Model comparison

Claude Opus 5 vs GPT-5.5

Anthropic against OpenAI, compared on context, price, and verified benchmark results.

Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Anthropic

Claude Opus 5

Frontier

OpenAI

GPT-5.5

Frontier

AI model capability comparison
Specification	Claude Opus 5	GPT-5.5
Provider	Anthropic	OpenAI
Tier	Frontier	Frontier
Context window	1M	Winner: 1.05M
Max output	128K	128K
Input / 1M tokens	$5	$5
Output / 1M tokens	Winner: $25	$30
Weights	Closed	Closed
Parameters	Not disclosedUnverified	Not disclosedUnverified
Reasoning levels	adaptive	none, low, medium, high, xhigh, max
Modalities	text, image	text, image
API model id	claude-opus-5	gpt-5.5
Released	July 24, 2026	April 23, 2026
Artificial Analysis Intelligence Index [max] (2026-08-14)	63	Not verifiedUnverified
Artificial Analysis Intelligence Index [xhigh] (2026-08-14)	Not verifiedUnverified	58
Humanity's Last Exam (2026-09-01)	Winner: 63.6	52.2
Terminal-Bench 2.1 (2026-09-03)	Winner: 86.7	83.4
SWE-bench Verified (2026-09-01)	Not verifiedUnverified	82.6
GPQA Diamond (2026-07-27)	Not verifiedUnverified	93.5

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

2026-09-03: Meta Muse Spark 1.3 launch table (independent cross-vendor run; conflicts with Google's 89.1 — both preserved)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
2026-09-02: Google Gemini 3.8 Flash launch eval table (independent cross-vendor run)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
2026-09-01: vals.ai SWE-bench Verified leaderboard (independent, mini-swe-agent bash-only); official SWE-bench not publishedReal GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
2026-09-01: Anthropic Fable 5.1 comparison table (vendor, with tools; 56.6 no tools)Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise. Comparability: comparable with caveat — Subset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.
2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
2026-07-27: Kimi K3 model card (vendor-reported, xhigh); announcement charts show 93.6 — minor conflict preservedAgentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
2026-04-23: OpenAI — Introducing GPT-5.5 (vendor, with tools; 41.4 no tools)Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise. Comparability: comparable with caveat — Subset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.

Pricing tiers: Claude Opus 5: Standard $5/$25 per MTok; cache reads 10% of base input. Knowledge cutoff May 2026. · GPT-5.5: Standard $5/$30 per MTok; >272K input billed 2x in / 1.5x out. Cached input $0.50/MTok; batch $2.50/$15.

FrontierRecord checked September 3, 2026

Claude Opus 5

Claude Opus 5 is Anthropic's top model for complex agentic coding and enterprise work — superseded at the top of the Artificial Analysis Index by Fable 5.1 (2026-09-01) but stronger on price.

Best for

Complex agentic coding
Enterprise work
Long-context analysis

Watch out

Output costs 5x input; long generations dominate the bill.

FrontierRecord checked September 3, 2026

GPT-5.5

GPT-5.5 is OpenAI's previous flagship — strong on Terminal-Bench 2.0 (82.7%) and 1M-token context.

Best for

Reasoning
Agentic coding
Long-context work

Watch out

Superseded by GPT-5.6 Sol on quality; still a capable, widely integrated model.

When the cheaper one wins

Claude Opus 5 is cheaper on output at $25 per million tokens against $30 for GPT-5.5 — about 1.2×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

Run the model picker

Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

Pricing verified on both sides — Input and output rates are verified for both models.
4/5 core specs verified on both sides — Not published for at least one side: parameter count.
4 shared named benchmarks with differing scores — Measured on: Artificial Analysis Intelligence Index, Humanity's Last Exam, Terminal-Bench 2.1, Terminal-Bench 2.1.
Verified within the last 90 days — Newest catalog check was 8 days ago.
Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Claude Opus 5: Anthropic — Claude Opus 5 (accessed 2026-08-29)
Claude Opus 5: Anthropic news — Claude Opus 5 (accessed 2026-08-29)
GPT-5.5: OpenAI — Introducing GPT-5.5 (accessed 2026-08-29)
GPT-5.5: OpenAI API pricing (gpt-5.5 $5/$30) (accessed 2026-08-29)

Related comparisons

Diving deeper on one model? Claude Opus 5 · GPT-5.5

Common questions

Claude Opus 5 vs GPT-5.5

Answered from the verified figures on this page rather than general guidance.

Is Claude Opus 5 or GPT-5.5 cheaper for input?

Both cost $5 per million input tokens at standard rates, so input price is not a deciding factor between them.

Is Claude Opus 5 or GPT-5.5 cheaper for output?

Claude Opus 5 is cheaper at $25 per million output tokens, against $30 for GPT-5.5 — roughly 1.2× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Claude Opus 5 has tiered pricing: Standard $5/$25 per MTok; cache reads 10% of base input. Knowledge cutoff May 2026. GPT-5.5 has tiered pricing: Standard $5/$30 per MTok; >272K input billed 2x in / 1.5x out. Cached input $0.50/MTok; batch $2.50/$15.

Which has the larger context window, Claude Opus 5 or GPT-5.5?

GPT-5.5 accepts 1.05M tokens against 1M for Claude Opus 5. This only matters if you routinely send very long documents or large codebases.

Do Claude Opus 5 and GPT-5.5 support the same reasoning levels?

Claude Opus 5 exposes adaptive, while GPT-5.5 exposes none, low, medium, high, xhigh, max.

Should I use Claude Opus 5 or GPT-5.5?

Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. Claude Opus 5 suits complex agentic coding; GPT-5.5 suits reasoning.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

Context: GPT-5.5 takes 1.05M against 1M for Claude Opus 5 — only decisive if your prompts approach the smaller window.
Measured capability: Claude Opus 5 leads Artificial Analysis Intelligence Index 63 to 58 (measured 2026-08-14).

Run the model picker Estimate stack cost All model comparisons

Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.