Model comparison

Claude Mythos 5.1 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 Mythos 5.1

Frontier

OpenAI

GPT-6 Astra

Frontier

AI model capability comparison
Specification	Claude Mythos 5.1	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	$10	$10
Output / 1M tokens
Output / 1M tokens	$50	$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-mythos-5-1	gpt-6-astra
Released
Released	September 1, 2026	September 3, 2026
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
Humanity's Last Exam · source date GPT-6 Astra: 2026-09-03
Humanity's Last Exam · source date GPT-6 Astra: 2026-09-03	Not verifiedUnverified	57.2

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

Pricing tiers

Claude Mythos 5.1: Standard $10/$50 per MTok, sharing Fable 5.1's specifications/pricing. Cache reads $0.25; 5-minute writes $12.50 and 1-hour writes $20. Batch $5/$25. US-only inference adds 10% where supported. Invite-only for vetted US organisations; API ID claude-mythos-5-1. Retirement not sooner than September 1, 2027; this is a minimum commitment, not an announced shutdown.

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 Mythos 5.1

Anthropic describes Claude Mythos 5.1 as its most capable model for cybersecurity and biology research — the Fable 5.1 model with fewer cyber/bio safeguards, restricted to vetted US organisations.

Best for

Cyber-defence research
Biology research
Claude Security workloads

Watch out

Invite-only for vetted US organisations through trusted access programmes, with 30-day retention required by default for safety monitoring. Adaptive thinking cannot be disabled and forced tool use errors. Shared underlying model does not make Fable benchmark results Mythos observations; safeguards and access 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

Both charge $50 per million output tokens at standard rates, so output price is not the split. Prefer the row whose “best for” line matches the job, then confirm the live vendor rate.

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 Mythos 5.1: Claude model overview — whole-profile source check October 1 (accessed 2026-10-01)
Claude Mythos 5.1: Claude current API pricing, caching and inference geography (accessed 2026-10-01)
Claude Mythos 5.1: Anthropic — Claude Mythos (accessed 2026-09-03)
Claude Mythos 5.1: Anthropic — model deprecations (claude-mythos-5) (accessed 2026-09-03)
Claude Mythos 5.1: Anthropic — Mythos 5.1 overview (1M context, 128K output, claude-mythos-5-1) (accessed 2026-09-26)
Claude Mythos 5.1: 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 Mythos 5.1 · GPT-6 Astra

Common questions

Claude Mythos 5.1 vs GPT-6 Astra

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

Is Claude Mythos 5.1 or GPT-6 Astra cheaper for input?

Both list a base rate of $10 per million input tokens. Actual cost can differ with context tiers, caching, tools and other charges. Claude Mythos 5.1: Standard $10/$50 per MTok, sharing Fable 5.1's specifications/pricing. Cache reads $0.25; 5-minute writes $12.50 and 1-hour writes $20. Batch $5/$25. US-only inference adds 10% where supported. Invite-only for vetted US organisations; API ID claude-mythos-5-1. Retirement not sooner than September 1, 2027; this is a minimum commitment, not an announced shutdown. 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 Mythos 5.1 or GPT-6 Astra cheaper for output?

Both list a base rate of $50 per million output tokens. Actual cost can differ with context tiers, caching, tools and other charges. Claude Mythos 5.1: Standard $10/$50 per MTok, sharing Fable 5.1's specifications/pricing. Cache reads $0.25; 5-minute writes $12.50 and 1-hour writes $20. Batch $5/$25. US-only inference adds 10% where supported. Invite-only for vetted US organisations; API ID claude-mythos-5-1. Retirement not sooner than September 1, 2027; this is a minimum commitment, not an announced shutdown. 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 Mythos 5.1 or GPT-6 Astra?

GPT-6 Astra accepts 1.05M tokens against 1M for Claude Mythos 5.1. This only matters if you routinely send very long documents or large codebases.

Do Claude Mythos 5.1 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 Mythos 5.1 or GPT-6 Astra?

Both are classified in our frontier tier; this editorial grouping does not imply equal capability. Claude Mythos 5.1 is a candidate for cyber-defence research; 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.

Context: GPT-6 Astra takes 1.05M against 1M for Claude Mythos 5.1 — only decisive if your prompts approach the smaller window.

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