Model comparison

Claude Opus 5 vs GPT-6 Astra

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

Recorded profile verification October 1, 2026Individual provider fields may changeEvidence confidence: Medium — see receipts below

Anthropic

Claude Opus 5

Frontier

OpenAI

GPT-6 Astra

Frontier

AI model capability comparison
Specification	Claude Opus 5	GPT-6 Astra
Provider
Provider	Anthropic	OpenAI
Tier
Tier	Frontier	Frontier
Context window
Context window	1M	Winner: 1.05M
Max output
Max output	128K	128K
Input / 1M tokens
Input / 1M tokens	Winner: $5	$10
Output / 1M tokens
Output / 1M tokens	Winner: $25	$50
Weights
Weights	Closed	Closed
Parameters
Parameters	Not verifiedUnverified	Not verifiedUnverified
Reasoning levels
Reasoning levels	low, medium, high, xhigh, max	low, medium, high, xhigh, max
Modalities
Modalities	text, image	text, image
API model id
API model id	claude-opus-5	gpt-6-astra
Released
Released	July 24, 2026	September 3, 2026
Humanity's Last Exam · source date Claude Opus 5: 2026-09-01, GPT-6 Astra: 2026-09-03 (comparability not verified)
Humanity's Last Exam · source date Claude Opus 5: 2026-09-01, GPT-6 Astra: 2026-09-03 (comparability not verified)	63.6	57.2
Terminal-Bench 2.1 · source date Claude Opus 5: 2026-09-02
Terminal-Bench 2.1 · source date Claude Opus 5: 2026-09-02	89.1	Not verifiedUnverified
Artificial Analysis Intelligence Index [max] · source date GPT-6 Astra: 2026-10-01
Artificial Analysis Intelligence Index [max] · source date GPT-6 Astra: 2026-10-01	Not verifiedUnverified	53
DeepSWE 1.1 · source date GPT-6 Astra: 2026-09-03
DeepSWE 1.1 · source date GPT-6 Astra: 2026-09-03	Not verifiedUnverified	74.1
OSWorld 2.0 (offline) · source date GPT-6 Astra: 2026-09-03
OSWorld 2.0 (offline) · source date GPT-6 Astra: 2026-09-03	Not verifiedUnverified	72.6
GPQA Diamond · source date GPT-6 Astra: 2026-09-03
GPQA Diamond · source date GPT-6 Astra: 2026-09-03	Not verifiedUnverified	96

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. 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.

Source date2026-10-01
Artificial Analysis (GPT-6 Astra (max))
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 the cited source and its date.
Source date2026-09-03
OpenAI GPT-6 Astra evaluation table (vendor-reported, with tools; maximum across evaluated efforts)
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.
Source date2026-09-03
OpenAI GPT-6 Astra evaluation table (vendor-reported; maximum across evaluated efforts)
Graduate-level science reasoning: multiple-choice questions written by domain PhDs.
Comparable with caveatDo not treat a fixed two-point band as universal measurement uncertainty; it depends on run count and evaluation setup. Chain-of-thought, prompt, and tool policy must match. The small pool limits fine-grained conclusions, and frontier scores can be near ceiling; Artificial Analysis dropped it from its Intelligence Index in v4.3.
Source date2026-09-03
OpenAI (vendor-reported) (v2026.08.08 offline set, partial reward; vendor research/API evaluation, maximum across evaluated efforts)
Computer-use: completing real OS tasks (files, apps, settings) in a sandboxed desktop.
Comparable with caveatOffline vs live interaction modes are NOT comparable; step budgets and screen resolution must match.
Source date2026-09-03
OpenAI (xhigh, mini-swe-agent; matches Datacurve's independent board (74.1% at $4.43/task, rank 1; board updated 2026-09-22))
Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.
Directly comparable
Source date2026-09-02
Google Gemini 3.8 Flash evaluation table quoting public leaderboard / Artificial Analysis, Terminus 2; not a Google-run Opus evaluation (Cross-provider quotation; common effort and experiment date unverified)
Agentic terminal work: multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNot comparable with Terminal-Bench 3.0 or 4.0 (different task sets) or v1; harness configuration (container, time limits) also shifts results.
Source date2026-09-01
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.
Comparable with caveatSubset/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 with no long-context surcharge. Cache reads $0.50; 5-minute writes $6.25 and 1-hour writes $10. Batch $2.50/$12.50. First-party Fast research preview $10/$50, unavailable with Batch. US-only inference adds 10% where supported. Batch 300K output requires output-300k-2026-03-24; standard stays 128K. Knowledge cutoff May 2026; retirement not sooner than July 24, 2027.

GPT-6 Astra: Standard $10/$50 per MTok (≤272K input); above 272K the full request bills $20/$75. Cached input $1/$2 and cache writes $12.50/$25 for short/long context. Batch/Flex are half Standard; Fast is 2x. Ultrafast is 6x: $60/$300 short, $120/$450 long, through Responses with global/US processing; no EU or other regional inference residency. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff Apr 30 2026. Enterprise model access is disabled by default.

FrontierRecord checked October 1, 2026

Claude Opus 5

Claude Opus 5 is Anthropic's July 2026 agentic-coding model, now 'Active (legacy)'. Its successor Opus 5.5 has lower base input/output prices ($4/$20 vs $5/$25 per million tokens); performance depends on the workload and evaluation settings.

Best for

Complex agentic coding
Enterprise work
Long-context analysis

Watch out

Active legacy, superseded by Opus 5.5. Test migration: Opus 5.5 makes adaptive thinking always on, rejects forced tool use and the older computer-use tool, and changes thinking-block/progress behavior. Partner cloud lifecycles and prices can differ.

FrontierRecord checked October 1, 2026

GPT-6 Astra

OpenAI describes GPT-6 Astra as its most capable model for complex reasoning, coding and computer use, and the first it gates at the Preparedness Framework's 'Critical' cybersecurity threshold.

Best for

Computer-use agents
Agentic coding
Hard reasoning

Watch out

OpenAI places Astra at its Critical cybersecurity threshold and disables it by default for Enterprise. Tool calling requires Responses; none reasoning and custom temperature/top_p/logprobs are unsupported. Long prompts above 272K increase the full-request rate. GPT-6.1 Sol has lower base token prices; compare results on your own workload.

Benchmark

DeepSWE 1.1 in context

Only GPT-6 Astra has a published DeepSWE 1.1 result. It is shown against the wider field, with cost per completed task alongside the score.

Local leader

GPT-6 Astra [xhigh]

74.1%

Rows shown

Best source-matched Pass@1 per model

Snapshot date

2026-10-01

Mirrored from deepswe.datacurve.ai

Better is toward the top-right (higher pass rate, lower cost). X-axis is reversed to match DeepSWE’s public chart. v1.1 uses average cost, output tokens and steps. Legacy v1 transcriptions are excluded here until an exact primary receipt is retained.

DeepSWE 1.1 leaderboard with pass rate, cost, tokens, and steps per task
#	Model	Pass@1	Cost / task	Tokens / task	Steps / task
1	GPT-6 Astra [xhigh]	74.1%	$4.43	30k	29
2	Gemini 3.8 Flash [high]	73.8%	$2.36	143k	166
3	Claude Opus 5 [max]	73.6%	$11.84	118k	99
4	GPT-5.6 Sol [max]	72.7%	$8.39	60k	61
5	Claude Fable 5 [xhigh]	69.9%	$13.41	80k	68
6	GPT-5.6 Terra [max]	69.6%	$4.95	72k	76
7	GLM 5.3 [max]	69.0%	$3.99	80k	124
8	Kimi K3 [max]	68.5%	$4.65	82k	98
9	Grok 4.6 [medium]	67.5%	$3.45	50k	70
10	GPT-5.6 Luna [max]	67.2%	$3.03	73k	102
11	GPT-5.5 [xhigh]	67.0%	$7.23	46k	82
12	Gemini 3.7 Flash [medium]	65.5%	$2.03	94k	117
13	GLM 5.3 Flash [max]	63.4%	$0.48	73k	123
14	DeepSeek V4-Pro [max]	62.8%	$0.24	106k	155
15	Claude Opus 4.8 [max]	59.0%	$13.22	135k	120
16	Qwen3.8-Max [xhigh]	57.5%	$3.73	95k	111
17	Muse Spark 1.2 [xhigh]	54.9%	$3.70	99k	101
18	Claude Sonnet 5 [max]	53.8%	$26.40	214k	268
19	Grok 4.5 [high]	53.8%	$2.42	36k	61
20	DeepSeek V4-Flash [max]	53.3%	$0.10	108k	153
21	Muse Spark 1.1 [xhigh]	53.3%	$2.36	74k	96
22	GPT-5.4 [xhigh]	51.8%	$5.65	71k	70
23	Gemini 3.6 Flash [high]	46.7%	$4.42	96k	117
24	GLM 5.2 [max]	43.8%	$3.92	78k	129
25	Gemini 3.5 Flash [high]	36.1%	$3.45	76k	105
26	Kimi K2.7 Code	30.5%	$2.82	59k	149
27	Claude Sonnet 4.6 [high]	29.9%	$5.52	76k	134
28	Gemini 3.1 Pro [high]	11.7%	$2.14	28k	76

“Best per model” shows each model’s highest source-matched Pass@1 in this capture; switch to all effort levels to see every retained configuration. Efforts differ across models, so this view is not a comparison at matched effort. The source was generated September 22 and captured October 1. Small gaps may not be statistically meaningful — confirm on deepswe.datacurve.ai.

When the cheaper one wins

Claude Opus 5 is cheaper on output at $25 per million tokens against $50 for GPT-6 Astra — about 2.0×. 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. On DeepSWE 1.1, Claude Opus 5 is 73.6% Pass@1 at $11.84/task versus GPT-6 Astra at 74.1% / $4.43/task. This compares standard short-context token rates, not total cost per accepted task. Include input, cache, context tiers, schedules, retries and review in your pilot.

Run the model picker

Evidence confidence: Medium

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.
No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
Verified within the last 90 days — Older of the two catalog checks was 25 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: Claude model overview — whole-profile source check October 1 (accessed 2026-10-01)
Claude Opus 5: Claude current API pricing, caching and inference geography (accessed 2026-10-01)
Claude Opus 5: Anthropic — Claude Opus 5 (accessed 2026-08-29)
Claude Opus 5: Anthropic news — Claude Opus 5 (accessed 2026-08-29)
Claude Opus 5: Anthropic — Claude Opus 5.5 (Opus 5 successor) (accessed 2026-09-26)
Claude Opus 5: Anthropic selectable effort levels (separate from adaptive thinking mode) (accessed 2026-10-01)
GPT-6 Astra: OpenAI model card — whole-profile source check October 1 (accessed 2026-10-01)
GPT-6 Astra: OpenAI current API pricing and processing tiers (accessed 2026-10-01)
GPT-6 Astra: OpenAI API changelog — September 3 release; checked October 1 (accessed 2026-10-01)
GPT-6 Astra: OpenAI — Introducing GPT-6 Astra (accessed 2026-09-03)
GPT-6 Astra: OpenAI API pricing (gpt-6-astra $10/$50) (accessed 2026-09-03)
GPT-6 Astra: CNBC — OpenAI launches GPT-6 Astra (accessed 2026-09-03)
GPT-6 Astra: OpenAI model docs — gpt-6-astra (128K max output, effort levels) (accessed 2026-09-05)
GPT-6 Astra: OpenAI API pricing (gpt-6-astra ≤272K $10/$50, >272K $20/$75) (accessed 2026-09-26)

Related comparisons

Diving deeper on one model? Claude Opus 5 · GPT-6 Astra

Common questions

Claude Opus 5 vs GPT-6 Astra

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

Is Claude Opus 5 or GPT-6 Astra cheaper for input?

Claude Opus 5 is cheaper at $5 per million input tokens, against $10 for GPT-6 Astra — roughly 2.0× the price. Estimate both input and output token volume for your workload. These are base rates; Claude Opus 5: Standard $5/$25 per MTok with no long-context surcharge. Cache reads $0.50; 5-minute writes $6.25 and 1-hour writes $10. Batch $2.50/$12.50. First-party Fast research preview $10/$50, unavailable with Batch. US-only inference adds 10% where supported. Batch 300K output requires output-300k-2026-03-24; standard stays 128K. Knowledge cutoff May 2026; retirement not sooner than July 24, 2027. GPT-6 Astra: Standard $10/$50 per MTok (≤272K input); above 272K the full request bills $20/$75. Cached input $1/$2 and cache writes $12.50/$25 for short/long context. Batch/Flex are half Standard; Fast is 2x. Ultrafast is 6x: $60/$300 short, $120/$450 long, through Responses with global/US processing; no EU or other regional inference residency. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff Apr 30 2026. Enterprise model access is disabled by default.

Is Claude Opus 5 or GPT-6 Astra cheaper for output?

Claude Opus 5 is cheaper at $25 per million output tokens, against $50 for GPT-6 Astra — roughly 2.0× the price. Estimate both input and output token volume for your workload. These are base rates; Claude Opus 5: Standard $5/$25 per MTok with no long-context surcharge. Cache reads $0.50; 5-minute writes $6.25 and 1-hour writes $10. Batch $2.50/$12.50. First-party Fast research preview $10/$50, unavailable with Batch. US-only inference adds 10% where supported. Batch 300K output requires output-300k-2026-03-24; standard stays 128K. Knowledge cutoff May 2026; retirement not sooner than July 24, 2027. GPT-6 Astra: Standard $10/$50 per MTok (≤272K input); above 272K the full request bills $20/$75. Cached input $1/$2 and cache writes $12.50/$25 for short/long context. Batch/Flex are half Standard; Fast is 2x. Ultrafast is 6x: $60/$300 short, $120/$450 long, through Responses with global/US processing; no EU or other regional inference residency. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff Apr 30 2026. Enterprise model access is disabled by default.

Which has the larger context window, Claude Opus 5 or GPT-6 Astra?

GPT-6 Astra 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-6 Astra support the same reasoning levels?

Both expose these named effort settings: "low", "medium", "high", "xhigh", "max". The same labels do not guarantee equal compute budgets or behavior across providers. Compare quality, latency and cost on your own tasks.

Should I use Claude Opus 5 or GPT-6 Astra?

Both are classified in our frontier tier; this editorial grouping does not imply equal capability. Claude Opus 5 is a candidate for complex agentic coding; GPT-6 Astra is a candidate for computer-use agents. Compare accuracy, tool reliability, latency and cost on representative tasks.

Next step

Choosing between them

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

Input price: Claude Opus 5 costs $5 per 1M tokens versus $10 for GPT-6 Astra — a 2x difference at the headline tier.
Context: GPT-6 Astra takes 1.05M against 1M for Claude Opus 5 — only decisive if your prompts approach the smaller window.

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