Model comparison

Claude Opus 5.5 vs GPT-6 Luna

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

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Anthropic

Claude Opus 5.5

Frontier

OpenAI

GPT-6 Luna

Budget

AI model capability comparison
Specification	Claude Opus 5.5	GPT-6 Luna
Provider
Provider	Anthropic	OpenAI
Tier
Tier	Frontier	Budget
Context window
Context window	1M	Winner: 1.05M
Max output
Max output	128K	128K
Input / 1M tokens
Input / 1M tokens	$4	Winner: $0.10
Output / 1M tokens
Output / 1M tokens	$20	Winner: $0.50
Weights
Weights	Closed	Closed
Parameters
Parameters	Not disclosedUnverified	GPT-6 low-cost tier
Reasoning levels
Reasoning levels	adaptive	none, low, medium, high, xhigh, max
Modalities
Modalities	text, image	text, image
API model id
API model id	claude-opus-5-5	gpt-6-luna
Released
Released	September 22, 2026	September 22, 2026
Artificial Analysis Intelligence Index [max] (2026-09-26)
Artificial Analysis Intelligence Index [max] (2026-09-26)	Winner: 57.6	37.3
Humanity's Last Exam [max] (2026-09-26)
Humanity's Last Exam [max] (2026-09-26)	61.4	Not verifiedUnverified
Terminal-Bench 4.0 [max] (2026-09-26)
Terminal-Bench 4.0 [max] (2026-09-26)	59.6	Not verifiedUnverified
Terminal-Bench 4.0 [xhigh] (2026-09-22)
Terminal-Bench 4.0 [xhigh] (2026-09-22)	66.4	Not verifiedUnverified
DeepSWE 1.1 [max] (2026-09-22)
DeepSWE 1.1 [max] (2026-09-22)	Not verifiedUnverified	66.6

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

Where each score comes from, and how far it can be compared across models.

2026-09-26
Artificial Analysis Terminal-Bench 4.0 (independent AA run, part of Intelligence Index v4.3.2)
Agentic terminal work: long multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNOT comparable with Terminal-Bench 2.x or 3.0 — 4.0 uses a new, non-overlapping task set. Within 4.0, scores from different harnesses (tbench.ai agent entries vs Artificial Analysis runs) are not interchangeable.
2026-09-26
Artificial Analysis Humanity's Last Exam (independent, 2,158 text-only questions)
Frontier-knowledge ceiling: extremely hard multi-domain questions written to be near-impossible without deep expertise.
Comparable with caveatSubset/tool configurations (text-only vs with-tools) differ between vendors and materially change scores; must match configuration to compare.
2026-09-26
Artificial Analysis
Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.
Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.
2026-09-22
OpenAI — Introducing GPT-6 Sol and Luna (vendor; not yet on Datacurve's board)
Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.
Directly comparable
2026-09-22
Anthropic — Claude Opus 5.5 announcement (vendor; conflicts with AA's independent 59.6 — harness difference preserved)
Agentic terminal work: long multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNOT comparable with Terminal-Bench 2.x or 3.0 — 4.0 uses a new, non-overlapping task set. Within 4.0, scores from different harnesses (tbench.ai agent entries vs Artificial Analysis runs) are not interchangeable.

Pricing tiers

Claude Opus 5.5: $4/$20 per MTok, no long-context surcharge. Cache reads $0.20; 5-minute cache writes $5, 1-hour writes $8. Batch $2/$10; Fast mode $8/$40. Batches API allows 300K output with the output-300k-2026-03-24 beta header. Knowledge cutoff Jun 2026; retirement not before 2027-09-22.

GPT-6 Luna: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.

FrontierRecord checked September 26, 2026

Claude Opus 5.5

Claude Opus 5.5 is Anthropic's default model for agentic coding and knowledge work — Anthropic says it performs near Fable 5.1 on most work at about 40% lower running cost than Opus 5, and it leads the Artificial Analysis Intelligence Index v4.3.2.

Best for

Complex agentic coding
Enterprise knowledge work
Default frontier model

Watch out

Breaking changes from Opus 5: adaptive thinking cannot be disabled (effort runs low to max, default medium) and forced tool use returns an error. Verbose at max effort, so cap output on cost-sensitive routes.

BudgetRecord checked September 26, 2026

GPT-6 Luna

GPT-6 Luna is OpenAI's cheapest current model at $0.10/$0.50 — the direct successor to GPT-5.6 Luna at half the price, with the full 1.05M-token context.

Best for

High-volume chat and extraction
Classification
Cost-capped agent loops

Watch out

Small tier: it matches GPT-5.6 Luna on the Artificial Analysis index but sits well below GPT-6 Sol on hard reasoning; the DeepSWE figure is vendor-reported at max effort.

When the cheaper one wins

GPT-6 Luna is cheaper on output at $0.50 per million tokens against $20 for Claude Opus 5.5 — about 40×. 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.

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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.
1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
Verified within the last 90 days — Newest catalog check was 2 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 5.5: Anthropic — Claude Opus 5.5 (accessed 2026-09-26)
Claude Opus 5.5: Anthropic docs — Opus 5.5 overview (1M context, 128K output) (accessed 2026-09-26)
Claude Opus 5.5: Anthropic pricing (claude-opus-5-5 $4/$20, cache reads $0.20) (accessed 2026-09-26)
Claude Opus 5.5: Artificial Analysis — Intelligence Index v4.3.2 (Opus 5.5 #1) (accessed 2026-09-26)
GPT-6 Luna: OpenAI — Introducing GPT-6 Sol and Luna (accessed 2026-09-26)
GPT-6 Luna: OpenAI model docs — gpt-6-luna (1.05M context, 128K output) (accessed 2026-09-26)
GPT-6 Luna: OpenAI API pricing (gpt-6-luna $0.10/$0.50, cached $0.01) (accessed 2026-09-26)

Related comparisons

Diving deeper on one model? Claude Opus 5.5 · GPT-6 Luna

Common questions

Claude Opus 5.5 vs GPT-6 Luna

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

Is Claude Opus 5.5 or GPT-6 Luna cheaper for input?

GPT-6 Luna is cheaper at $0.10 per million input tokens, against $4 for Claude Opus 5.5 — roughly 40× 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 5.5 has tiered pricing: $4/$20 per MTok, no long-context surcharge. Cache reads $0.20; 5-minute cache writes $5, 1-hour writes $8. Batch $2/$10; Fast mode $8/$40. Batches API allows 300K output with the output-300k-2026-03-24 beta header. Knowledge cutoff Jun 2026; retirement not before 2027-09-22. GPT-6 Luna has tiered pricing: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.

Is Claude Opus 5.5 or GPT-6 Luna cheaper for output?

GPT-6 Luna is cheaper at $0.50 per million output tokens, against $20 for Claude Opus 5.5 — roughly 40× 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 5.5 has tiered pricing: $4/$20 per MTok, no long-context surcharge. Cache reads $0.20; 5-minute cache writes $5, 1-hour writes $8. Batch $2/$10; Fast mode $8/$40. Batches API allows 300K output with the output-300k-2026-03-24 beta header. Knowledge cutoff Jun 2026; retirement not before 2027-09-22. GPT-6 Luna has tiered pricing: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.

Which has the larger context window, Claude Opus 5.5 or GPT-6 Luna?

GPT-6 Luna accepts 1.05M tokens against 1M for Claude Opus 5.5. This only matters if you routinely send very long documents or large codebases.

Do Claude Opus 5.5 and GPT-6 Luna support the same reasoning levels?

Claude Opus 5.5 exposes adaptive, while GPT-6 Luna exposes none, low, medium, high, xhigh, max.

Should I use Claude Opus 5.5 or GPT-6 Luna?

Claude Opus 5.5 is the frontier tier and GPT-6 Luna the budget tier. The useful question is whether your hardest task actually fails on the cheaper one — most production volume such as classification, extraction and summarisation does not.

Next step

Choosing between them

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

Input price: GPT-6 Luna costs $0.10 per 1M tokens versus $4 for Claude Opus 5.5 — a 40x difference at the headline tier.
Context: GPT-6 Luna takes 1.05M against 1M for Claude Opus 5.5 — only decisive if your prompts approach the smaller window.
Measured capability: Claude Opus 5.5 leads Artificial Analysis Intelligence Index 57.6 to 37.3 (measured 2026-09-26).
Positioning: Claude Opus 5.5 sits in the frontier tier, GPT-6 Luna in the budget tier — most production volume (classification, extraction, summarisation) does not need the pricier tier.

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