AI Model Wars, Feb 2026: Claude Opus 4.6 vs GPT-5.3-Codex

The short version

This isn't a clean win-lose comparison. It's a tooling choice.

Claude Opus 4.6 is about long-horizon work, deep context, and coordination tooling. GPT-5.3-Codex is about fast, agentic coding performance and tight interactive loops.

If you're building complex systems, you'll likely use both-but for different phases.

What changed in February 2026

Claude Opus 4.6

• 1M token context window (first for Opus-class models)
• Better coding, planning, long-horizon agentic tasks
• SOTA on Terminal-Bench 2.0, Humanity's Last Exam, BrowseComp
• +144 Elo vs GPT-5.2 and +190 vs Opus 4.5 on GDPval-AA
• Agent Teams, compaction API, adaptive thinking, effort controls
• Price unchanged: $5/$25 per million input/output tokens

GPT-5.3-Codex

• Most capable agentic coding model to date (OpenAI claim)
• SOTA on SWE-Bench Pro (multilingual) and Terminal-Bench 2.0
• 25% faster than GPT-5.2-Codex
• Interactive steering without losing context
• Strong on OSWorld and GDPval
• First model classified "High" cybersecurity capability

Benchmarks: the hard numbers

Terminal-Bench 2.0

Both models claim SOTA status here, which implies a tight race in command-line and multi-tool tasks.

This suggests parity on pure terminal competence, which is usually the core of "agentic coding."

GDPval-AA

Opus 4.6 leads by +144 Elo over GPT-5.2 and +190 over Opus 4.5.

We don't have a direct GDPval-AA delta against GPT-5.3, but Opus 4.6 is clearly strong on professional knowledge work. GPT-5.3 is described as strong on GDPval as well.

SWE-Bench Pro

GPT-5.3-Codex is SOTA on SWE-Bench Pro (multilingual, four languages).

Opus 4.6 doesn't claim a SWE-Bench Pro SOTA. That makes GPT-5.3-Codex the safer pick for multilingual codebases and bug-fixing tasks benchmarked by SWE-Bench.

Head-to-head: where each model shines

1M context vs interactive steering

Opus 4.6's 1M context window is a structural advantage for long-horizon work.

GPT-5.3-Codex's interactive steering makes it feel more like a collaborator. You can redirect mid-run without losing context, which is a usability edge.

If the work is "load everything, then reason deeply," Opus 4.6 wins. If the work is "iterate fast with human guidance," GPT-5.3-Codex wins.

Planning depth vs execution speed

Opus 4.6 improves long-horizon planning and agentic tasks.

GPT-5.3-Codex is 25% faster and built for coding execution loops. For fast test-fix cycles, speed matters more than maximal context.

Team orchestration vs single-agent strength

Anthropic ships Agent Teams with Opus 4.6: multiple Claude Code instances coordinated by a lead. For a deeper comparison of autonomous agent capabilities, see our Codex vs Claude Opus autonomous agents breakdown.

GPT-5.3-Codex doesn't ship a comparable multi-agent coordination layer in this release. It's strongest as a single agent with interactive steering.

What this means for builders

Use Opus 4.6 for long-horizon, high-context tasks

• Large migrations or refactors spanning multiple repositories
• Security investigations (38/40 ranked best vs Opus 4.5)
• Legal/finance workflows (BigLaw Bench 90.2%; finance +23 vs Sonnet 4.5)

The 1M context window changes what you can do in one run. It reduces orchestration overhead and makes compaction a cost-saving strategy — we explored the full implications in what 1M-token context actually changes.

Use GPT-5.3-Codex for fast, interactive coding

• Bug triage and patching
• Test-fix loops where speed compounds
• Multilingual codebases (SWE-Bench Pro SOTA)

The 25% speed boost and interactive steering make it ideal for tight loops and daily engineering tasks.

Strengths and weaknesses in practice

Claude Opus 4.6 strengths

• Deep context and long-horizon planning
• Coordination tooling (Agent Teams, delegate mode)
• Strong professional domain performance (GDPval-AA, BigLaw Bench)
• Pricing stability at $5/$25 per million tokens

Claude Opus 4.6 weaknesses

• Potentially higher latency for huge contexts
• Agent Teams is new and needs operational guardrails

GPT-5.3-Codex strengths

• SOTA coding benchmark performance
• 25% faster than GPT-5.2-Codex
• Interactive steering without losing context
• Strong on OSWorld for computer-use tasks

GPT-5.3-Codex weaknesses

• No 1M context window
• High cybersecurity capability classification demands governance

A practical decision framework

If you need to "load the universe"

Pick Opus 4.6. The 1M context window is a genuine workflow unlock.

It's the right choice for audits, large refactors, or any task where you need to keep a lot of state alive across days.

If you need to ship quickly

Pick GPT-5.3-Codex. The speed and interactive steering help teams move faster.

It's more suitable for routine engineering workflows where response time matters.

If you need multi‑agent coordination

Opus 4.6's Agent Teams is the current differentiator. We explore how these tools compare in editor-integrated workflows in our Cursor vs Claude Code agentic teams piece.

If your work benefits from multiple specialized agents—docs, tests, infra, code—Claude's tooling is ahead today.

What to watch next

• Whether GPT-5.3-Codex gets a larger context window in a follow-on release.
• Whether Anthropic's Agent Teams matures into a durable orchestration layer.
• Benchmark stability across real-world production workloads.

Bottom line

This is the most interesting two-horse race in AI tooling right now.

Claude Opus 4.6 is the long-horizon, high-context, coordinated agent. GPT-5.3-Codex is the fast, interactive, coding-first agent.

Builders should stop looking for a single "best model" and start optimizing by workload. If you do that, you'll likely use both-and get better outcomes from each.