anthropic
Anthropic: Claude Fable 5.2
anthropic/claude-fable-5.2
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
Anthropic's Claude Fable 5.2 (canonical ID anthropic/claude-fable-5.2-20261109) is described in the OpenRouter catalog as the vendor's most capable model for demanding technical work, with reported gains over Fable 5.1 in coding, reasoning, and vision. It accepts text, image, and file inputs and returns text, with a one-million-token context window. Reasoning is mandatory with selectable effort levels. Catalog-listed arena measurements cover design and coding categories, but only catalog data was supplied; no independent model card was available in this source pack.[1]
Strengths
- Vendor-reported strength in coding, reasoning, and vision over the prior Fable 5.1 generation; the catalog also lists measured arena results across design, agent, and coding-related categories.[1]
- Broad input surface: text, image, and file inputs with text output, plus a very large context window.[1]
- Mandatory reasoning with five selectable effort levels, and API support for tools, tool choice, structured outputs, and verbosity control.[1]
Limitations
- All evidence comes from the OpenRouter catalog; no independent model card was available in this source pack, so vendor-reported capability claims and catalog benchmark listings should be validated on real workloads before adoption.[1]
- Reasoning cannot be disabled (only its effort can be tuned), and the knowledge cutoff is not reported; some catalog benchmark fields are also empty.[1]
Where to use it
- Demanding technical work such as coding assistance and reasoning-heavy analysis, per the vendor description relayed by the catalog — worth piloting before committing.[1]
- Multimodal document workflows: the catalog lists image and file inputs alongside text, and arena measurements include PDF-oriented agent tasks.[1]
- Tool-using agents and structured-output pipelines, given supported parameters for tools, tool choice, and response formatting.[1]
Sources
- [1] OpenRouter catalog · Anthropic: Claude Fable 5.2Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Claude Fable 5.2 is Anthropic's most capable model for the most demanding technical work, with gains over Fable 5.1 in coding, reasoning, and vision. In prerelease testing it completed otherwise-infeasible...
Specifications
- Model ID
- anthropic/claude-fable-5.2
- Canonical ID
- anthropic/claude-fable-5.2-20261109
- Creator
- anthropic
- Added to OpenRouter
- 09.11.2026
- Context length
- 1,000,000
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $8 / out $40
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | SS — top 10% of the cohort | reasoning: mandatory · default high · efforts: max, xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default high · efforts: max, xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Intelligence index | 64.6 | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 65.5% · rank 2 | 1,323Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · pdfwin rate 68.2% · rank 3 | 1,306Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 76.8% · rank 1 | 1,516Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 62.7% · rank 3 | 1,374Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 65.2% · rank 5 | 1,399Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 61.1% · rank 5 | 1,361Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 60.6% · rank 3 | 1,353Elo | SS — top 10% of the cohort | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| 1,000,000 | $8 | $40 | — | — | 100% | |
| Amazon Bedrock | 1,000,000 | $8 | $40 | — | — | — |
| Azure | 1,000,000 | $8 | $40 | — | — | 33.33% |
| Anthropic | 1,000,000 | $8 | $40 | — | — | 73.33% |
| Anthropic | 1,000,000 | $16 | $80 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
- Google DeepMind and Artificial Analysis Introduce MKA, a Benchmark for Visually Grounded Agent WorkMKA is a 200-task benchmark that measures whether AI agents can extract decisive evidence from blueprints, scans, and charts and turn it into professional deliverables.
- Gemini 4 Carbon opens to general availability at launch pricingSimon Willison reports that Google's Gemini 4 Carbon, previously limited to a subset of cyber defenders, is now available to everyone, with launch prices set to double on December 1st.