GPT-5.3 Codex is the better value play at 60-75% lower cost, with the highest-ever OSWorld score (64.7%) and strong general reasoning. Claude Opus 4.6 is the better choice for complex, long-running agent workflows and large codebases with its 1M context window and Agent Teams. Both launched February 5, 2026.
TL;DR: Budget-sensitive? GPT-5.3. Complex agent workflows? Opus 4.6. Most teams will use both.
February 5, 2026 will be remembered as the day the AI coding race turned into a full sprint. OpenAI shipped GPT-5.3 Codex with the highest OSWorld score ever recorded. Anthropic countered with Opus 4.6 and Agent Teams. Both dropped within hours of each other.
For developers choosing between them, the decision is no longer about which model is "better." It is about which model fits your workflow, budget, and the type of work you actually do.
This breakdown covers the benchmarks, pricing math, agent capabilities, and practical tradeoffs so you can make an informed choice.
Head-to-Head Benchmarks
Nine benchmarks that matter for real-world coding work. Winners are color-coded.
Head-to-Head Benchmarks
Score (%) on key developer benchmarks. Higher is better.
Sources: OpenAI, Anthropic, Terminal-Bench, OSWorld. Approximate values where exact figures not published.
| Benchmark | GPT-5.3 Codex | Claude Opus 4.6 |
|---|---|---|
| Terminal-Bench (Overall) | 77.3% | #1 (est. ~80%+) |
| OSWorld (Computer Use) | 64.7% | ~42% (Sonnet 4.6) |
| SWE-Bench Verified | ~75% | ~80% |
| MMLU-Pro | ~88% | ~86% |
| GPQA Diamond | ~72% | ~70% |
| HumanEval+ | ~92% | ~91% |
| Finance Agent Bench | N/A | #1 |
| Agentic Coding (Multi-step) | Strong | Strong |
| Multimodal Reasoning | Native video + audio | Image + text |
Sources: OpenAI, Anthropic, Terminal-Bench, OSWorld leaderboards. Updated Feb 17, 2026.
Specs at a Glance
| Spec | GPT-5.3 Codex | Claude Opus 4.6 |
|---|---|---|
| Context Window | 400K tokens | 1M tokens (beta) |
| Max Output | ~64K tokens | 128K tokens |
| Input Price | $1.25 / 1M tokens | $5 / 1M tokens |
| Output Price | $10 / 1M tokens | $25 / 1M tokens |
| Agent Framework | Interactive Steering | Agent Teams |
| Computer Use | OSWorld: 64.7% | Available (lower score) |
| Release Date | February 5, 2026 | February 5, 2026 |
| Availability | API, ChatGPT Pro | API, claude.ai, Copilot |
Terminal-Bench: The Benchmark That Actually Matters
Terminal-Bench measures how well models perform real developer tasks in a terminal environment: debugging, file manipulation, build configuration, and multi-step coding workflows. It is widely considered the most practical coding benchmark available.
GPT-5.3 Codex scored 77.3% on Terminal-Bench, placing it as the second-highest model. Claude Opus 4.6 holds the overall #1 ranking. Both models significantly outpace the previous generation. For comparison, GPT-5.2 scored roughly 25% lower than GPT-5.3.
The gap is meaningful but narrow. In practical terms, both models handle most terminal-based coding tasks well. The difference shows up in multi-step workflows where Opus 4.6's Agent Teams give it an edge by parallelizing work across multiple agent instances.
OSWorld: Where GPT-5.3 Pulls Ahead
OSWorld tests a model's ability to operate a computer like a human: clicking buttons, navigating menus, filling forms, and automating GUI workflows. GPT-5.3 Codex scored 64.7%, the highest ever recorded on this benchmark.
This is a category where the gap is wide. Claude's best computer-use score (via Sonnet 4.6) sits around 42%. If your workflow involves browser automation, desktop application testing, or any kind of GUI-driven task, GPT-5.3 Codex has a clear advantage.
Pricing: The Math That Actually Matters
The price difference between these models is substantial and will drive many real-world decisions.
GPT-5.3 Codex
$1.25 / $10
per 1M input / output tokens
Claude Opus 4.6
$5 / $25
per 1M input / output tokens
For a concrete example: processing 10 million input tokens and 2 million output tokens per day costs roughly $32.50/day with GPT-5.3 Codex vs $100/day with Opus 4.6. Over a month, that is $975 vs $3,000. The difference compounds fast at scale.
However, cost per token does not equal cost per task. If Opus 4.6's Agent Teams complete a complex task in one pass that would take GPT-5.3 three attempts, the effective cost flips. The right comparison is cost per successful outcome, not cost per token.
Context Window: 400K vs 1M Tokens
Claude Opus 4.6 offers a 1 million token context window (in beta), while GPT-5.3 Codex provides 400,000 tokens. Both are massive improvements over previous generations.
In practice, 400K tokens covers most codebases and documents you would need to analyze in a single session. The 1M window matters for specific workflows: analyzing an entire monorepo, processing legal contracts end-to-end, or maintaining context across very long coding sessions where you need the model to remember decisions made hundreds of thousands of tokens ago.
Opus 4.6 also generates up to 128K output tokens vs GPT-5.3's ~64K. For generating long documents, comprehensive code reviews, or multi-file refactors, this output limit matters.
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Agent Teams vs Interactive Steering
The biggest architectural difference between these models is how they handle agentic workflows.
Claude Opus 4.6's Agent Teams split work across multiple parallel agents. One agent researches, another writes code, a third reviews. They coordinate automatically. This approach excels at complex tasks that have naturally separable components: building a feature that requires API changes, frontend updates, and test coverage simultaneously.
GPT-5.3 Codex's Interactive Steering takes a different approach. Instead of splitting work across agents, it lets you guide a single agent session in real-time, adjusting direction as the model works. This feels more like pair programming where you steer while the AI codes.
Neither approach is universally better. Agent Teams is stronger for well-defined, decomposable tasks. Interactive Steering is stronger for exploratory work where you are not sure exactly what you want until you see it taking shape.
Safety and Reliability
Both companies have invested heavily in safety for this generation. OpenAI reports GPT-5.3 was tested by over 100 external red teamers and integrates "monitor" models that flag risky outputs. Anthropic highlights that Opus 4.6 "never lies to the user or actively deceives them" and includes training-level safety measures rather than bolted-on filters.
In practice, both models occasionally refuse reasonable coding requests due to false positive safety triggers. This is a known tradeoff with frontier models. For enterprise deployments, Anthropic's more conservative safety stance and Claude's ad-free positioning may carry weight with compliance teams.
When to Choose Each Model
Choose GPT-5.3 Codex
- ✓Budget matters and you need high-volume output
- ✓GUI automation, browser testing, or computer use
- ✓Multimodal workflows (video, audio, images)
- ✓Solo developer doing iterative "vibe coding"
- ✓General knowledge and reasoning tasks
Choose Claude Opus 4.6
- ✓Complex multi-agent workflows (Agent Teams)
- ✓Large codebase analysis (1M context window)
- ✓Long-form output generation (128K tokens)
- ✓Finance, legal, or compliance-heavy domains
- ✓Enterprise environments prioritizing safety
What This Means for Development Teams
The simultaneous release of these two models on the same day tells you everything about the current state of AI development tools. The race is real, and developers are the ones benefiting.
The practical takeaway: stop thinking about "which model is best" and start thinking about which model is best for which task. The smartest teams in 2026 are already using model routers that send cheap, high-volume tasks to GPT-5.3 and complex, high-stakes tasks to Opus 4.6.
Both models will keep improving. OpenAI has hinted at GPT-5.4 with expanded reasoning, and Anthropic just shipped Sonnet 4.6 alongside Opus 4.6 within two weeks. The competitive pressure means faster iteration, lower prices, and better tools for everyone building software.
Methodology and Sources
Benchmark data sourced from OpenAI, Anthropic, Terminal-Bench leaderboard, and OSWorld leaderboard as of February 17, 2026. Pricing reflects official API rates at time of publication. Where exact benchmark numbers are not publicly available, we note estimates based on independent testing and leaderboard positioning. "Winner" designations reflect the current public data and may shift as more detailed benchmarks are published.
