GPT-5.3 Codex
OpenAI's most capable agentic coding model — autonomous software engineering with vision, reasoning, and tool use.
Overview
What is GPT-5.3 Codex
GPT-5.3 Codex is OpenAI's most capable agentic coding model, released in February 2026. It combines frontier coding performance with advanced reasoning, vision, and tool-use capabilities to handle long-running software engineering tasks autonomously. Users can steer it mid-workflow without losing context, and it is the first OpenAI model that contributed to its own training and deployment.
Running it privately on Venice
On Venice, GPT-5.3 Codex runs under an anonymized privacy tier with zero retention — your prompts are not stored, profiled, or used for training. You get the full agentic coding stack, including tool use, vision, reasoning, and web search, without a ChatGPT subscription or enterprise contract. It is a closed, proprietary model, so you cannot self-host it, but Venice lets you use it permissionlessly with sovereign control over your data.
Assessment
Strengths and limitations
- OpenAI reports new industry-high scores on SWE-Bench Pro and Terminal-Bench, plus strong performance on OSWorld and GDPval, making it a top-tier agentic coding model.
- Native support for vision, tool use, reasoning, web search, and structured JSON output enables end-to-end research, diagnosis, and execution in one model.
- 25% faster than its predecessor and designed for long-horizon tasks that users can steer mid-run without context loss.
- The first OpenAI model used to debug its own training, manage deployment, and evaluate results — a notable milestone in self-improvement.
- On Venice it runs under an anonymized, zero-retention privacy tier with no prompt storage or training reuse.
- Closed and proprietary: no open weights, so self-hosting, auditing, or fine-tuning are impossible outside OpenAI's infrastructure.
- High output pricing ($17.50/1M tokens) can make long agentic runs costly compared to open-weight alternatives.
- No TEE or end-to-end encryption on Venice; privacy is policy-based anonymization, not cryptographic.
- Cybersecurity high-capability safeguards may add friction or restrictions in certain enterprise or defensive use cases.
- Its optimization for agentic software engineering can be overkill for simple chat, creative writing, or low-complexity tasks.
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- OpenAI
- Released
- February 5, 2026
- Architecture
- Proprietary / undisclosed
- Parameters
- Undisclosed
- Modality
- Text, code, and vision
- Open weights
- No — proprietary
- Context window
- 400K tokens
- Max output
- 128K tokens
- Capabilities
- Vision, Function calling, Reasoning, Web search, Code-optimized
- Privacy on Venice
- Anonymized — prompts not stored
- Available on Venice since
- Feb 2026
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai-gpt-53-codex",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $2.19 per 1M input tokens and $17.50 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Best for | Open weights | Price (Venice) |
|---|---|---|---|
| GPT-5.3 Codex | Agentic coding & SWE | No | $2.19 in · $17.50 out / 1M |
| Claude Opus 4.8 | Complex reasoning & 1M context | No | $6 in · $30 out / 1M |
| DeepSeek V3.2 | Open-weight inference | Yes | $0.33 in · $0.48 out / 1M |
| Kimi K2.6 | Open long-context chat | Yes | $0.75 in · $3.50 out / 1M |
The specialist leader for autonomous software engineering with vision, tool use, and web search.
Use cases
What it is good for
- 01Autonomous software engineering: end-to-end feature implementation, bug fixing, and code review across large repositories.
- 02Terminal and infrastructure automation: shell-level operations, deployment scripting, and systems diagnostics.
- 03Multimodal code analysis: reviewing UI mockups, diagrams, or screenshots alongside text to generate or refactor frontend code.
- 04Research and integration tasks: using web search and tool use to evaluate libraries, APIs, and design patterns before writing code.
- 05Long-form technical documentation: generating architecture docs, migration guides, or test plans up to 128K tokens in length.
Prompting
Getting better results
Break large tasks into discrete, verifiable steps — the model excels at long-horizon execution when given clear milestones.
Provide repository context or file trees in the prompt; the large context window can ingest entire modules for holistic changes.
Use structured output (JSON schema) when you need machine-readable results like configuration files, test matrices, or API payloads.
For vision tasks, attach screenshots of UI bugs or diagrams directly and ask for specific code changes rather than vague descriptions.
Version history
Current release — agentic coding with vision and tool use.
FAQ
Frequently asked questions
GPT-5.3 Codex is OpenAI's most capable agentic coding model, released in February 2026. It combines frontier coding performance with reasoning, vision, and tool-use capabilities to autonomously execute long-running software engineering tasks while remaining steerable mid-workflow.
Venice charges $2.19 per 1M input tokens and $17.50 per 1M output tokens, with cached input at $0.22 per 1M. There is no subscription required; you pay per token with credits.
No. GPT-5.3 Codex is a closed, proprietary model with no open weights. You cannot self-host or fine-tune it. For open-weight alternatives, DeepSeek V3.2 or Kimi K2.6 on Venice offer transparent weights and lower cost.
Yes. On Venice it supports function calling, web search, structured JSON output, and reasoning. It can invoke tools, browse the web, and return formatted data for agentic workflows.
Yes. It accepts image inputs, including multiple images in a single prompt, enabling UI screenshot debugging, diagram-to-code, and visual code review.
GPT-5.3 Codex leads on agentic coding benchmarks like SWE-Bench Pro and is optimized for long-horizon software engineering with vision. Claude Opus 4.8 offers a 1M token context and deeper multi-turn reasoning breadth. Choose Codex for autonomous coding agents and Opus for complex generalist reasoning.
It runs under Venice's anonymized privacy tier with zero retention — prompts are not stored, profiled, or used for training. However, there is no TEE or end-to-end encryption; privacy is enforced by policy and infrastructure design.
New Venice accounts receive free credits daily and a welcome bonus, so you can send initial prompts without a credit card. Sustained use requires purchasing credits for the per-token rates.
Run GPT-5.3 Codex privately
No prompt logging. No data used for training.