Claude Fable 5.1 and GPT-6 Astra arrived two days apart. Both target hard coding, research and agentic work, both carry roughly one-million-token context windows, and both list at $10 per million input tokens and $50 per million output tokens. Meaning the pricing is the same... at least on paper!
That makes this less of a spec-sheet fight and more of a workflow fight. Fable 5.1 currently leads the independent Intelligence Index, while Astra leads several coding, computer-use and automation benchmarks. Head-to-head builds remain mixed. In this article, we clear the doubt by testing where each model wins.
TL;DR: Both are equally good and the choice depends on whether you’d prefer a high cost/quality output or a moderate quality/cost output.
Fable 5.1 vs Astra: Quick Comparison
| Category | Claude Fable 5.1 | GPT-6 Astra |
|---|---|---|
| Release | Sep 1, 2026 | Sep 3, 2026 |
| Context | 1M tokens | 1.05M tokens |
| Max output | 128K | 128K |
| Knowledge cutoff | Jun 2026 | Apr 30, 2026 |
| Reasoning | Adaptive, always on | Low / medium / high / xhigh / max |
| Input / output | $10 / $50 per 1M | $10 / $50 per 1M |
| Cache read | $0.25 / 1M | $1 / 1M |
| Best fit | Deep reasoning, long agents | Computer use, end-to-end execution |
Benchmarks: Neither Model Owns the Whole Board
OpenAI’s launch table has Astra ahead on most of the rows it published. Artificial Analysis reverses the headline result, giving Fable 5.1 the highest Intelligence Index score it has measured so far.
| Benchmark | Fable 5.1 | Astra | Winner |
|---|---|---|---|
| AA Intelligence Index (max) | 66 | 61 | Fable |
| Humanity’s Last Exam + tools | 65.0% | 57.2% | Fable |
| Terminal-Bench 4.0 | 55.8% | 57.9% | Astra |
| DeepSWE v1.1 | 67.4% | 74.1% | Astra |
| AutomationBench | 31.4% | 41.4% | Astra |
| Terminal-Bench Science 0.1 | 52.6% | 64.6% | Astra |
The caveat matters: OpenAI chose the harnesses and effort settings for its launch table, while Artificial Analysis runs a separate methodology. These scores are useful signals, not a universal ranking.
AutomationBench compares Astra directly with Fable 5.1 across accuracy and estimated API cost.
Hands-On: Same Task, Fable 5.1 vs Astra
For a real comparison, the prompt has to go to both models. The four rounds below are based on Chase AI’s direct three-day test, where the same projects were run through GPT-6 Astra and Claude Fable 5.1. I have shortened each task into the kind of prompt you can actually rerun without a wall of instructions.
1. Making each other’s Web application
For ChatGPT:
| Create a Claude web application clone for me. make sure to nail the aesthetic of the app. |
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For Claude:
| Create a ChatGPT web application clone for me. make sure to nail the aesthetic of the app. |
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Both GPT-6 Astra and Fable 5.1 did an amazing job of replicating each other’s interface. Both the model took ~5 minutes to get this done and aesthetically (which was the ask) the interface looks almost identical to the real one.
Winner: Both GPT-6 Astra and Fable 5.1
2. HTML Animation
| Create an animation of Gojo hitting a Black Flash on Sukuna, based on how it went in the manga. |
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GPT-6 Astra:
Claude Fable 5.1:
Astra produced the much more aesthetic and true to the canon content animation. This is how the actual events had gone in the manga.
Fable 5.1 on the other hand did a pretty horrible job of animating the sequence. The narration is whimsical (nothing like that actually happened) the characters looked cartoony and nothing except the kanji for Black Flash was correct in the sequence.
Winner: GPT-6 Astra.
3. Motion Graphics
| Create a 15-second animated explainer showing what happens when I send a text message over the internet. |
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GPT-6 Astra:
Claude Fable 5.1:
Both models did an amazing job of illustrating the text delivery process over the internet. Where ChatGPT Astra adopted a slide-deck illustrative approach, Fable 5.1 did this entire process in a single canvas. It’s a lot easier to follow and understand Fable’s output than ChatGPT one, and it also looks aesthetically better.
Winner: Claude Fable 5.1.
4. 3D Globe App
| Build an interactive 3D globe travel dashboard that plots routes between cities and feels premium. |
|---|
GPT-6 Astra:
Claude Fable 5.1:
Astra’s result was clean and looked like the first iteration of a website. Fable pushed harder on spectacle, with richer motion and visuals while maintaining functionality. Also the level of detail on offer by Fable 5.1 was much more (time for trip, more locations) than Astra.
Winner: Fable 5.1.
Verdict
| Round | Winner |
|---|---|
| Web App | Both |
| HTML Animation | GPT-6 Astra |
| Motion graphics | Fable 5.1 |
| 3D globe app | Fable 5.1 |
Further tests on Astra and Fable 5.1
One creator test is not enough. A separate four-build comparison from AI for Mortals hid the model identities during review. The result is more or less the same:
| Build | Winner | Why |
|---|---|---|
| 3D kart racer | Fable 5.1 | Better polish, environment and game feel |
| Theo Jansen walker | Astra | Cleaner controls and stronger 3D presentation |
| 3D dive-watch page | Fable 5.1 | Smoother choreography and richer detail |
| Site recreation | Astra | Closest reproduction and strongest tool-using workflow |
This is the more believable pattern: Astra is very strong when the task requires a staged workflow and lots of tool use. Fable can still win when the final artifact depends heavily on taste, motion and visual polish.
Pricing: Same Price, Very Different Economics
| Rate | Claude Fable 5.1 | GPT-6 Astra |
|---|---|---|
| Input | $10 / 1M | $10 / 1M |
| Output | $50 / 1M | $50 / 1M |
| 5-min cache write | $12.50 / 1M | $12.50 / 1M |
| Cache read | $0.25 / 1M | $1 / 1M |
| >272K surcharge | None listed | 2x input/cache, 1.5x output |
Fable wins the rate card on repeated context. Astra often wins the completed-task bill because it uses fewer tokens. Artificial Analysis currently shows Fable 5.1 as the higher-intelligence model, while Astra offers lower cost-per-task at several effort settings. The creator tests above show the same tension in the wild.
For running the 4 tests shown in this article, I used xHigh (Extra High) setting for Claude Fable 5.1 and Extra High setting for GPT-6 Astra. The token used and cost are as follows:
Fable 5.1 Token Usage
GPT-6 Astra Token Usage
Fable 5.1 took almost twice the tokens to achieve the same result. Also, due the time taken for the task completion was more than Astra.
Therefore, in terms of token economics and cost: GPT-6 Astra is the clear winner.
Which One Should You Use?
Choose Claude Fable 5.1 if:
- You care most about deep reasoning, research or long autonomous code work.
- Your workflow repeatedly reuses a huge context window and cache cost matters.
- You prefer a model that can satisfy a spec with fewer intervention steps.
- Visual taste and creative interpretation matter more than fast execution.
Choose GPT-6 Astra if:
- The task spans code, browser work, software and finished artifacts.
- You care about computer use, automation and tool-heavy workflows.
- You want strong first-pass UI polish from low-direction prompts.
- Cost per completed task matters more than the raw cache-read rate.
Final Take
Astra does not simply replace Fable 5.1, and Fable does not keep an automatic coding crown. The current evidence is messier and more useful than that.
Fable 5.1 leads the independent intelligence score and still wins some of the hardest visual builds. Astra wins more of OpenAI’s published benchmarks, is stronger at computer-centered work and repeatedly shows better task efficiency. For most teams, the right answer is routing: Fable for depth, Astra for execution.
Frequently Asked Questions
Is GPT-6 Astra better than Claude Fable 5.1?
Not across every workload. Astra leads more published action-heavy benchmarks; Fable leads the independent Intelligence Index and wins some direct visual builds.
Which is better for coding?
Astra leads several vendor coding benchmarks. Fable remains extremely competitive in long-horizon coding and can lead when evaluated inside Claude Code.
Which one is cheaper?
Fable has cheaper cache reads. Astra often uses fewer tokens per completed task, so the cheaper model depends on the workflow.
Which one should I test first?
Start Fable on long reasoning or codebase work. Start Astra when the task needs browsers, tools, software or a polished artifact.