GPT-5.5 vs Claude Opus 4.8 (2026): Benchmarks, Pricing & Which to Use
Both released within weeks of each other in 2026 as OpenAI and Anthropic's flagship models. GPT-5.5 leans into occupation-specific knowledge work; Claude Opus 4.8 leans into agentic coding and computer use. Here's how they actually compare.
Quick Verdict
Best for finance, customer service, and general knowledge-work agents
Best for agentic coding and large codebase migrations
Bottom line: Choose GPT-5.5 if your workload is general professional knowledge work — finance modeling, customer-service automation, or tasks that benefit from its 1M token context window. Choose Claude Opus 4.8 if you're running agentic coding pipelines, since dynamic workflows and its honesty improvements directly reduce compounding errors in autonomous coding.
GPT-5.5 vs Claude Opus 4.8: Feature Comparison
| Feature | GPT-5.5 | Claude Opus 4.8 |
|---|---|---|
| Release date | April 23, 2026 | May 28, 2026 |
| Core strength | Occupation-specific knowledge work (finance, customer service) | Agentic coding, honesty, computer use |
| Standout benchmark | 84.9% GDPval (44-occupation knowledge work) | 84% Online-Mind2Web (computer use) |
| Context window | 1M tokens | 200K tokens |
| Input price (per 1M tokens) | $5 | $5 |
| Output price (per 1M tokens) | $30 | $25 |
| Higher-accuracy variant | GPT-5.5 Pro ($30/$180 per 1M) | Fast mode ($10/$50 per 1M, speed not accuracy) |
| Agentic infrastructure | Standard tool use + computer use | Dynamic workflows — hundreds of parallel subagents in Claude Code |
| Reliability focus | Professional deliverable accuracy across occupations | 4x fewer false code-confidence claims than Opus 4.7 |
| Best for | Finance, customer service, and general knowledge-work agents | Agentic coding pipelines and large codebase migrations |
Why Choose GPT-5.5
GPT-5.5 is OpenAI's first fully retrained base model since GPT-4.5, and it shows in the benchmark choices — OpenAI leaned on occupation-specific evals like GDPval (44 occupations), FinanceAgent, and investment-banking modeling rather than only generic reasoning tests. That makes it a strong fit for teams building agents meant to produce actual professional deliverables rather than just hold a conversation well.
Its 1M token context window — five times Opus 4.8's 200K — is a real structural advantage for large-document or large-codebase tasks that need to reference more material at once. Tau2-bench Telecom score of 98.0% without prompt tuning also makes it a strong default for customer-service automation that needs to work well out of the box.
Why Choose Claude Opus 4.8
Claude Opus 4.8's dynamic workflows feature is purpose-built for agentic coding at scale — it can plan a large engineering task, spin up hundreds of parallel subagents within a single Claude Code session, and verify outputs before reporting completion. Anthropic has demonstrated full codebase-scale migrations using this feature, using the existing test suite as the quality bar.
The honesty improvements matter just as much in practice: Opus 4.8 is roughly 4x less likely than Opus 4.7 to claim code is working when it isn't, which directly reduces the compounding errors that plague long autonomous coding runs. Output pricing is also 20% cheaper than GPT-5.5 ($25 vs $30 per million tokens), which adds up for output-heavy code-generation workloads.
Frequently Asked Questions
Is GPT-5.5 or Claude Opus 4.8 better?
It depends on the workload. GPT-5.5 was benchmarked heavily on occupation-specific knowledge work — 84.9% on GDPval, 98.0% on Tau2-bench Telecom customer-service workflows, and strong scores on financial modeling tasks. Claude Opus 4.8 was benchmarked on agentic coding and computer use — 84% on Online-Mind2Web and a 4x reduction in false code-confidence versus Opus 4.7. Teams building finance, customer-service, or general knowledge-work agents tend to get more value from GPT-5.5; teams running agentic coding pipelines or large codebase migrations tend to get more value from Opus 4.8.
Which is cheaper, GPT-5.5 or Claude Opus 4.8?
Input pricing is identical at $5 per million tokens. Output pricing favors Opus 4.8 slightly at $25 per million tokens versus GPT-5.5's $30 per million tokens. For output-heavy workloads (long-form generation, extensive code output), that 20% output price difference compounds — Opus 4.8 is the cheaper choice at scale for those use cases.
Which model has a bigger context window?
GPT-5.5 ships with a 1 million token context window in the API, five times larger than Claude Opus 4.8's 200K token window. For tasks involving very large codebases, long documents, or multi-file agentic work that needs to hold more context at once, GPT-5.5's window is a meaningful structural advantage.
Which model is better for coding?
Claude Opus 4.8 is purpose-built for agentic coding — its dynamic workflows feature lets it plan a large engineering task and launch hundreds of parallel subagents within a single Claude Code session, verifying outputs before reporting completion. It's also 4x less likely than its predecessor to claim broken code is working, which matters directly for autonomous coding reliability. GPT-5.5's coding capability is strong but its headline benchmarks target broader knowledge work rather than coding specifically.
Do I need the Pro/Fast variants of either model?
GPT-5.5 Pro ($30/$180 per million tokens) trades cost for maximum accuracy on the hardest reasoning and agentic tasks. Claude's Fast mode ($10/$50 per million tokens) trades cost the other direction — it's optimized for lower latency and higher throughput, not higher accuracy. Most teams should start on the standard tier of either model and only move to Pro or Fast mode once they've identified a specific bottleneck (accuracy or speed) in production.
Read the Full Reviews
Get the complete breakdown of benchmarks, pricing, and use cases for each model.
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