Which is better for coding in May 2026 — GPT-5.5 or Claude Opus 4.7?

Depends on benchmark. GPT-5.5 leads Terminal-Bench 2.0 (82.7% vs Opus 4.7's 69.4% per DataCamp's May 2026 test). Opus 4.7 leads SWE-Bench Pro for real GitHub issue resolution (64.3% vs 58.6%). Translation: GPT-5.5 wins on terminal/agentic loops, Opus 4.7 wins on careful production patches. For day-to-day coding, Opus 4.7 produces more reviewable code; for autonomous long runs, GPT-5.5 finishes more tasks.

What does the AISI cybersecurity eval show?

GPT-5.5 hit 71.4% pass rate on AISI's Expert-tier cyber tasks (vs Mythos Preview 68.6%, GPT-5.4 52.4%, Opus 4.7 48.6%) and completed AISI's 32-step 'The Last Ones' attack range end-to-end in 2 of 10 attempts — a first for any frontier model. AISI flagged GPT-5.5 as the first model needing extra deployment safeguards on offensive cyber capability. Opus 4.7 lags here, partly by Anthropic design choice.

How does pricing compare?

GPT-5.5 is roughly $5/M input + $15/M output tokens via OpenAI API. Claude Opus 4.7 is $15/M input + $75/M output tokens — 3-5x more expensive on output. Sonnet 4.7 (Anthropic's mid-tier) is $3/M input + $15/M output and matches GPT-5.5's pricing while losing only modestly on benchmarks. For most production work, Sonnet 4.7 is the cost-rational Anthropic pick; Opus 4.7 is for hardest tasks only.

Which model should I build my product on?

Build on the API that fits your workflow: GPT-5.5 if your stack lives in autonomous long-running agentic loops; Opus 4.7 if you ship code patches that need to pass code review; Sonnet 4.7 if you want Anthropic quality at GPT-5.5 prices. Most production teams in May 2026 hedge: route easy tasks to Sonnet 4.7, hard tasks to Opus 4.7 or GPT-5.5 depending on which one their harness handles better.

Quick Answer

GPT-5.5 vs Claude Opus 4.7: Real Pick (May 2026)

Published: May 3, 2026

GPT-5.5 vs Claude Opus 4.7: Real Workflow Pick (May 2026)

The two flagships shipped 7 days apart in April 2026. A month later, the benchmark dust has settled — and the picks are clearer than the leaderboard ranking suggests. GPT-5.5 dominates terminal-loop benchmarks. Opus 4.7 dominates real GitHub issue resolution. Here’s the May 2026 decision guide.

Last verified: May 3, 2026

Headline numbers

Benchmark	GPT-5.5	Claude Opus 4.7	Notes
Terminal-Bench 2.0	82.7%	69.4%	DataCamp May 2026 test; GPT-5.5 dominates
SWE-Bench Pro	58.6%	64.3%	RevolutionInAI May 2026; Opus wins production patches
SWE-Bench Verified	~75%	~74%	Effectively tied at the top
AISI Expert cyber tasks	71.4%	48.6%	AISI eval; GPT-5.5 is first model flagged for extra safeguards
OSWorld-Verified (computer use)	76.4%	73.1%	GPT-5.5 leads
Tool-call reliability	High	High	Both ship-quality
Long-context reasoning (1M tok)	Strong	Strongest	Opus 4.7 leads at 500K+ token recall

Key takeaway: GPT-5.5 is a stronger autonomous agent. Opus 4.7 is a more careful coder. The numbers reflect different design choices, not one model being “better.”

Pricing (May 2026)

Model	Input ($/M tok)	Output ($/M tok)	Notes
GPT-5.5	$5	$15	OpenAI API; included in Plus/Pro at use limits
Claude Opus 4.7	$15	$75	Anthropic API; ~3-5x more expensive on output
Claude Sonnet 4.7	$3	$15	The cost-rational Anthropic pick — matches GPT-5.5 pricing, ~92% of Opus 4.7 quality
Gemini 3.1 Pro	$2	$12	Cheapest of the frontier three

Output cost matters most for coding agents (which generate large diffs). Over a month of heavy agent use, Opus 4.7 can run $400-1200 vs GPT-5.5’s $100-400. That’s the bigger story than benchmarks.

When to pick GPT-5.5

GPT-5.5 wins for:

Autonomous long-running coding agents. The Terminal-Bench 2.0 lead (82.7%) is real — GPT-5.5 stays on track through 30-50 turn loops better than Opus 4.7.
Computer use / browser agents. OSWorld-Verified leads + native vision + agentic training make it the best computer-use model.
Codex CLI users. GPT-5.5 is the default and best-tuned model for OpenAI’s coding harness.
Cost-sensitive at scale. $5/$15 vs Opus $15/$75 means GPT-5.5 wins on cost-per-finished-task.
Cybersecurity research / red team work. AISI eval shows the strongest offensive cyber capability among public models — controversial but real.

When to pick Claude Opus 4.7

Opus 4.7 wins for:

Production patches that need to pass code review. SWE-Bench Pro (64.3% vs 58.6%) tracks “would a senior engineer merge this?” Opus 4.7 generates more reviewable diffs.
Long-context document analysis. Best 500K-1M token recall; ideal for reading whole codebases or large legal documents in one pass.
Careful refactors / architectural decisions. Opus 4.7’s slower, more deliberate reasoning style produces fewer regressions on multi-file changes.
Claude Code users. Opus 4.7 is best-tuned for Claude Code’s harness — and Claude Code’s skills + sub-agent ecosystem is the largest in May 2026.
Safety-sensitive deployments. Anthropic’s design choices score lower on offensive cyber by intent — useful for organizations that want lower-capability defaults on harm-adjacent tasks.

When to pick neither — pick Sonnet 4.7

For 80% of production workloads in May 2026, Claude Sonnet 4.7 is the cost-rational pick:

$3/$15 pricing matches GPT-5.5
~92% of Opus 4.7’s quality on most coding tasks
Faster than Opus 4.7
Native to Claude Code with full skills/sub-agent support

If you’re spending more than $500/month on Opus 4.7, run a 2-week test routing the easy 70% of tasks to Sonnet 4.7. Most teams cut spend 50-70% with no quality loss.

Decision tree

Building a long-running autonomous agent? → GPT-5.5
Generating production patches that need review? → Opus 4.7
Already paying for ChatGPT Pro? → GPT-5.5 via Codex CLI
Already on Claude Pro/Max? → Opus 4.7 (or Sonnet 4.7 for cost)
Doing computer-use / browser agents? → GPT-5.5
Reading whole codebases (500K+ tokens)? → Opus 4.7
Cost-sensitive, need frontier quality? → Sonnet 4.7 or Gemini 3.1 Pro
Don’t want to pick — want vendor freedom? → Run OpenCode and route per task

What about Mythos Preview?

Anthropic’s Claude Mythos Preview (internal codename “Capybara”) is a tier above Opus and ranks #1 on BenchLM.ai’s provisional leaderboard with a 99/100 overall score. It leads SWE-Bench Pro at 77.8%. But it’s not a model you can procure today — Mythos Preview remains in restricted research access in May 2026 and isn’t part of any production decision. Watch for general availability later in 2026.

Bottom line

GPT-5.5 vs Opus 4.7 isn’t a “which is smarter” question — it’s “which fits your workflow.” Long autonomous loops, computer use, cost-per-task → GPT-5.5. Reviewable code patches, long-context reading, careful refactors → Opus 4.7. For most production teams, the right answer is Sonnet 4.7 plus an Opus 4.7 fallback — and routing the easy 70% of work to the cheaper model.

Sources: DataCamp Terminal-Bench 2.0 May 2026 head-to-head, RevolutionInAI SWE-Bench Pro analysis, AISI Cybersecurity Evaluation May 1 2026, OpenAI / Anthropic pricing pages, BenchLM.ai leaderboard, llm-stats.com.