Claude Fable 5 is the better pick when response speed matters more than maximum reasoning depth.
AnthropicPremium
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
Price
$10.00/1M
Context
1M tokens
Why this page recommends it
GPT-6 Astra leads on coding with a score of 100 vs 100 for Claude Fable 5.
GPT-6 Astra has the larger context window: 1.05M vs 1M for Claude Fable 5.
Both models are similarly priced — the decision comes down to capability, not cost.
Decision notes
Choose GPT-6 Astra for computer and browser use, long-horizon agentic coding, and frontier math and science work. Its coding and research scores are what carry the recommendation here.
Choose Claude Fable 5 when your work is mostly the hardest coding tasks and autonomous multi-step agents — that is the workload it was tuned for.
Both models serve different primary workflows — GPT-6 Astra for computer and browser use and long-horizon agentic coding, Claude Fable 5 for the hardest coding tasks and autonomous multi-step agents — so running each where it has a clear edge often beats forcing one to do both.
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#1GPT-6 Astra91 pts
#2Claude Fable 591 pts
Quality first
GPT-6 Astra
OpenAI / Premium / Sep 4, 2026
91
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You are cost-sensitive or latency-bound — GPT-5.6 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak.
Recommended comparisons
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Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.
The case for each model
What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.
OpenAI's September 3, 2026 frontier release — the first GPT-6 model and OpenAI's answer to Claude Fable 5.1 two days earlier. State of the art on computer use (OSWorld 2.0 72.6% in ~47% less time than GPT-5.6 Sol), agentic coding (Terminal-Bench 4.0 57.9%), and frontier math (FrontierMath Tier 4 97.6%). $10/$50 per 1M tokens, 1.05M context, 128K output, knowledge cutoff April 30, 2026.
Input
$10.00/1M
Output
$50.00/1M
Context
1.1M tokens
Speed
Deliberate
What people actually use it for
Computer-use agents that fill forms, update CRMs, run QA in a browser — 72.6% on OSWorld 2.0 at ~40 minutes per task vs Sol's 75
Agentic coding in Codex with cross-context notes — 57.9% Terminal-Bench 4.0, ahead of Claude Fable 5.1 (55.8%)
Frontier math and science — 97.6% FrontierMath Tier 4 and 64.6% Terminal-Bench Science, both well clear of every rival OpenAI tested
Where it wins
OSWorld 2.0 72.6% vs 65.7% for GPT-5.6 Sol, in roughly 47% less time per task — the new computer-use ceiling
Terminal-Bench 4.0 57.9% — ahead of Claude Fable 5.1 (55.8%), Opus 5 (52.3%) and GPT-5.6 Sol (37.3%)
FrontierMath Tier 4 (v2) 97.6% vs Fable 5.1's 87.8%; Terminal-Bench Science 64.6% vs 52.6%; GPQA Diamond 96.0%
1.05M context with 96.3% on OpenAI MRCR 8-needle at 512K–1M (Sol: 73.8%) and 128K max output
OpenAI's lowest misaligned-outcome rates to date: 2.4% on its computer-use safety benchmark vs 22.0% for Sol, 0% scope-creep on impossible cyber tasks vs 48%
Where it falls down
$10/$50 per 1M — five times GPT-5.6 Sol's $2/$10 and the same premium as Claude Fable 5.1; Fast mode doubles it again
Trails Claude Fable 5.1 on Humanity's Last Exam with tools (57.2% vs 65.0%) and on the Artificial Analysis Intelligence Index (61.2 vs 65.7)
OpenAI published no SWE-bench Verified or SWE-bench Pro figure at launch, so it does not appear on our SWE-bench leaderboard
Rolling out over days, not instantly: Enterprise access is off by default, advanced cyber tasks are refused outside OpenAI Daybreak, and the safety layer can pause or stop legitimate agent runs
OpenAI's own system card finds its written reasoning harder to monitor than Sol's
Skip it if
You are cost-sensitive or latency-bound — GPT-5.6 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak.
Our verdict
The new computer-use and agentic-coding ceiling, and OpenAI's first model priced like a Mythos-class Claude. Astra beats Claude Fable 5.1 on Terminal-Bench 4.0 (57.9% vs 55.8%), Terminal-Bench Science (64.6% vs 52.6%) and FrontierMath Tier 4 (97.6% vs 87.8%), and it is the only model with a credible OSWorld 2.0 result above 70%. It loses to Fable 5.1 on Humanity's Last Exam and on Artificial Analysis's index, costs five times GPT-5.6 Sol, and ships without a SWE-bench number. If your work is computer use, browser agents or math, it is the pick; for everyday coding at scale, Sol at $2/$10 remains the value default.
Released September 3, 2026. API ID gpt-6-astra; rolling out over the coming days to ChatGPT Plus, Pro, Business and Enterprise (usage inside existing allowances; GPT-6 Astra Pro for Pro/Business/Enterprise; Enterprise off by default), the OpenAI API, Microsoft Azure and Amazon Bedrock. Standard API pricing $10/$50 per 1M tokens; Fast mode is up to 2x speed at 2x price; cache reads and writes have separate rates. Model docs list 1,050,000 context, 128,000 max output, knowledge cutoff April 30, 2026, reasoning efforts up to 'max'. Published launch numbers (Astra / GPT-5.6 Sol / Fable 5.1 / Opus 5): OSWorld 2.0 72.6 / 65.7 / — / 70.2; Terminal-Bench 4.0 57.9 / 37.3 / 55.8 / 52.3; Terminal-Bench Science 0.1 64.6 / 22.4 / 52.6 / 30.0; FrontierMath Tier 4 v2 97.6 / 83.0 / 87.8 / 73.2; GPQA Diamond 96.0 / 94.6 / 93.7 / 93.7; Humanity's Last Exam w/ tools 57.2 / — / 65.0 / 63.6; AutomationBench 41.4 / 18.1 / 31.4 / 26.9; DeepSWE v1.1 74.1 / 72.7 / 67.4 / 73.7; ARC-AGI-2 95.0 / 92.5 / 90.0 / 90.4; ARC-AGI-3 99.9 (OpenAI responses-API harness; ARC Prize's stateless runs score far lower) / 7.8 / — / 30.2; ExploitBench 100.0 / 78.5 / — / 70; SRE-Bench 88.0 / 55.9; Artificial Analysis Intelligence Index v4.1.1 61.2 / 60.9 / 65.7 / 63.1. Meets the Critical threshold for cybersecurity under OpenAI's Preparedness Framework; advanced cyber workflows gated behind OpenAI Daybreak. All figures from OpenAI's launch post and model docs, verified September 4, 2026.
Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.
Input
$10.00/1M
Output
$50.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Autonomous agents that plan, write, run, and debug across an entire codebase with minimal supervision
Whole-repo refactors and PR review where accuracy outranks latency or cost
80.3% SWE-Bench Pro — the new #1, up from Opus 4.8's 69.2% and GPT-5.5's 58.6%
1932 on GDPval-AA, ahead of Opus 4.8 (1890) and GPT-5.5 (1769)
1M-token context at standard pricing, 128K max output per request
Mythos-class capability released for general use with new cyber-risk safeguards
Where it falls down
Priced at $10/$50 per 1M tokens — double Opus 4.8 ($5/$25)
Deliberate pace; not for latency-sensitive interactive apps
Standard-use safeguards block some high-risk security workloads (use Mythos 5 with partner access)
Skip it if
You are starting new work — Claude Fable 5.1 supersedes it at the same base price with 75% cheaper cache reads. Also skip it if you are latency- or cost-sensitive.
Our verdict
Superseded by Claude Fable 5.1 on September 1, 2026, which beats it on every benchmark Anthropic published and costs less to run thanks to a 75% cache-read cut. Fable 5 remains a frontier-class model — 80.3% SWE-Bench Pro, an 11-point leap over Opus 4.8 — and stays available at the same $10/$50, but there is no reason to start new work on it.
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses. Superseded by Claude Fable 5.1 on September 1, 2026 — same $10/$50 base pricing, cache reads cut from $1.00 to $0.25 per 1M tokens.
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FAQ
Is GPT-6 Astra better than Claude Fable 5?
GPT-6 Astra wins on more of the categories we score — coding, research, long context — so it is the better default of the two. Claude Fable 5 is the better pick when your work is mostly the hardest coding tasks and autonomous multi-step agents. Neither is universally "better": GPT-6 Astra is aimed at computer and browser use and long-horizon agentic coding, Claude Fable 5 at the hardest coding tasks and autonomous multi-step agents.
Which is cheaper — GPT-6 Astra or Claude Fable 5?
Both models are similarly priced at $10/1M input tokens. The decision should come down to capability, not cost.
Which has a larger context window — GPT-6 Astra or Claude Fable 5?
GPT-6 Astra has the larger context window at 1.05M tokens vs Claude Fable 5's 1M. For large document analysis, GPT-6 Astra is the stronger pick.
Is GPT-6 Astra or Claude Fable 5 better for coding?
GPT-6 Astra and Claude Fable 5 are similarly matched on coding. GPT-6 Astra is the overall coding leader in this directory at 100/100.
Which is faster — GPT-6 Astra or Claude Fable 5?
Both GPT-6 Astra and Claude Fable 5 have similar speed profiles — rated deliberate. Neither will be the bottleneck if latency is your deciding factor.
What are the downsides of GPT-6 Astra?
$10/$50 per 1M — five times GPT-5.6 Sol's $2/$10 and the same premium as Claude Fable 5.1; Fast mode doubles it again. Trails Claude Fable 5.1 on Humanity's Last Exam with tools (57.2% vs 65.0%) and on the Artificial Analysis Intelligence Index (61.2 vs 65.7). OpenAI published no SWE-bench Verified or SWE-bench Pro figure at launch, so it does not appear on our SWE-bench leaderboard. Avoid it if you are cost-sensitive or latency-bound — GPT-5.6 Sol is a fifth of the price — or you need it today in an Enterprise workspace, where it is off by default, or for offensive-security work, which it refuses outside OpenAI Daybreak. That is the main case for looking at Claude Fable 5 instead.
What are the downsides of Claude Fable 5?
Priced at $10/$50 per 1M tokens — double Opus 4.8 ($5/$25). Deliberate pace; not for latency-sensitive interactive apps. Standard-use safeguards block some high-risk security workloads (use Mythos 5 with partner access). Avoid it if you are starting new work — Claude Fable 5.1 supersedes it at the same base price with 75% cheaper cache reads. Also skip it if you are latency- or cost-sensitive. Against GPT-6 Astra specifically, the two are close enough on capability that price and speed decide it.
What does a month of real work cost on GPT-6 Astra vs Claude Fable 5?
Take a moderate workload of 10M input and 2M output tokens a month. GPT-6 Astra runs $200.00 (at $10/1M in and $50/1M out); Claude Fable 5 runs $200.00 (at $10/1M in and $50/1M out). The gap is small enough that price should not decide this one. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Can I use GPT-6 Astra and Claude Fable 5 together?
Yes, and for most teams that beats picking one. A common split is GPT-6 Astra for computer and browser use and long-horizon agentic coding, with Claude Fable 5 handling the hardest coding tasks and autonomous multi-step agents. Since GPT-6 Astra is both the stronger and the cheaper option here, a split mainly makes sense if Claude Fable 5 covers a capability you specifically need.