Both are their lab’s most capable model, and both are slow and expensive. Fable 5.1 is the stronger pick for long agent work and hard open-ended reasoning; Astra leads on maths, science and operating software. For most teams the honest answer is neither — Opus 5.5 or GPT-6.1 Sol do most of the same work for much less.
| Claude Fable 5.1 | GPT-6 Astra | |
|---|---|---|
| Made by | Anthropic | OpenAI |
| Released | September 2026 | September 2026 |
| Input price, per 1M tokens | S$13.39 | S$13.39 |
| Output price, per 1M tokens | S$66.95 | S$66.95 |
| Cached input, per 1M tokens | S$0.3348 | S$1.34 |
| Batch (about half price) | Yes | Yes |
| Context window | 1M tokens | 1.05M tokens |
| Longest answer | 128K tokens | 128K tokens |
| Reads | Text, Images, PDFs | Text, Images |
| Thinks before answering | Always on | Always on |
| Open weights | No | No |
Prices are Roar AI’s published rates, live from our price list. Specs are each lab’s own published figures. Prices are our published US dollar rates converted at S$1.30 to the dollar, our rate for October — the same rate your card is charged.
Take 1,000 requests, each about 3,000 tokens in and 1,000 out — a long prompt and a page of answer.
The two cost about the same for this job. Models that think before answering spend extra output tokens doing it, so on hard prompts the real gap can be wider than the rates suggest.
On Roar AI both are on the same key and the same monthly invoice, paid in your local currency. Trying the other one is a one-word change:
client.chat.completions.create(model="claude-fable-5-1", …) client.chat.completions.create(model="gpt-6-astra", …)
Send the same prompts to both for a day and compare the answers on your own work — that settles it faster than any benchmark. Read the docs.
Send the same prompts to each and compare the answers on your own work.