Claude Opus 4.8 vs GPT-5.5: Complete Benchmarks and Pricing Comparison

Anthropic's Opus 4.8 also maintains Opus 4.7's pricing — no increase despite meaningful benchmark gains . GPT-5.5, by contrast, doubled the API price of its predecessor GPT-5.4, though OpenAI argues that token efficiency improvements make the effective cost increase closer to 20% .

All three models support prompt caching at roughly 90% savings on cached input tokens and offer batch processing at a 50% discount .

GPT-5.5 also has a Pro tier at $30/$180 per million tokens, aimed at research-grade workloads . Claude Opus has no equivalent tier.

Benchmark Scores: Opus 4.8's Strengths Are Agentic

Direct model comparisons are complicated by different benchmark versions and testing protocols. Where scores are available on the same test, Opus 4.8 leads GPT-5.5 in the areas developers care most about.

Agentic Coding: A 10.6-Point Gap

SWE-bench Pro is the most widely cited benchmark for real-world software engineering tasks, and Opus 4.8 scores 69.2% against GPT-5.5's 58.6% — a lead of 10.6 percentage points . Opus 4.7 was already ahead at 64.3%, and Opus 4.8 extends that advantage. Anthropic's announcement highlights faster task completion and 4x fewer code bugs compared to prior models .

Terminal-Bench: Different Versions, Different Stories

This benchmark requires careful reading. GPT-5.5 reports 82.7% on Terminal-Bench 2.0 , while Opus 4.8's 74.6% was measured on Terminal-Bench 2.1, a newer version . The two are not directly comparable. Additionally, OpenAI's 82.7% claim has faced scrutiny; the benchmark owner's leaderboard showed 82.0% ± 2.2 on the same day . Opus 4.7 scored 69.4% on Terminal-Bench 2.0 , and independent tests using different harnesses have found GPT-5.5 sometimes underperforming GPT-5.4 on this benchmark .

Knowledge Work and Agentic Behavior

On GDPval-AA, a knowledge work evaluation, Opus 4.8 achieves an Elo score of 1890 compared to GPT-5.5's 1769 — a roughly 7% advantage . Opus 4.8 is also the first model to achieve a 100% completion rate on Anthropic's Super-Agent benchmark, meaning it successfully executed every end-to-end agentic task in the test suite . GPT-5.5 did not reach 100%.

On agentic computer use (OSWorld-Verified), the scores cluster closer: Opus 4.8 at 83.4%, GPT-5.5 at 78.7%, and Opus 4.7 at 82.8% . These are improvements measured in single-digit points, not generational leaps.

Where GPT-5.5 Might Still Lead

GPT-5.5's benchmark coverage is thinner on the shared benchmarks Anthropic published with Opus 4.8, partly because OpenAI focuses on different metrics. On GPQA Diamond (graduate-level science reasoning), Opus 4.7 hit 94.2% , while earlier comparisons showed GPT-5.4 had a slight edge over Opus 4.7 on pure mathematical reasoning and some knowledge-recall tests . No direct GPQA comparison between Opus 4.8 and GPT-5.5 is yet available, though Opus 4.8 is reported at 93.6% .

OpenAI also claims GPT-5.5 uses roughly 40% fewer output tokens per coding task than GPT-5.4, which could partially offset its higher per-token price on certain workloads .

Context Window and Other Specs

All three models converge on a 1-million-token context window, though Anthropic documents Opus 4.8's maximum output at 128K tokens per request . GPT-5.5's maximum output is listed at 32K tokens .

Claude's fast mode is optional and runs at roughly 2.5x speed. Anthropic says fast mode for Opus 4.8 is three times cheaper than fast inference on previous Opus generations . GPT-5.5 does not offer an equivalent premium-speed tier.

The Controversial Numbers Problem

Independent benchmarks should be read with their limitations in mind:

• GPT-5.5's CursorBench scores on alternative harnesses were lower than GPT-5.4's in some community tests, raising questions about how representative OpenAI's self-reported numbers are .
• Terminal-Bench versions differ across these models, making cross-model leaderboard rankings unreliable if you don't check the version number .
• SWE-bench Pro is the cleanest shared benchmark, and it consistently favors Claude across multiple releases. On this metric, the gap between Opus 4.8 and GPT-5.5 is large enough to be a real workflow difference.

Which Model Should You Choose?

Choose Claude Opus 4.8 if: agentic coding, computer-use tasks, knowledge work, or long-context operations dominate your workload. It leads on every shared benchmark where comparisons are possible, and the pricing is unchanged from Opus 4.7.

Choose GPT-5.5 if: you're deeply embedded in the OpenAI ecosystem, prioritize pure mathematical reasoning, or expect token-efficiency gains to offset the higher per-token price on your specific prompt patterns.

Stick with Opus 4.7 if: you want frontier-level agentic coding (64.3% SWE-bench Pro is still well ahead of GPT-5.5) and don't need the specific gains Opus 4.8 brings — but given the identical price, there's little reason not to upgrade.

For developers running output-heavy agents or long-document analysis, Claude Opus's 17% cheaper output pricing and flat long-context rates make a concrete difference to monthly API bills.