Model details
GPT-5.4
GPT-5.4 is a frontier reasoning model from OpenAI that unifies coding, tool use, and professional task handling into a single general-purpose system, absorbing the coding capabilities of GPT-5.3-Codex while extending into spreadsheets, presentations, and document workflows. In ChatGPT it ships as GPT-5.4 Thinking with the ability to surface an upfront plan of its reasoning so users can steer mid-response, and it improves deep web research on highly specific queries while keeping better that quick-info value across longer thinking traces. In the API and Codex, the release marks OpenAI's first general-purpose model with native, state-of-the-art computer-use capabilities, letting agents operate software environments and stitch together multi-step workflows across applications.
For practitioners, GPT-5.4 is aimed at complex real work where accuracy and efficiency matter more than breadth of modalities: agentic coding, enterprise document tasks, and long-horizon research that benefits from extended reasoning. The model's broad rollout inside GitHub Copilot highlights its role in software engineering workflows, where teams pair it with governance and security controls to balance productivity against operational risk. The Pro tier targets users who need maximum performance on hard problems, while the standard release prioritizes faster, more relevant answers with less back-and-forth, making it a strong fit for professional teams that want a single capable model for reasoning, coding, and tool-driven automation rather than a stack of narrow specialists.
Quick Info
Powered by- Provider
- Databricks
- Model key
- databricks-gpt-5-4
- Release date
- Mar 5, 2026
- Last updated
- Mar 5, 2026
- Knowledge cutoff
- 2025-08-31
- Input modalities
- Output modalities
- Capabilities
Cost
- Input token cost
- $2.50
- Output token cost
- $15.00
Limits
- Input tokens
- 922,000 tokens
- Output tokens
- 128,000 tokens
- Context window
- 1,050,000 tokens
OpenCode
Model variants
Transparent token rates
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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
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