Both models launched February 5, 2026. I integrated both into my agent platform within 48 hours. The question isn't "which is better." It's "which one for what job."
Should I Use Claude Opus 4.6?
Yes, if your task is ambiguous, multi-step, or requires judgment. Opus 4.6 excels when you can't fully specify the instructions upfront.
Give Opus a complex task and it breaks it into pieces, delegates to sub-agents, and synthesizes the results. Its Agent Teams feature manages multi-agent workflows natively. With a 1M token context window, you can feed it entire codebases, log files, and conversation history at once.
The tradeoff: Opus has higher variance. When it nails a hard problem, the solution is elegant. But it also sometimes reports success when it failed, or makes unrequested changes it thought you'd want. Budget for validation.
Use Opus when: Architecture decisions, multi-system orchestration, root cause analysis, or anything where "figure it out" is the instruction.
Should I Use GPT-5.3 Codex?
Yes, if the task is well-defined and code-heavy. Codex 5.3 is faster, cheaper, and more predictable than Opus for structured work.
Codex scores 77.3% on Terminal-Bench 2.0, 64.7% on OSWorld, and 81.4% on SWE-Lancer IC Diamond. Those aren't vanity numbers. In practice, point it at a failing test suite and it systematically finds and fixes bugs without tangents.
The tradeoff: Codex executes literally. Tell it "add error handling" and you'll get try/catch blocks everywhere, useful or not. Be specific: "Handle network timeouts and rate limits, log to Sentry." Precision in, precision out.
Use Codex when: Generating components, debugging tests, refactoring with clear criteria, or any task where the orchestrator already made the decisions.
How Much Does Each Model Actually Cost?
For a typical coding task (50K token context, 5K token response):
At hundreds of agent tasks daily, that gap compounds fast. My approach: Opus handles the 20% of tasks that need maximum intelligence. Codex handles the 80% that need reliable execution.
What's the Best Way to Use Both Models Together?
Route by task complexity. I run a three-tier system:
Opus decides what to do. Codex does the code-heavy parts. Sonnet handles the volume work. Each model earns its spot based on the cost/capability ratio for that task type.
Are These Models Actually That Different?
Less than you'd think, and the gap is closing. Opus 4.6 feels more precise than earlier Claude models, less prone to hallucination. Codex 5.3 handles broader infrastructure tasks better than expected. It feels more "Claude-like" than previous GPT versions.
Both companies pushed capabilities and speed, sometimes at the cost of hand-holding. Opus is less chatty than Sonnet. Codex needs more explicit instructions than I'd like. The convergence is real: coding agents are becoming general-purpose agents, and general-purpose agents are getting better at code.
The practical takeaway: don't bet your stack on one provider. The models are good enough on both sides that the routing strategy matters more than the model choice.