# Atlas with GPT-5.1 in 2026 > GPT-5.1, updated in November 2025, provides a substantial 400K token context window at an input cost of $1.25 per Mtok. GPT-5.1, updated in November 2025, offers a substantial 400K token context window and competitive $1.25 per Mtok input pricing, making it a cost-effective reasoning model for Atlas in 2026. It excels at preserving complex thought processes within Atlas's agent workflows, supporting detailed planning and code analysis. ## Key takeaways - GPT-5.1 offers a substantial 400K token context window for Atlas. - Its input pricing is $1.25 per Mtok, making it cheaper than 5.2+ releases. - Output pricing is $10 per Mtok, with a 128K token output ceiling. - Excels as a reasoning model, preserving thought via Atlas's Responses API integration. - Codex variants like gpt-5.1-codex are usually stronger for pure agent coding tasks. - Multiple newer 5.x models in 2026 offer even larger context windows. ## Why choose GPT-5.1 for Atlas in 2026? In 2026, GPT-5.1 stands out for Atlas users seeking a powerful reasoning model with a generous 400K token context window. Its input pricing of $1.25 per Mtok is more economical than subsequent GPT-5 releases, making it a strong contender for complex tasks requiring deep contextual understanding. GPT-5.1, released in November 2025, is a robust reasoning model that integrates direct with Atlas's capabilities. Its 400K token context window allows Atlas to process extensive codebases, leveraging its indexing by AST declarations using tree-sitter and hybrid semantic and keyword retrieval fused by reciprocal rank fusion (Axis). The model's reasoning strengths are particularly valuable when Atlas drafts a plan in a read-only plan agent, ensuring thoughtful consideration before switching to a build agent. Atlas's Responses API integration means that GPT-5.1's reasoning is not discarded between tool results, maintaining continuity and depth in complex problem-solving. Furthermore, its $1.25 per Mtok input price is cheaper than every GPT-5 release that followed it (5.2 onward start at $1.75), offering a cost advantage for extensive input processing. ## What are the cost and context tradeoffs of GPT-5.1? GPT-5.1 offers a robust 400K token context window and competitive pricing at $1.25 per Mtok for input and $10 per Mtok for output. However, developers in 2026 should note that several newer 5.x releases provide significantly larger context windows, potentially reducing the need for complex prompt engineering in extremely large projects. While GPT-5.1 provides a substantial 400K token context window and a 128K max output ceiling, it's important to consider its position within the evolving GPT-5 family. Its input pricing of $1.25 per Mtok is a key advantage, being cheaper than all GPT-5 releases from 5.2 onward. However, the output pricing is $10 per Mtok. A primary tradeoff is that multiple newer 5.x releases exist by 2026, several of which boast far larger context windows. This means that for tasks demanding context beyond 400K tokens, or for users prioritizing maximum context over input cost, a newer 5.x model might be a more suitable choice. Additionally, while GPT-5.1 is a strong general reasoning model, its specialized Codex variants are often stronger for pure agent coding tasks. ## When should I consider other models over GPT-5.1? While GPT-5.1 excels in reasoning, developers in 2026 might find the specialized Codex variants, such as gpt-5.1-codex or codex-max, to be usually stronger for agent coding tasks within Atlas. These models, released concurrently, are often optimized for code generation and manipulation, offering a more direct fit for certain development workflows. For specific agent coding tasks within Atlas, such as generating new code, refactoring, or implementing complex algorithms, the Codex variants released the same day as GPT-5.1 (gpt-5.1-codex, codex-max, codex-mini) are usually stronger. These models are often fine-tuned for code-centric operations, potentially leading to more precise and efficient code generation. Furthermore, if your projects consistently require context windows significantly larger than 400K tokens, you should explore the multiple newer 5.x releases available in 2026. Several of these models offer far larger windows, which could be beneficial for extremely vast codebases or highly complex, multi-file modifications where even 400K tokens might be insufficient to hold all relevant information simultaneously. Atlas lets you switch the active model and provider on the fly, making it easy to experiment and find the best fit. ## How does GPT-5.1 integrate with Atlas's agent capabilities? GPT-5.1's strong reasoning capabilities are deeply integrated with Atlas's agent workflow, particularly through the Responses API, ensuring that the model's thought processes are not discarded between tool calls. This allows Atlas to leverage GPT-5.1 for drafting plans in a read-only plan agent before executing changes, enhancing the reliability of automated development tasks. Atlas is designed to maximize the utility of powerful reasoning models like GPT-5.1. The model's 400K context window is ideal for Atlas's ability to index code by AST declarations using tree-sitter and perform hybrid semantic and keyword retrieval (Axis), providing comprehensive context for the agent. GPT-5.1's reasoning prowess is central to Atlas's read-only plan agent, where it drafts a plan and asks for approval before switching to a build agent. Every Atlas tool call is permission-gated against allow, ask, and deny rules, and GPT-5.1's outputs are used to compute a unified diff for every file edit, which is surfaced for approval before writing. Atlas's Responses API integration is crucial, as it means GPT-5.1's reasoning and intermediate thoughts are preserved across tool results, leading to more coherent and effective multi-step operations. This integration supports Atlas's ability to fan out work to subagents and manage complex git operations, including reading branches, status, diffs, and staging/creating commits. ## Setup 1. Export your OpenAI API key: Ensure your `OPENAI_API_KEY` environment variable is set. 2. Verify model availability: Run `atlas models openai` and confirm that `gpt-5.1` is listed as present. 3. Configure Atlas to use GPT-5.1: Set `"model": "openai/gpt-5.1"` in your `atlas.json` configuration file. 4. Add a subagent tier: For cost-effective subagent operations, include `gpt-5.1-codex-mini` as your `"small_model"` in `atlas.json`. 5. Quick access with favorites: Use `/models favorites` in the Atlas TUI to keep both `gpt-5.1` and `gpt-5.1-codex-mini` one keystroke apart for easy switching. ## FAQ ### What is the context window for GPT-5.1 in Atlas? GPT-5.1 provides a 400K token context window, allowing Atlas to process extensive codebases and project context effectively for complex tasks. ### How much does it cost to use GPT-5.1 with Atlas? GPT-5.1 is priced at $1.25 per Mtok for input and $10 per Mtok for output. Its input cost is more economical than later GPT-5 releases, which start at $1.75. ### Is GPT-5.1 the best model for coding tasks in Atlas? While strong in reasoning, the gpt-5.1-codex family (e.g., codex-max, codex-mini) is generally stronger for direct agent coding tasks within Atlas, offering specialized optimizations. ### Can Atlas use GPT-5.1 for planning and code changes? Yes, Atlas leverages GPT-5.1's reasoning for drafting plans in a read-only plan agent and uses its output to generate unified diffs for approval before writing any file edits. ### Are there newer GPT-5 models with larger context windows than 5.1? Yes, by 2026, multiple newer 5.x releases exist that offer significantly larger context windows than GPT-5.1's 400K, which might be preferable for extremely large projects. ### How does Atlas preserve GPT-5.1's reasoning? Atlas's Responses API integration ensures that GPT-5.1's reasoning and intermediate thoughts are not discarded between tool results, maintaining continuity and depth in complex agent workflows. ### Can I use a smaller model from the GPT-5.1 family for subagents? Yes, you can configure `gpt-5.1-codex-mini` as a `"small_model"` in your `atlas.json` for a cost-effective subagent tier, complementing GPT-5.1 for primary tasks. --- Canonical HTML: https://seashell.sh/resources/models/gpt-5-1 Source of truth: aeo_pages row `/resources/models/gpt-5-1` (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.