GPT-5.3-Codex Is Now the Copilot Default — and Every Older Codex Model Retires July 23

GPT-5.3-Codex has been OpenAI’s primary agentic coding model since February 5, 2026. On May 17 it became the base model for all GitHub Copilot Business and Enterprise organizations, replacing GPT-4.1 as the default. On June 5, GPT-5.2-Codex was removed from most Copilot model pickers.

And on July 23, 2026, every earlier Codex API model shuts down.

If you have any production calls to gpt-5-codex, gpt-5.1-codex, gpt-5.1-codex-max, gpt-5.2-codex, or gpt-5.1-codex-mini, those calls fail in 51 days.

What Is Being Shut Down

The following model IDs reach end-of-life on July 23, 2026:

The legacy codex-mini-latest model was already removed from the API on February 12, 2026.

gpt-5.3-codex is not on this list. It has a long-term support commitment in GitHub Copilot Business and Enterprise through February 4, 2027.

The Migration

Change the model string:

# Before (any of these)
response = client.responses.create(
    model="gpt-5.2-codex",  # or gpt-5.1-codex, gpt-5-codex, etc.
    ...
)

# After
response = client.responses.create(
    model="gpt-5.3-codex",
    ...
)

GPT-5.3-Codex is backward-compatible with the same API surfaces as earlier Codex models. Existing prompts, tool definitions, and system messages transfer without modification.

The one thing to check: if your code passes a reasoning_effort parameter, gpt-5.3-codex accepts "low", "medium", "high", and "xhigh". The older models accepted a narrower set of values. If you were passing an unsupported string, you may get a different behavior — validate your reasoning_effort values after migrating.

What GPT-5.3-Codex Is

GPT-5.3-Codex combines two training stacks that were previously separate: the specialized coding training from the Codex lineage and the broader reasoning and professional knowledge from the GPT-5.2 base. Earlier Codex models were optimized narrowly for code generation. GPT-5.3-Codex handles the full agentic coding loop — research, planning, writing, running, debugging — without needing a separate orchestration model for non-code steps.

OpenAI describes the model as working “much like a colleague” during interactive sessions: you can steer it during long multi-file tasks without losing context, ask it to pause and replan, or hand off partial work to a human reviewer mid-task.

The model was used during its own development. OpenAI’s Codex team used early versions of GPT-5.3-Codex to debug its own training runs and manage deployment processes.

Capabilities Worth Knowing

Reasoning Effort Settings

GPT-5.3-Codex supports four reasoning effort levels via the API:

response = client.responses.create(
    model="gpt-5.3-codex",
    reasoning_effort="high",  # "low", "medium", "high", "xhigh"
    ...
)

• low — fast iteration, good for autocomplete-style tasks and short edits
• medium — balanced; default for most API calls
• high — longer reasoning; appropriate for architecture decisions and complex multi-file refactors
• xhigh — maximum reasoning budget; use for tasks where correctness matters more than latency (security audits, migration planning, critical path debugging)

Latency and cost scale with reasoning effort. For most build loops, medium is the right starting point. Use xhigh sparingly — it can take several minutes for complex tasks.

Computer Use

GPT-5.3-Codex can interact with a desktop through screenshots. This applies to coding tasks involving legacy tooling that lacks an API: filling forms in a web IDE, clicking through a UI-only deployment pipeline, or navigating a GUI-based database tool. The model accepts screenshot inputs and outputs structured actions or Playwright scripts.

response = client.responses.create(
    model="gpt-5.3-codex",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Click the 'Deploy to Production' button"},
                {"type": "image_url", "image_url": {"url": "data:image/png;base64,..."}}
            ]
        }
    ]
)

Terminal-Bench Performance

GPT-5.3-Codex ranks at the top of Terminal-Bench 2.0, a benchmark specifically for command-line agentic tasks — shell scripting, build systems, package management, file manipulation pipelines. If your agent runs in a terminal or interacts with shell commands as a core workflow, benchmark performance here is directly relevant.

Specifications

Pricing is identical to GPT-5.2-Codex. Migrating does not change your API costs.

GitHub Copilot Status

GPT-5.3-Codex is now the default model across GitHub Copilot. Timeline of changes:

• February 9, 2026: GA for Copilot Pro, Pro+, Business, Enterprise
• February 25, 2026: Available in GitHub.com, GitHub Mobile, and Visual Studio
• March 18, 2026: Long-term support commitment announced — guaranteed available in Copilot Business and Enterprise through February 4, 2027
• May 17, 2026: Became the base/default model for all Copilot Business and Enterprise organizations
• June 5, 2026: GPT-5.2-Codex deprecated from most Copilot experiences; GPT-5.3-Codex is the automatic replacement

For teams using Copilot via GitHub’s UI, this migration happened automatically on May 17. If you had explicit model selection set to gpt-5.2-codex in VS Code or JetBrains settings, check whether those overrides are still active — they may cause inconsistent behavior between your IDE and the Copilot API.

GPT-5.3-Codex vs. GPT-5.5

GPT-5.5 is OpenAI’s current top model. The Codex documentation now lists GPT-5.5 as the preferred model for most Codex tasks, with GPT-5.3-Codex as an “alternative model.”

The distinction is specialization vs. breadth:

• GPT-5.5 handles coding plus everything else (writing, analysis, multimodal tasks, professional documents). It is the right choice when your agent does coding alongside non-coding work.
• GPT-5.3-Codex is optimized for the agentic coding loop specifically. For pure code generation and terminal-execution pipelines, it benchmarks comparably to GPT-5.5 at lower per-token input costs ($1.75 vs. GPT-5.5’s $5.00).

If your agent is exclusively writing, running, and debugging code — no document generation, no multimodal input — GPT-5.3-Codex remains cost-competitive at the task it was designed for.

GPT-5.3-Codex-Spark

OpenAI has released gpt-5.3-codex-spark as a research preview. It is text-only (no image input), optimized for near-instant coding iteration at low latency. Currently restricted to ChatGPT Pro users only — no API access as of June 2026. Watch this space for a broader rollout.

Builder Actions

1. Audit your API calls now. Search your codebase for gpt-5-codex, gpt-5.1-codex, gpt-5.1-codex-max, gpt-5.1-codex-mini, gpt-5.2-codex. Every instance of these model IDs breaks on July 23.
2. Swap to gpt-5.3-codex. No other code changes required for most workloads.
3. Validate reasoning effort values. If you pass a reasoning_effort parameter, confirm your value is one of "low", "medium", "high", or "xhigh".
4. Check Copilot IDE settings. If you have explicit model overrides in VS Code, JetBrains, or CLI settings, verify they point to gpt-5.3-codex or gpt-5.5.
5. Evaluate GPT-5.5 if you are on a mixed workload. For agents that combine coding with document generation, analysis, or multimodal inputs, GPT-5.5 is now recommended as the primary model.

July 23 is 51 days out. The migration is a one-line change. Do it before it is urgent.