# Claude Fable 5.2 vs Muse Spark Open

> Claude Fable 5.2 scores 77.3 (BB) to Muse Spark Open's 53.4 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-muse-spark-open
- Markdown: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-muse-spark-open.md (~7,450 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-09

Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments & pricing. Both do llm inference.

- Claude Fable 5.2: grade BB, 77.3/100, rank #35 of 1517. Markdown https://www.anchorterminal.com/tools/claude-fable-5-2.md · JSON https://www.anchorterminal.com/api/v1/tools/claude-fable-5-2.json
- Muse Spark Open: grade D, 53.4/100, rank #954 of 1517. Markdown https://www.anchorterminal.com/tools/muse-spark-open.md · JSON https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json
- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md
- All 956 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### Claude Fable 5.2 (BB)

Good for: Agents doing long, hard work (large coding changes, multi-step research, computer use) that can pay frontier prices, accept 30-day retention and don't need to force a tool call.

Ahead on:
- Reliability, 60 against 42
- Schema & documentation, 90 against 61
- Agent ergonomics, 95 against 69
- Security & auth, 92 against 44
- Maintenance & community, 91 against 60
- Transparency & trust, 85 against 53

Also in its favour:
- Agent-ready, a grade of BB or better
- A hosted endpoint, with nothing to install

Watch for: Adaptive thinking is always on and can't be turned off

### Muse Spark Open (D)

Good for: A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.

Ahead on:
- Payments & pricing, 50 against 30

Also in its favour:
- No key needed to call it

Watch for: The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight


## Why the edge

### Security & auth: Claude Fable 5.2 +48

- Claude Fable 5.2 (92): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Workspace-scoped keys with expiry and Workload Identity Federation, no scopes below the workspace (25 of 30). No training on API data without express permission (20). The model requires 30-day retention, is a Covered Model and is outside ZDR unless Anthropic expressly authorises it, per the model page read 9 November, the same as Fable 5.1 (12 of 15). Usage and cost analytics, Compliance API and OpenTelemetry export (15). security.txt, HackerOne and SOC 2, ISO 27001 and ISO 42001 (20). Thinking blocks work only in the account that produced them or one linked to it, per the model page. 25 + 20 + 12 + 15 + 20 = 92.
- Muse Spark Open (44): Read as software the owner runs. No account or key to run it. Meta's weights need manual approval on Hugging Face and an access token, and server authentication is the owner's to add (12 of 30). An agent model that calls whatever tools the operator gives it. The card recommends human-in-the-loop confirmation for irreversible actions and Meta reports agentic-risk evaluations, but nothing in the model or template enforces an approval (8 of 20). The chat template neutralises special-token sequences and media placeholders in caller text and wraps tool results in `<tool_output>`, and the card advises protecting internal assistant messages and layering defences against adversarial input. No indirect prompt-injection results are published (10 of 15). No call log of its own. Visibility depends on the serving stack (5 of 15). Weights are safetensors that load through Transformers' own classes from 5.19, and Meta published cyber, chemical, biological and misalignment evaluations. dev.meta.ai/.well-known/security.txt answers 404 (re-read on 4 November), research.meta.ai per the 15 October check, and no security route is on the card or in the docs, only museoss@meta.com and the Hugging Face discussions (9 of 20). 12 + 8 + 10 + 5 + 9 = 44.

### Transparency & trust: Claude Fable 5.2 +32

- Claude Fable 5.2 (85): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Commercial Terms with named contracting parties and Apache 2.0 SDKs (15). Retention stated two ways across the docs and the privacy centre, though for this model the model page is plain that 30 days is required (20 of 30, kept at the platform's reading). Deprecation page with dates, and this model's retirement floor on its page (20). Processing countries and subprocessors named (20). The benchmark figures are Anthropic's own, with no third-party run of this model found on 9 November. 15 + 20 + 20 + 20 = 75.
- Muse Spark Open (53): Weights are downloadable under the Muse Model Licence, which is clear and broad in its grant but not an OSI licence. It adds a display requirement, a separate agreement before Model as a Service by a licensee group above $20M gross revenue, and a Usage Policy with field-of-use limits (military, nuclear, espionage, critical infrastructure, heavy machinery) and an age limit of 18. It has no regional exclusion and no governing-law clause. Training code and data aren't released (18 of 30). Inputs stay on the owner's hardware, and Meta's docs say self-hosting keeps 'every prompt and response' inside the owner's infrastructure. The access form's details, and a download from Meta's own page after signing in, go to Meta under its general privacy policy, which we didn't read, and the training data is described in outline only (20 of 30). No deprecation policy, dated notices or versioning found (0 of 20). The Get the model page says everything runs offline once the weights land, and safetensors weights carry no code. No other telemetry statement, and Meta's download form records name, date of birth, country and IP location (12 of 20). 18 + 20 + 0 + 12 = 50.

### Maintenance & community: Claude Fable 5.2 +31

- Claude Fable 5.2 (91): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released 9 November 2026 beside dated release notes several times a week (30). 60 days' minimum notice for retirements, and the model page says retirement not sooner than 9 November 2027 (8 of 12, the Claude API's reading). Model shutdowns kept to notice (8). Support centre and dated notes (15). The sampled SDK issue without a reply, per the 1 October check (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 8 + 8 + 15 + 5 + 15 + 10 = 91.
- Muse Spark Open (60): Read for an open-weight model released three weeks ago. Released on 15 October 2026 (30). One release, BF16 and NVFP4 on the same day, with no history of revisions, successors or notice periods, and Meta Model API has no deprecation policy either (6 of 20). None of the 29 replies counted by script on 4 November across the BF16 repository's discussions came from Meta. Feedback goes to the discussions or museoss@meta.com, and Meta's docs and developer blog carry dated posts (8 of 25). Day-one support in vLLM, SGLang, TensorRT-LLM, Transformers, llama.cpp, MLX and Unsloth with Meta's own recipes, though SGLang's is a dev image and TensorRT-LLM's a feature branch (12 of 15). Current dependencies (Transformers 5.19), but no CI visible to us (4 of 10). 30 + 6 + 8 + 12 + 4 = 60.

### Schema & documentation: Claude Fable 5.2 +29

- Claude Fable 5.2 (90): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. The SDK-bundled OpenAPI file as half a contract (15 of 25, the Claude API listing's judgement call). llms.txt with Markdown twins (10). The model page, what's new and the migration guide say what changed from Fable 5.1 and what to send and not send (forced tool choice, sampling parameters, `computer_20251124` returning 400 except on Bedrock), read 9 November (20). Structured outputs and strict tools GA (15). Documented error types with `request_id` (15). `anthropic-version` and dated release notes (15). 15 + 10 + 20 + 15 + 15 + 15 = 90.
- Muse Spark Open (61): Read for a model the owner serves. No specification of its own. The contract is the Jinja chat template, which renders OpenAI-format tools with `additionalProperties: false` added and rejects bad values, plus the OpenAI-compatible servers in vLLM and SGLang with the `muse` parsers (10 of 25). dev.meta.ai/llms.txt lists the Muse Spark Open overview and seven pages under it, plus three cookbook pages, each with a Markdown copy (10). The card lists seven intended uses and six limitations, the docs say when to pick BF16 or NVFP4 and which reasoning strength suits which task, and the Usage Policy states what is out of scope (17 of 20). `reasoning_effort` is an enum of four values and anything else returns an error, and tools take JSON Schema. Structured output is documented only for TensorRT-LLM's `response_format`, not in the prompting guide or for vLLM and SGLang (11 of 15). curl and Python examples for every runtime and hosted provider, the rendered prompt for each case, and the template's own error messages, but no error reference for a served model (11 of 15). One release, with no changelog or version scheme beyond the licence's version line, Muse Spark Open (2 of 15). 10 + 10 + 17 + 11 + 11 + 2 = 61.

### Agent ergonomics: Claude Fable 5.2 +26

- Claude Fable 5.2 (95): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Tool use with parallel calls, 15 of 20 because `tool_choice` any or tool returns a 400 `invalid_request_error`, per the model page read 9 November. Structured outputs (15). Prompt caching with reads at $0.20, 0.025x input, per the pricing page read 9 November (15). 1M context by default and at most, 128K output (15). Batch at half price (10). Official SDKs in seven languages (10). Documented errors, `retry-after` and retries (15). 15 + 15 + 15 + 15 + 10 + 10 + 15 = 95.
- Muse Spark Open (69): Model reading of the checklist (tool use, structured output, caching, context, throughput, defaults and SDKs, errors). OpenAI-format tools and parallel calls come back as `tool_calls`, and the template supports namespaced tools and deferred loading through a `tool_search` tool. A forced `tool_choice` is not documented (17 of 20). JSON mode and JSON Schema come from each runtime's guided decoding, which Meta's docs show for TensorRT-LLM only (8 of 15). Prefix caching is the runtime's. Meta's SGLang command turns on hierarchical caching, and Dynamo routes each request to the worker holding its cached context (8 of 10). 1,048,576-token context, with sliding-window attention on 46 of 62 layers holding KV memory down (15 of 15). Draft models for speculative decoding in SGLang and vLLM, and no batch mode of its own (7 of 10). Any OpenAI SDK works against a local server, but reasoning can't be turned off, defaults to the most expensive level, and needs streaming, a `max_tokens` budget for reasoning and the right stop tokens (6 of 15). The template raises named errors for an unsupported reasoning effort, tool arguments passed as a string and a tool message with no name. Server errors are the runtime's (8 of 15). 17 + 8 + 8 + 15 + 7 + 6 + 8 = 69.

### Payments & pricing: Muse Spark Open +20

- Claude Fable 5.2 (30): Model reading for claude-fable-5-2 on the Claude API. Platform facts are the Claude API listing's (anthropic-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol on the pricing page, read 9 November (0). Per-token prices published without a login, $8 input and $40 output (20). New users get a small amount of free credit, without the page saying whether a card is needed, so half, as for the Claude API (10). Keys from the browser Console only (0). 0 + 20 + 10 + 0 = 30.
- Muse Spark Open (50): Self-hosted rule. Nothing to buy from Meta, and the licence grants use free of charge. The Model as a Service clause asks for a separate agreement only from licensee groups above $20M gross revenue in 12 months (20). Free to run with no card (20). Meta's own weights need a manually reviewed Hugging Face form with legal name and date of birth, or, since the 4 November re-read of Get the model, a signed-in download from Meta's own page, so an agent can't get them alone. The ungated GGUF quantisations from ggml-org and Unsloth that Meta's docs point to download without approval (the Unsloth repository is ungated on 4 November), so part of the line (10 of 20). No payment protocol (0). Hosted copies at $1.25 input and $4.25 output per million tokens need each provider's own account and are not graded. 20 + 20 + 10 + 0 = 50.

## Score by category

| Category | Weight | Claude Fable 5.2 | Muse Spark Open | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 60 | 42 | Claude Fable 5.2 +18 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 90 | 61 | Claude Fable 5.2 +29 |
| Agent ergonomics | 13% (16.2 this run) | 95 | 69 | Claude Fable 5.2 +26 |
| Security & auth | 14% (17.5 this run) | 92 | 44 | Claude Fable 5.2 +48 |
| Payments & pricing | 10% (12.5 this run) | 30 | 50 | Muse Spark Open +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 91 | 60 | Claude Fable 5.2 +31 |
| Transparency & trust | 7% (8.8 this run) | 85 | 53 | Claude Fable 5.2 +32 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **77.3 · BB** | **53.4 · D** | |

## Facts side by side

| Fact | Claude Fable 5.2 | Muse Spark Open |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Anthropic | Meta |
| Hosted endpoint | `https://api.anthropic.com/v1` | no (local only) |
| Transports |  | HTTP |
| Auth | API key | None |
| Pricing | Pay per use | Free |
| x402 | no | no |
| Licence | Closed model, used through the Claude API and cloud platforms under Anthropic's Commercial Terms of Service | Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-09 | 2026-10-15 |
| Terms last updated | no date given | 2026-10-15 |
| Privacy policy last updated | no date given | no document linked |
| Customer content may train models | yes, with an opt-out | not found in the text |
| Terms restrict automated access | not found in the text | not found in the text |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | yes | not found in the text |

## How the scores have moved

### Claude Fable 5.2

No score change since it was listed.

### Muse Spark Open

- -0.1 on 30 October 2026: checklist
- no change on 28 October 2026: new evidence
- +0.1 on 27 October 2026: checklist

## Verdicts

**Claude Fable 5.2.** Anthropic's strongest generally available model, 20% cheaper than Fable 5.1 at $8 and $40 per million tokens, with large vendor-reported gains in coding and agent work and the Claude API's mature tooling. Thinking can't be turned off, tools can't be forced, and it requires 30-day retention.

**Muse Spark Open.** Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.

## Before you call either

### Claude Fable 5.2

1. Call https://api.anthropic.com/v1/messages with model claude-fable-5-2 and your key
2. Steer thinking with the effort parameter (default high); don't send temperature, top_p or top_k
3. Don't force a tool with tool_choice any or tool; describe the tool and let the model choose
4. Thinking blocks from it are read only by Fable 5.2 and Mythos 5.2, so keep them out of other models' context
5. Check data retention before sending regulated data, since 30 days is required
6. Expect a refusal-and-fallback path on high-risk cyber or biology requests; read Anthropic's refusals and fallback page

### Muse Spark Open

1. Start vLLM or SGLang with `--reasoning-parser muse --tool-call-parser muse` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as raw text
2. Set `reasoning_effort` to `low` or `medium` for short tasks. The default is `xhigh`, reasoning can't be turned off, and other values return an error
3. Stop only on `<|eot|>` and end of text. Stopping on `<|eom|>` cuts off tool calls and final answers
4. Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`
5. Don't call Meta Model API for this model. Use a self-hosted server or a hosted provider's model string, such as `meta-models/muse-spark-open`

## Questions

### Which is better for AI agents, Claude Fable 5.2 or Muse Spark Open?

Claude Fable 5.2 scores 77.3 (BB) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 6 of 7 scored categories. Muse Spark Open leads on payments & pricing.

### Do Claude Fable 5.2 and Muse Spark Open need an API key?

Claude Fable 5.2 needs an API key. Muse Spark Open needs no key.

### Can an agent call Claude Fable 5.2 and Muse Spark Open without installing anything?

Claude Fable 5.2 has a hosted endpoint at https://api.anthropic.com/v1. No hosted endpoint is listed for Muse Spark Open.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-muse-spark-open.json, and with the fewest tokens: https://www.anchorterminal.com/compare/claude-fable-5-2-vs-muse-spark-open.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "claude-fable-5-2", "b": "muse-spark-open"}`. From a terminal: `anchor compare claude-fable-5-2 muse-spark-open`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/claude-fable-5-2.json and https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json

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- [Eden AI vs Muse Spark Open](https://www.anchorterminal.com/compare/eden-ai-vs-muse-spark-open.md)
- [Glimpse vs Muse Spark Open](https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-spark-open.md)
- [Fireworks AI Inference vs Muse Spark Open](https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open.md)
- [Gemini Developer API vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.md)
- [GroqCloud vs Muse Spark Open](https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.md)
- [Hugging Face Inference Providers vs Muse Spark Open](https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-spark-open.md)
- [Inkling 2 Small vs Muse Spark Open](https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-spark-open.md)
- [Jais 3 vs Muse Spark Open](https://www.anchorterminal.com/compare/jais-3-vs-muse-spark-open.md)
- [Meta Model API vs Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)
- [MiniMax API vs Muse Spark Open](https://www.anchorterminal.com/compare/minimax-api-vs-muse-spark-open.md)
- [Mistral AI API vs Muse Spark Open](https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.md)
- [Muse Ember vs Muse Spark Open](https://www.anchorterminal.com/compare/muse-ember-vs-muse-spark-open.md)
- [Muse Spark Open vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/muse-spark-open-vs-nemotron-3-5-super-vl.md)
- [Muse Spark Open vs Novita AI](https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai.md)
- [Muse Spark Open vs OpenAI API](https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.md)
- [Muse Spark Open vs OpenRouter](https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter.md)
- [Muse Spark Open vs Prism Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference.md)
- [Muse Spark Open vs Router.com (Ramp Router)](https://www.anchorterminal.com/compare/muse-spark-open-vs-ramp-router.md)
- [Muse Spark Open vs Beam 1.0](https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam.md)
- [Muse Spark Open vs RouterPlus](https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus.md)
- [Muse Spark Open vs SambaCloud](https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.md)
- [Muse Spark Open vs SiliconFlow](https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.md)
- [Muse Spark Open vs Simplismart](https://www.anchorterminal.com/compare/muse-spark-open-vs-simplismart.md)
- [Muse Spark Open vs StepFun API](https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.md)
- [Muse Spark Open vs SWE-2 Flash](https://www.anchorterminal.com/compare/muse-spark-open-vs-swe-2-flash.md)
- [Muse Spark Open vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/muse-spark-open-vs-tencent-tokenhub.md)
- [Muse Spark Open vs Together AI Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.md)
- [Muse Spark Open vs Vercel AI Gateway](https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway.md)
- [Muse Spark Open vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/muse-spark-open-vs-vertex-ai.md)
- [Muse Spark Open vs xAI API (Grok)](https://www.anchorterminal.com/compare/muse-spark-open-vs-xai-api.md)

## Disclosure

- Anthropic makes the models this research run and the review panel run on. This listing was graded by an agent running on Claude, by the same published checklist as every other listing, from Anthropic's own pages and the Claude API listing's platform readings, with every judgement call written in the note. The panel reviews Anthropic's listings at our founder's request, and every review carries a conflict label, because every reviewer and the arbiter run on Claude.

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