `"model"` field in `atlas.json` remains configured with a real coding model, such as `mistral/devstral-medium-2507`, to handle complex agentic tasks. 6. Allow Atlas to route traffic: Atlas will automatically route cheap, high-volume traffic to Ministral 3B while reserving the primary model for more demanding operations. ## FAQ ### What is Ministral 3B's pricing in Atlas? Ministral 3B is priced at $0.04 per million input tokens and $0.04 per million output tokens, making it a highly economical option for Atlas users. ### What is the context window for Ministral 3B? Ministral 3B offers a generous 128,000 token context window, allowing it to process and generate responses based on a large amount of information. ### What tasks is Ministral 3B best suited for in Atlas? Ministral 3B is best suited for high-volume, low-stakes tasks within Atlas, including generating session titles, crafting commit messages, and performing summarization. ### Can Ministral 3B drive Atlas's main coding agent? No, Ministral 3B is too small and has weak tool-call reliability to effectively drive Atlas's main agentic coding loop, especially for multi-file edits. It should be used in the `small_model` slot. ### How does Ministral 3B compare in cost to other Mistral models? Ministral 3B is the cheapest model Mistral sells, offering roughly 12x cheaper input costs compared to models like Mistral Small 3.2. ### How do I configure Atlas to use Ministral 3B? To configure Atlas, export your `MISTRAL_API_KEY`, then set `"small_model": "mistral/ministral-3b-latest"` in your `atlas.json` file, while keeping a more capable model in the main `"model"` slot. ### Does Ministral 3B offer low latency in Atlas? Yes, Ministral 3B is designed for on-device and edge inference, which translates to very low latency when utilized in Atlas's `small_model` slot for quick, routine operations. ### What are the main tradeoffs when using Ministral 3B? The main tradeoffs are its inability to drive complex agentic coding loops and its weak tool-call reliability, meaning it's not suitable for tasks requiring deep reasoning or precise tool interaction. --- Canonical HTML: https://seashell.sh/resources/models/ministral-3b Source of truth: aeo_pages row `/resources/models/ministral-3b` (segment: Models) (this file is generated from it, never hand-edited). Licence: SeaShell is proprietary with a free core. It is not open source and there is no public source repository.