GPT-6 Astra wins on coding (99 vs 98). For most workflows, GPT-6 Astra is the stronger default — openai's frontier answer to fable 5.1 — computer-use and agentic-coding leader at $10/$50.
The safest GPT-6 Astra vs Claude Fable 5 default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-6 Astra is the strongest answer here for GPT-6 Astra vs Claude Fable 5 — pick it when quality of output matters more than the $10.00/1M/1M input you pay for it.
Claude Sonnet 5.5 handles the same job for about 80% less per token. Start here and only move up if the output is not good enough.
Claude Fable 5 is the fastest of these for GPT-6 Astra vs Claude Fable 5 — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-6 Astra leads on coding with a score of 99 vs 98 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.
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.
Switch the scoring lens to see whether the GPT-6 Astra vs Claude Fable 5 answer changes when cost, speed, or long-document depth leads the decision.
OpenAI / Premium / Sep 4, 2026
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.
Where the GPT-6 Astra vs Claude Fable 5 recommendation shifts once you weigh price or latency differently.
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GPT-6 AstraOpenAI | $10.00/1M | $50.00/1M | $200 | 1.1M tokens | Deliberate | 100 | 97 | 100 |
| Claude Fable 5Anthropic | $10.00/1M | $50.00/1M | $200 | 1M tokens | Deliberate | 100 | 98 | 100 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for GPT-6 Astra vs Claude Fable 5, what it is genuinely good at, and where we would steer you away from it.
The default answer for GPT-6 Astra vs Claude Fable 5 — 100/100 on the coding axis, and the model we would start with unless the price below rules it out.
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.
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.
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.
Full pricing, benchmark table and release notes on the GPT-6 Astra page.
The fastest model in this shortlist for GPT-6 Astra vs Claude Fable 5. Pick it when turnaround is what your readers or users notice.
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.
You are latency- or cost-sensitive, or your tasks don't need frontier-level reasoning — Opus 4.8 at half the price is plenty.
The strongest coding and reasoning model you can actually use today. 80.3% SWE-Bench Pro is an 11-point leap over Opus 4.8 — the biggest single-release jump of 2026. It costs 2× Opus 4.8, so use it for the hardest agentic and engineering work and keep Opus 4.8 or Sonnet for everyday volume.
Full pricing, benchmark table and release notes on the Claude Fable 5 page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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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.
Both models are similarly priced at $10/1M input tokens. The decision should come down to capability, not cost.
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.
GPT-6 Astra is better for coding with a score of 99 vs Claude Fable 5's 98 (out of 100). Claude Opus 5.5 is the overall coding leader in this directory at 100/100.
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.
$10/$50 per 1M — two and a half times GPT-5.6 Sol's $4/$20 promotional rate, five times GPT-6.1 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-6.1 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.
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 gap shows up most on coding (99 vs 98).
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.
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.