GPT-5.4 Guide: OpenAI's Autonomous Agent Model (2026)
GPT-5.4 scores 75% on OSWorld, beating humans at computer use. 1M context, $2.50/MTok, 5 model variants. Full benchmarks, pricing, and comparison guide.
TL;DR
OpenAI released GPT-5.4 on March 5, 2026 — the first general-purpose model to beat humans at autonomous computer use. Key stats:
| Feature | Detail |
|---|---|
| OSWorld-Verified | 75.0% — surpasses human baseline (72.4%) |
| SWE-bench Pro | 57.7% — strong coding, but trails Claude Opus 4.6 (80.8%) |
| Context Window | Up to 1.05M tokens (272K standard, 1M extended) |
| Computer Use | Native, state-of-the-art — first built into a general model |
| Token Efficiency | Significantly fewer tokens than GPT-5.2 for equivalent tasks |
| API Price | $2.50 input / $15.00 output per 1M tokens |
| Variants | Standard, Thinking, Pro, Mini, Nano |
| Interactive Thinking | Upfront plan + mid-response steering |
What Is GPT-5.4?
GPT-5.4 is OpenAI's flagship large language model, released March 5, 2026. It combines the best of GPT-5.3 Codex's coding strengths with breakthrough autonomous computer-use capabilities, a 1-million-token context window, and a new interactive thinking system.
The headline: GPT-5.4 is the first general-purpose AI model to exceed human performance on desktop computer tasks. It scores 75.0% on OSWorld-Verified — a benchmark where human expert testers score 72.4%. No other model had cleanly crossed that threshold before.
This is a 28-point improvement over GPT-5.2 (47.3%) in under four months. The model can parse screen coordinates from screenshots and issue mouse and keyboard commands directly, allowing it to navigate files, browsers, terminals, and productivity software autonomously.
Key Features
Native Computer Use
Unlike previous models that needed external tooling for computer control, GPT-5.4 has computer-use capabilities built in. In the Codex app and via the API, the model can:
- Navigate desktop environments through screenshots and keyboard/mouse actions
- Operate across multiple applications in sequence
- Complete multi-step workflows (file management, browser tasks, terminal operations)
- Handle productivity software like spreadsheets, presentations, and documents
1 Million Token Context Window
GPT-5.4 supports up to 1.05M tokens of context. The standard window is 272K tokens; requests that exceed this threshold are processed at 2x the normal input rate. This massive context is critical for agentic workflows where the model needs to hold long tool-use histories, large codebases, or extended document sets in memory.
Interactive Thinking
GPT-5.4 Thinking introduces a new paradigm: the model provides an upfront plan of its reasoning, and you can steer it mid-response. Add instructions, correct course, or refine the direction without starting over. This is a significant quality-of-life improvement for complex, multi-step tasks.
Improved Token Efficiency
OpenAI reports GPT-5.4 uses significantly fewer tokens to solve problems compared to GPT-5.2, along with a 33% reduction in factual errors. For production deployments, this means lower costs per task even before accounting for the competitive pricing.
Benchmarks
Where GPT-5.4 Leads
| Benchmark | What It Tests | GPT-5.4 | Best Competitor |
|---|---|---|---|
| OSWorld-Verified | Desktop computer use | 75.0% | Claude Opus 4.6: 72.7% |
| Toolathlon | Multi-step tool/API use | Top score | — |
| GDPval | Knowledge work | 83% | — |
Full Model Comparison
| Benchmark | GPT-5.4 | Claude Opus 4.6 | Gemini 3.1 Pro |
|---|---|---|---|
| OSWorld-Verified | 75.0% | 72.7% | N/A |
| SWE-bench Verified | ~80% | 80.8% | 80.6% |
| SWE-bench Pro | 57.7% | ~45% | 54.2% |
| ARC-AGI-2 | 52.9% | 68.8% | 77.1% |
| GDPval | 83% | — | — |
What the Numbers Mean
GPT-5.4 is the first model that credibly handles computer use, coding, and knowledge work at frontier level simultaneously. The 75% OSWorld score is the clearest milestone — it means the model can complete three out of four real desktop tasks that even expert humans find challenging.
However, the picture is nuanced. On SWE-bench Verified (real-world coding), Claude Opus 4.6 and Gemini 3.1 Pro both significantly outperform GPT-5.4 at 80.8% and 80.6% respectively. On abstract reasoning (ARC-AGI-2), GPT-5.4 trails Claude Opus 4.6 by 16 percentage points and Gemini 3.1 Pro by over 24 points.
The takeaway: GPT-5.4 wins on autonomous computer control and practical tool use, but it is not the best model for every task.
Model Variants and Pricing
GPT-5.4 ships in five variants, each targeting different use cases and budgets:
| Variant | Input (per 1M tokens) | Output (per 1M tokens) | Best For |
|---|---|---|---|
| GPT-5.4 Standard | $2.50 | $15.00 | General-purpose, computer use, agentic workflows |
| GPT-5.4 Thinking | $2.50 | $15.00 | Complex reasoning with interactive plan steering |
| GPT-5.4 Pro | $30.00 | $180.00 | Legal, medical, financial — max accuracy |
| GPT-5.4 Mini | $0.75 | $4.50 | High-volume, latency-sensitive workloads |
| GPT-5.4 Nano | TBD | TBD | Edge and embedded use cases |
- Prompts exceeding 272K tokens are charged at 2x the standard input rate ($5.00/MTok for Standard).
- Regional data residency endpoints carry a 10% surcharge across all variants.
- GPT-5.4 Mini is available to free-tier ChatGPT users; Nano is API-only.
Cost Comparison: GPT-5.4 vs Claude Opus 4.6
For a typical daily workload:
| GPT-5.4 | Claude Opus 4.6 | |
|---|---|---|
| Avg. daily cost | ~$5.50 | ~$10.00 |
| Avg. monthly cost | ~$165 | ~$300 |
| Cost ratio | 1x | ~1.8x |
GPT-5.4 is roughly 50% cheaper than Claude Opus 4.6 for equivalent token throughput. The Mini variant pushes this further — scoring 54.38% on SWE-bench Pro at roughly 6x lower cost.
GPT-5.4 vs Claude Opus 4.6: When to Use Which?
This is the question most teams are asking in April 2026. The answer depends on your workload.
Choose GPT-5.4 If You Need:
- Desktop automation and computer use — 75.0% OSWorld vs 72.7% for Opus 4.6
- Tool calling and API orchestration — better accuracy in fewer steps on Toolathlon
- Cost efficiency — roughly half the per-token cost of Opus 4.6
- Token-efficient reasoning — fewer tokens per problem means lower bills
- Rapid prototyping — fast iteration with lower overhead
Choose Claude Opus 4.6 If You Need:
- Complex multi-file code refactoring — leads SWE-bench Verified at 80.8%
- Long-context coherence — stronger at maintaining quality across very long contexts
- Abstract and novel reasoning — 16-point lead on ARC-AGI-2
- Agentic search and deep code architecture — excels at tasks requiring deep understanding
- Writing quality and nuance — ranked #1 in Chatbot Arena user satisfaction
Head-to-Head Summary
| Dimension | Winner | Margin |
|---|---|---|
| Computer Use (OSWorld) | GPT-5.4 | 75.0% vs 72.7% |
| Coding (SWE-bench Verified) | Claude Opus 4.6 | 80.8% vs ~80% |
| Abstract Reasoning (ARC-AGI-2) | Claude Opus 4.6 | 68.8% vs 52.9% |
| Tool Calling (Toolathlon) | GPT-5.4 | Fewer steps, better accuracy |
| Knowledge Work (GDPval) | GPT-5.4 | 83% |
| Pricing | GPT-5.4 | ~50% cheaper |
| User Satisfaction | Claude Opus 4.6 | #1 Chatbot Arena |
How to Access GPT-5.4
GPT-5.4 is available through:
- ChatGPT — GPT-5.4 Thinking is the default model for Plus, Pro, and Team users. Mini is available for free-tier users.
- OpenAI API — All five variants accessible via the standard completions and chat endpoints.
- Codex App — Full computer-use capabilities with the desktop agent.
- OpenRouter — Third-party access at competitive rates.
computer_use tool parameter and provide screenshots as image inputs. The model returns structured actions (click, type, scroll) that your application translates into system events.
FAQ
Is GPT-5.4 better than Claude Opus 4.6?
It depends on the task. GPT-5.4 wins on computer use, tool calling, and cost efficiency. Claude Opus 4.6 wins on complex coding, abstract reasoning, and writing quality. For most teams, the choice comes down to whether your primary workload is desktop automation (GPT-5.4) or deep software engineering (Opus 4.6).
How much does GPT-5.4 cost?
The standard model costs $2.50 per million input tokens and $15.00 per million output tokens. The Pro variant is $30/$180 per MTok. Mini is $0.75/$4.50 per MTok. Prompts exceeding 272K tokens are charged at double the input rate.
Can GPT-5.4 really use a computer better than humans?
On the OSWorld-Verified benchmark, yes — 75.0% vs the human expert baseline of 72.4%. However, benchmarks measure specific task categories. Real-world computer use involves judgment, context, and adaptability that benchmarks do not fully capture. It is best thought of as superhuman on structured desktop tasks, not a wholesale replacement for human computer use.
What is the context window for GPT-5.4?
Up to 1.05 million tokens. The standard tier is 272K tokens. Extending beyond 272K doubles the input token cost. The full 1M context is critical for agentic workflows that accumulate long interaction histories.
Should I upgrade from GPT-5.3 Codex?
If your workload involves computer use or multi-tool orchestration, yes. The jump from 64.7% to 75.0% on OSWorld is substantial. For pure coding tasks, the improvement over GPT-5.3 Codex is more incremental — SWE-bench Pro went from 56.8% to 57.7%. Evaluate based on your specific use case.
What model variants are available?
Five: Standard, Thinking, Pro, Mini, and Nano. Standard and Thinking share the same pricing and are the main models for most use cases. Pro is the premium tier for maximum accuracy. Mini targets cost-sensitive production deployments. Nano is designed for edge and embedded applications.
Bottom Line
GPT-5.4 marks a genuine inflection point for autonomous AI agents. It is the first general-purpose model to beat human experts at desktop computer use, and it does so while being 50% cheaper than its main competitor. The five-variant lineup means there is a GPT-5.4 for every budget and latency requirement.
That said, it is not the best at everything. Claude Opus 4.6 remains the stronger choice for complex software engineering and abstract reasoning. Gemini 3.1 Pro still leads on several reasoning benchmarks. The right answer for most teams is not "which model is best" but "which model is best for this task."
If you are building AI-powered products and want to leverage models like GPT-5.4 and Claude Opus 4.6 without getting bogged down in infrastructure, Y Build helps you ship faster. We provide the tools and platform to build, deploy, and iterate on AI applications — so you can focus on the product, not the plumbing.
Sources: OpenAI GPT-5.4 Announcement, OpenAI API Pricing, NxCode GPT-5.4 Complete Guide, NxCode GPT-5.4 vs Claude Opus 4.6, DataCamp GPT-5.4 Overview, Artificial Analysis GPT-5.4, MindStudio Benchmark Comparison, Nerd Level Tech: GPT-5.4 Beats Humans