GPT-5.1 Codex Max is the November 2025 Codex Max tier, still priced at the GPT-5.1 rate of $1.25 / $10 per Mtok (input / output) with a 400K token context window and 128K output. It is the cheapest way into OpenAI's coding-specialized Codex post-training, and inside Atlas that buys sustained agentic loops at a price point closer to a general mid-tier model. The cost of the discount: it is two generations behind GPT-5.3 Codex on reasoning quality.
How cheap is GPT-5.1 Codex Max compared to other Codex models?
GPT-5.1 Codex Max charges $1.25 input per Mtok, the lowest of any Codex-line model and 30 percent under GPT-5.3 Codex's $1.75. Full pricing is $1.25 / $10 per Mtok, still the November 2025 GPT-5.1 rate, which has not been repriced upward.
The pricing anomaly is the reason to care. OpenAI kept GPT-5.1 Codex Max on the original GPT-5.1 rate card while newer Codex models launched above it, so the cheapest route into coding-specialized post-training is also the oldest one. In Atlas, where the model gets re-fed a growing transcript and a set of retrieved declarations on every turn, a 30 percent cut on input compounds across a session. Output is $10 per Mtok, which is the same headline output rate as Claude Sonnet 5.
What does Codex post-training give GPT-5.1 Codex Max in an Atlas loop?
GPT-5.1 Codex Max carries Codex post-training for sustained agentic loops, at a price point closer to a general mid-tier model. In Atlas that means the November 2025 model keeps driving a task through repeated tool calls instead of pausing for confirmation after every step.
Sustained loops are what an Atlas session is made of. Atlas searches code with hybrid semantic and keyword retrieval fused by reciprocal rank fusion, connects to Model Context Protocol servers and exposes their tools to the agent, and permission-gates each of those calls against allow, ask, and deny rules. A model that stalls between steps turns one intention into many turns. GPT-5.1 Codex Max was post-trained to keep going, and at $1.25 / $10 per Mtok you get that behavior without paying a specialist premium.
What is the 400K context ceiling on GPT-5.1 Codex Max?
GPT-5.1 Codex Max has a 400K token context window with 128K output tokens, the same 400K ceiling as the rest of the Codex line. Whole-monorepo context is out of reach, so GPT-5.1 Codex Max is a model for scoped work rather than repository-wide reasoning.
Know the ceiling before you plan around it. Atlas can retrieve efficiently, since it indexes code by AST declarations using tree-sitter rather than blind line windows, and that keeps a 400K budget viable on a large codebase for a bounded task. But there is no configuration that turns 400K into a million. If your task genuinely requires holding an entire monorepo at once, GPT-5.1 Codex Max is the wrong tier and no amount of retrieval tuning will fix it. The 128K output ceiling, by contrast, is generous and rarely the binding constraint.
What do you give up by choosing GPT-5.1 Codex Max in 2026?
GPT-5.1 Codex Max is two generations behind GPT-5.3 Codex on reasoning quality. That is the honest cost of its $1.25 input rate, and in 2026 it means the November 2025 model will miss inferences a newer Codex model catches, especially on tangled multi-step problems.
The right way to hold that tradeoff is to notice when it bites. If GPT-5.1 Codex Max is churning: proposing edits, getting rejected at the permission gate, and rewriting, the 30 percent input saving is already gone. Atlas lets you switch the active model and provider on the fly with favorites and recents, so the escalation to GPT-5.3 Codex costs a keystroke. Use GPT-5.1 Codex Max as the default for routine, well-understood changes and let the harder work pay for a newer model.
Should you use GPT-5.1 Codex Max or gpt-5.1-codex-mini?
If cost is the constraint, compare GPT-5.1 Codex Max at $1.25 / $10 per Mtok against gpt-5.1-codex-mini at $0.25 / $2 before committing. The mini tier is five times cheaper on input, and for genuinely small tasks that gap is worth checking rather than assuming.
Do the comparison on a real task, not in the abstract. Set OPENAI_API_KEY or use atlas login, then run atlas models openai to confirm gpt-5.1-codex-max is exposed, and choose it from /models in the TUI. Run the same scoped change on both tiers and count the turns. Because Atlas snapshots file changes as git patches so edits can be diffed and rolled back, the experiment is safe and reversible. If the mini tier lands the change in the same number of turns, take the $0.25 rate.
Setup
- 01Set `OPENAI_API_KEY`, or use `atlas login`.
- 02Run `atlas models openai` to confirm gpt-5.1-codex-max is exposed.
- 03Choose it from `/models` in the TUI.
- 04If cost is the constraint, compare against gpt-5.1-codex-mini at $0.25 / $2 before committing.
- 05Escalate to GPT-5.3 Codex when reasoning quality, not price, becomes the binding constraint.
Frequently asked questions
- how much does gpt-5.1 codex max cost per million tokens
- GPT-5.1 Codex Max costs $1.25 / $10 per Mtok (input / output), still the November 2025 GPT-5.1 rate. At $1.25 input it is 30 percent under GPT-5.3 Codex's $1.75.
- what is the cheapest codex model for agentic coding
- GPT-5.1 Codex Max at $1.25 input per Mtok is the lowest of any Codex-line model, and it is the cheapest way into OpenAI's coding-specialized Codex post-training with a 400K window.
- what is gpt-5.1 codex max's context window
- GPT-5.1 Codex Max has a 400K token context window with 128K output tokens, the same 400K ceiling as the rest of the Codex line.
- gpt-5.1 codex max vs gpt-5.3 codex
- GPT-5.1 Codex Max is 30 percent cheaper on input ($1.25 versus $1.75 per Mtok) but two generations behind GPT-5.3 Codex on reasoning quality. Both share a 400K context ceiling.
- gpt-5.1 codex max vs gpt-5.1 codex mini pricing
- GPT-5.1 Codex Max is $1.25 / $10 per Mtok. gpt-5.1-codex-mini is $0.25 / $2 per Mtok, so compare the two before committing if cost is the constraint.
- how do i enable gpt-5.1 codex max in atlas
- Set `OPENAI_API_KEY` or use `atlas login`, run `atlas models openai` to confirm gpt-5.1-codex-max is exposed, then choose it from `/models` in the TUI.
- can gpt-5.1 codex max handle a whole monorepo
- No. GPT-5.1 Codex Max is capped at the same 400K context ceiling as the rest of the Codex line, so whole-monorepo context is out of reach.
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