# Gemini 4 Carbon vs Muse Spark Open

> Gemini 4 Carbon scores 62.6 (B) 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/gemini-4-carbon-vs-muse-spark-open
- Markdown: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.md (~7,300 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: 2026-11-10

Gemini 4 Carbon scores 62.6 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments & pricing. Both do llm inference.

- Gemini 4 Carbon: grade B, 62.6/100, rank #555 of 1518. Markdown https://www.anchorterminal.com/tools/gemini-4-carbon.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json
- Muse Spark Open: grade D, 53.4/100, rank #955 of 1518. 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 1000 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### Gemini 4 Carbon (B)

Good for: Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.

Ahead on:
- Schema & documentation, 85 against 61
- Agent ergonomics, 93 against 69
- Security & auth, 55 against 44
- Maintenance & community, 83 against 60
- Transparency & trust, 72 against 53

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: Paid tier only, with no free tier to try it on

### 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 20

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

### Payments & pricing: Muse Spark Open +30

- Gemini 4 Carbon (20): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Introductory prices published in Google's 28 October announcement without a login, $2 and $10, then $4 and $20; the Gemini API pricing page as read on 10 November showed no Carbon row, so the figures rest on the announcement (20). No free tier: Google's developer post puts Carbon on the paid tier (0). A Google account and AI Studio for a key (0). 0 + 20 + 0 + 0 = 20.
- 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.

### Schema & documentation: Gemini 4 Carbon +24

- Gemini 4 Carbon (85): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Carbon takes and refuses, the parameters that return 400 or are ignored, and how to migrate (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.
- 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: Gemini 4 Carbon +24

- Gemini 4 Carbon (93): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling, with forced calls by FunctionCallingConfig on the API (20). Structured output (13 of 15). Implicit caching with durable caching on by default, cached input 95% off, explicit caches not supported, per the Cloud guide read on 10 November (15). 1,048,576 tokens shared between input and output (15). Batch at half price on the platform (10). Python and JavaScript SDKs (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 15 + 15 + 10 + 10 + 10 = 93.
- 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.

### Maintenance & community: Gemini 4 Carbon +23

- Gemini 4 Carbon (83): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released to developers on 10 November 2026, with the platform's changelog (30). Deprecations with earliest dates and no stated minimum notice (4 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 4 + 4 + 15 + 5 + 15 + 10 = 83.
- 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.

### Transparency & trust: Gemini 4 Carbon +19

- Gemini 4 Carbon (72): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service with clear terms, SDKs Apache-2.0 (15). Paid-tier data isn't used, abuse retention has no number, and request storage is on by default for new paid projects (20 of 30). Deprecations table (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.
- 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.

### Security & auth: Gemini 4 Carbon +11

- Gemini 4 Carbon (55): Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Carbon is on the paid tier only, and Google's terms say paid-tier content isn't used to improve products; AI Studio use under a Google AI Ultra subscription falls under terms we didn't read, so 15 of 20 (a judgement call; the platform's 10 is for its free tier). Abuse retention with no number, and new paid projects store requests by default since 26 October (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 15 + 5 + 15 + 5 = 55.
- 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.

## Score by category

| Category | Weight | Gemini 4 Carbon | Muse Spark Open | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 40 | 42 | Muse Spark Open +2 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 85 | 61 | Gemini 4 Carbon +24 |
| Agent ergonomics | 13% (16.2 this run) | 93 | 69 | Gemini 4 Carbon +24 |
| Security & auth | 14% (17.5 this run) | 55 | 44 | Gemini 4 Carbon +11 |
| Payments & pricing | 10% (12.5 this run) | 20 | 50 | Muse Spark Open +30 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 83 | 60 | Gemini 4 Carbon +23 |
| Transparency & trust | 7% (8.8 this run) | 72 | 53 | Gemini 4 Carbon +19 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **62.6 · B** | **53.4 · D** | |

## Facts side by side

| Fact | Gemini 4 Carbon | Muse Spark Open |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Google | Meta |
| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | no (local only) |
| Transports |  | HTTP |
| Auth | API key | None |
| Pricing | Pay per use | Free |
| x402 | no | no |
| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | 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 | 2026-11-10 | 2026-10-15 |
| Terms last updated | 2026-04-28 | 2026-10-15 |
| Privacy policy last updated | 2026-10-01 | no document linked |
| Customer content may train models | yes | not found in the text |
| Terms restrict automated access | yes | 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 | not found in the text | not found in the text |

## How the scores have moved

### Gemini 4 Carbon

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

**Gemini 4 Carbon.** Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given.

**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

### Gemini 4 Carbon

1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-carbon and an x-goog-api-key on a billed project
2. Set thinking_level (LOW, MEDIUM or HIGH) instead of thinking_budget, and don't send temperature, top_p or top_k
3. Count output against the same 1,048,576-token limit as the input, and set max_output_tokens for long answers
4. Put static prompt content first so implicit caching applies; explicit caches aren't supported
5. Use gemini-4-argon for most coding and knowledge work, and Carbon for the hardest long tasks, as Google suggests

### 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, Gemini 4 Carbon or Muse Spark Open?

Gemini 4 Carbon scores 62.6 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments & pricing.

### Do Gemini 4 Carbon and Muse Spark Open need an API key?

Gemini 4 Carbon needs an API key. Muse Spark Open needs no key.

### Can an agent call Gemini 4 Carbon and Muse Spark Open without installing anything?

Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta. No hosted endpoint is listed for Muse Spark Open.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-carbon-vs-muse-spark-open.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemini-4-carbon", "b": "muse-spark-open"}`. From a terminal: `anchor compare gemini-4-carbon muse-spark-open`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-carbon.json and https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json

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- [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)

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