Claude Fable 5.1 is the better pick when response speed matters more than maximum reasoning depth.
AnthropicPremium
Best for
Frontier agentic coding, long-horizon autonomous work, and agentic scientific research
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 5.1.
GPT-6 Astra has the larger context window: 1.05M vs 1M for Claude Fable 5.1.
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.
Claude Fable 5.1 earns its place when your work is mostly frontier agentic coding and long-horizon autonomous work, even though it loses the overall count here.
Both models serve different primary workflows — GPT-6 Astra for computer and browser use and long-horizon agentic coding, Claude Fable 5.1 for frontier agentic coding and long-horizon autonomous work — 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 5.191 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.
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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 September 1, 2026 frontier release and the new capability ceiling for coding, agents, and scientific work. Base pricing is unchanged at $10/$50, but cache reads dropped 75% to $0.25/1M — roughly 25% cheaper on typical workloads and up to 45% cheaper on agentic ones. 1M context, 128K output, adaptive thinking always on.
Input
$10.00/1M
Output
$50.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Agentic scientific research — 52.6% on Terminal-Bench-Science 0.1, more than double Fable 5's 24.7%
Long-running autonomous coding agents that plan, run, and debug across a whole repository
Cache-heavy agent loops where the 75% cache-read cut ($1.00 → $0.25 per 1M) is the real saving
Where it wins
52.6% Terminal-Bench-Science 0.1 — 2.1x Fable 5 (24.7%), well clear of Opus 5 (29.0%) and GPT-5.6 Sol (22.4%)
55.8% Terminal-Bench 4.0 agentic coding, ahead of Opus 5 (52.3%) and Fable 5 (42.0%)
Cache reads cut 75% to $0.25/1M — ~25% cheaper for typical use, ~45% for heavily agentic work
Independent Vals AI evaluation ranks it #1 of 51 on the Vals Index, #1 on LiveCodeBench (90.5%) and MMLU Pro (92.4%)
1M-token context and 128K max output at standard rates, with adaptive thinking always enabled
Where it falls down
Base rates are still $10/$50 per 1M — double Claude Opus 5 for anything that is not cache-heavy
Anthropic published no SWE-bench Verified or SWE-bench Pro figure for 5.1 at launch
On Claude Pro it only runs on pay-as-you-go credits; Max includes it up to 50% of weekly limits
Deliberate, high-latency profile — the wrong choice for interactive, latency-bound apps
Skip it if
You need low latency, or your workload is uncached and cost-sensitive — Claude Opus 5 is half the base price and within a few points on agentic coding.
Our verdict
The new frontier leader, and the rare upgrade that costs less than the model it replaces. Base $10/$50 pricing did not move, but a 75% cut to cache reads makes typical workloads ~25% cheaper than Fable 5 and heavily agentic ones ~45% cheaper — while more than doubling Fable 5 on agentic science and beating Opus 5 on agentic coding. If you were already on Fable 5, switching is a straight win. If you were on Opus 5 for the price, it still costs 2x on uncached tokens.
Released September 1, 2026 alongside Claude Mythos 5.1, the first update to the Mythos-class line since Fable 5 on June 9. API ID claude-fable-5-1; generally available on the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry. Published launch numbers (Fable 5.1 / Fable 5 / Opus 5 / GPT-5.6 Sol): Terminal-Bench-Science 0.1 52.6 / 24.7 / 29.0 / 22.4; Terminal-Bench 4.0 55.8 / 42.0 / 52.3 / 37.3; CursorBench 3.2.0 73.4 / 70.5 / 70.0 / 67.2; AutomationBench 31.4 / 17.1 / 26.9 / 19.6; OSWorld 2.0 strict 41.7 / 36.1 / 39.6; Humanity's Last Exam (no tools) 60.9 / 57.8 / 56.6; GDPval-AA v2 1853 / 1723 / 1824 / 1711. GDPval-AA v2 is rescaled from the v1 numbers quoted on the Fable 5 page and is not directly comparable to them.
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FAQ
Is GPT-6 Astra better than Claude Fable 5.1?
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 5.1 is the better pick when your work is mostly frontier agentic coding and long-horizon autonomous work. Neither is universally "better": GPT-6 Astra is aimed at computer and browser use and long-horizon agentic coding, Claude Fable 5.1 at frontier agentic coding and long-horizon autonomous work.
Which is cheaper — GPT-6 Astra or Claude Fable 5.1?
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 5.1?
GPT-6 Astra has the larger context window at 1.05M tokens vs Claude Fable 5.1's 1M. For large document analysis, GPT-6 Astra is the stronger pick.
Is GPT-6 Astra or Claude Fable 5.1 better for coding?
GPT-6 Astra and Claude Fable 5.1 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 5.1?
Both GPT-6 Astra and Claude Fable 5.1 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 5.1 instead.
What are the downsides of Claude Fable 5.1?
Base rates are still $10/$50 per 1M — double Claude Opus 5 for anything that is not cache-heavy. Anthropic published no SWE-bench Verified or SWE-bench Pro figure for 5.1 at launch. On Claude Pro it only runs on pay-as-you-go credits; Max includes it up to 50% of weekly limits. Avoid it if you need low latency, or your workload is uncached and cost-sensitive — Claude Opus 5 is half the base price and within a few points on agentic coding. 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 5.1?
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 5.1 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 5.1 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 5.1 handling frontier agentic coding and long-horizon autonomous work. Since GPT-6 Astra is both the stronger and the cheaper option here, a split mainly makes sense if Claude Fable 5.1 covers a capability you specifically need.