90 days of the enterprise, pro and team plans free, no card needed. See the plans
Model comparison
Anthropic's Claude Fable 5.1 against OpenAI's GPT-6 Astra: vendor list prices, limits, abilities and the Artificial Analysis indexes side by side - and what OpenSmartRoute does when both are available.
Both list at $20 per million tokens blended (3 input : 1 output).
Intelligence index 53 against 53: within a point of each other.
Claude Fable 5.1 scores 82 on the coding index against 77 - 5 points apart.
Claude Fable 5.1 scores 58 on the agentic index against 51 - 7 points apart.
GPT-6 Astra reads 1.1M tokens at once, Claude Fable 5.1 1M.
Vendor list prices per million tokens and published limits; indexes are Artificial Analysis composites (0-100).
| Specification | Claude Fable 5.1 | GPT-6 Astra |
|---|---|---|
| Input price / 1M tokens | $10.0 | $10.0 |
| Output price / 1M tokens | $50.0 | $50.0 |
| Blended (3 in : 1 out) | $20.0 | $20.0 |
| Cached input / 1M | $0.25 | $1.00 |
| Context window | 1M | 1.1M |
| Max output | 128K | 128K |
| Input | text, image, file | file, image, text |
| Output | text | text |
| Tool calls | ||
| Structured output | ||
| Reasoning | ||
| Open weights | ||
| Intelligence index | 53 | 53 |
| Coding index | 82 | 77 |
| Agentic index | 58 | 51 |
| Released | Sep 1, 2026 | Sep 4, 2026 |
| Available on this deployment |
List price times tokens for three typical workloads; your mix of input and output decides which model's pricing suits you.
| Workload | Claude Fable 5.1 | GPT-6 Astra | Difference |
|---|---|---|---|
| Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations. | $450 | $450 | same |
| Document summaries100M in, 5M out - long inputs, short answers. | $1,250 | $1,250 | same |
| Coding assistant60M in, 20M out - a team's editor assistant, output-heavy. | $1,600 | $1,600 | same |
The two measure the same on the intelligence index, so the router treats them as peers and lets price, observed latency and your outcomes decide: Claude Fable 5.1 wins on cost, and a few bad outcomes on either move the next requests to the other.
# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry)
targets:
- { id: claude-fable-5.1, kind: llm, metadata: { model: anthropic/claude-fable-5.1 } }
- { id: gpt-6-astra, kind: llm, metadata: { model: openai/gpt-6-astra } }
# rules.yaml - the cheaper model by default, the stronger one when the request is hard
rules:
- name: simple-requests-stay-cheap
when: { max_complexity: 0.45 }
prefer: [claude-fable-5.1]
weight: 0.8
- name: hard-requests-escalate
when: { min_complexity: 0.45 }
prefer: [gpt-6-astra]
weight: 0.8Every Anthropic and OpenAI model, with prices, is on the vendor pages; the rankings show what the router actually picks.