Compare
Claude Fable 5 Default vs GPT-5.1-Codex-Max
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
Claude Fable 5 Default
Context window
1M
1,000,000 tokens · ~750K words
Model
GPT-5.1-Codex-Max
Context window
400K
400,000 tokens · ~300K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Claude Fable 5 Default has about 2.5× the context window of the other in this pair.
Claude Fable 5 Default has 150% more context capacity (1000K vs 400K tokens). GPT-5.1-Codex-Max is 87% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Claude Fable 5 Default. Its 1000K context fits entire documents without chunking (vs 400K).
RAG / high-volume retrieval
Use GPT-5.1-Codex-Max. Input tokens are 87% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Claude Fable 5 Default | GPT-5.1-Codex-Max |
|---|---|---|
| Context window | 1,000,000 tokens (1000K) | 400,000 tokens (400K) |
| Max output tokens | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Speed tier | Balanced | Balanced |
| Vision | Yes | Yes |
| Function calling | Yes | Yes |
| Extended thinking | Yes | Yes |
| Prompt caching | Yes | Yes |
| Batch API | Yes | No |
| Release date | N/A | Dec 2025 |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | Claude Fable 5 Default in | Claude Fable 5 Default out | GPT-5.1-Codex-Max in | GPT-5.1-Codex-Max out |
|---|---|---|---|---|
| Google Vertex | $10.00/M | $50.00/M | — | — |
| Openrouter | — | — | $1.25/M | $10.00/M |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model