{ "data": { "a": { "slug": "muse-spark-open", "name": "Muse Spark Open", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai/models/muse-spark-open", "kind": "model", "category": "inference", "summary": "Muse Spark Open is Meta's open-weight multimodal model for coding and agentic work, with 816B total and 42B active parameters and a 1M-token context, released on 15 October 2026 under the Muse Model Licence for self-hosting.", "url": "https://www.anchorterminal.com/tools/muse-spark-open", "markdownUrl": "https://www.anchorterminal.com/tools/muse-spark-open.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/muse-spark-open.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json", "repo": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B", "license": "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", "transports": [ "http" ], "packages": [], "auth": "none", "authNotes": "Running the model needs no account or key. Getting Meta's weights does. Both Hugging Face repositories (BF16 and NVFP4) are gated with manual review and ask for full legal name, date of birth, country, affiliation and job title, and downloads then use a Hugging Face access token. The GGUF quantisations from ggml-org and Unsloth that Meta's docs point to are not gated. A local server has whatever authentication the owner adds, such as llama.cpp's `--api-key`.", "pricing": "free", "pricingNotes": "Free to download and run under the Muse Model Licence, with the owner's GPUs as the cost. A licensee whose group has more than $20M gross revenue in any 12 months must notify Meta and sign a separate agreement before offering it as Model as a Service. Hosted copies cost $1.25 input, $0.15 cached input and $4.25 output per million tokens on Fireworks, Baseten, Modal and OpenRouter (checked 2026-10-15). Meta Model API does not serve it.", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Muse Spark Open is a model the owner runs, with no payment route from Meta, and Meta Model API does not serve it (checked 2026-10-15).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-15" }, "docsUrl": "https://dev.meta.ai/docs/muse-spark-open", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm", "inference.open-weights", "inference.local" ], "tags": [ "model", "open-weights", "self-hosted", "local", "free", "gated", "multimodal", "openai-compatible", "llms-txt", "gpu", "new" ], "lastRelease": "2026-10-15", "graded": true, "anchor": { "graded": true, "score": 53.4, "grade": "D", "agentReady": false, "rank": 760, "ranked": true, "rankOf": 1095, "categoryRank": 16, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 69, "maintenance": 60, "payments": 50, "reliability": 42, "schema": 61, "security": 44, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-15" }, "negative": 0, "verdict": "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.", "bestFor": "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.", "strengths": [ "816B total and 42B active parameters with a 1,048,576-token context, taking text, image, video and audio input", "Day-one support in vLLM, SGLang, TensorRT-LLM, Transformers, llama.cpp, MLX and Unsloth, with commands for each in Meta's docs", "With the `muse` parsers, reasoning comes back in its own field and tool calls as a standard `tool_calls` array", "The licence grants use, fine-tuning, distillation and resale free of charge, with no user cap and no regional exclusion", "llms.txt and Markdown docs cover checkpoints, prompting, stop tokens, recommended settings and post-training" ], "weaknesses": [ "The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight", "Meta's Hugging Face repositories need manual approval with legal name and date of birth, which the Get the model page doesn't mention", "Products must display \"Built with Muse Spark Open\", and a company group with over $20M revenue needs Meta's agreement to offer it as Model as a Service", "The Usage Policy rules out military, nuclear, espionage, critical infrastructure and heavy machinery uses, and users under 18", "Released on 15 October 2026, with no changelog, deprecation policy or CI found, and the full evaluation report not yet published" ], "agentNotes": [ "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", "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", "Stop only on `\u003c|eot|\u003e` and end of text. Stopping on `\u003c|eom|\u003e` cuts off tool calls and final answers", "Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`", "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`" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 53.4 } ], "editorialScores": { "ergonomics": 69, "maintenance": 60, "payments": 50, "reliability": 42, "schema": 61, "security": 44, "transparency": 50 }, "provenanceScore": 55 }, "connect": { "install": "hf download meta-models/Muse-Spark-Open-816B-A42B-NVFP4 --local-dir ./muse-spark-open-nvfp4\n\nexport VLLM_USE_RUST_FRONTEND=1\nvllm serve meta-models/Muse-Spark-Open-816B-A42B-NVFP4 \\\n --tensor-parallel-size 4 \\\n --enable-expert-parallel \\\n --max-model-len 1048576 \\\n --reasoning-parser muse \\\n --tool-call-parser muse \\\n --enable-auto-tool-choice", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"model\": \"meta-models/Muse-Spark-Open-816B-A42B-NVFP4\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Refactor this module.\"}],\n \"reasoning_effort\": \"xhigh\"\n }'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/muse-spark-open" }, "sameCompany": [ "meta-model-api", "muse-code" ], "area": "models", "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "meta.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": null, "terms": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B/blob/main/LICENSE.md", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-15", "notes": [ "The licence names Meta Platforms, Inc. as copyright holder, and defines Meta as Meta Platforms Ireland Limited for licensees in the European region and Meta Platforms, Inc. elsewhere. The model card names the same two as model provider.", "The licence is the document that governs use of the weights, so it is recorded as the terms. LICENSE.md matches the text shown on the gated access form word for word. The Usage Policy is its Exhibit A. The separate USE_POLICY.md that Meta's docs link answered 401 without access and wasn't read.", "No privacy policy governs the model, because the owner runs it and no input reaches Meta. The access form says its details are handled under the Meta Privacy Policy on www.facebook.com, whose robots.txt asks readers like ours not to fetch it, so it wasn't read.", "The domain is meta.ai, where Meta's developer docs (dev.meta.ai) and research post (research.meta.ai) sit, the same as the meta-model-api and muse-code listings. RDAP gives a registration date of 16 December 2017.", "No hosted endpoint from Meta, so no status page. No changelog for the model was found, and the Hugging Face commit history needs access to read.", "dev.meta.ai/.well-known/security.txt and research.meta.ai/.well-known/security.txt returned 404 on 15 October 2026.", "WebFetch read the research post. It refused the Hugging Face model card as outside its allowed set, so the card, LICENSE.md, the repository and collection metadata, the discussions, the evaluation methodology PDF, Meta's docs pages and the providers' model pages were read with curl." ], "score": 55 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/muse-spark-open.json", "live": { "slug": "muse-spark-open", "pages": [ { "url": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B/blob/main/LICENSE.md", "kind": "terms", "status": 200, "checkedAt": "2026-10-15T21:58:24.678553754Z", "changedAt": "2026-10-15T21:58:24.678553754Z", "fingerprint": "7ffd7a072112" } ], "updatedAt": "2026-10-15T21:58:24.678553754Z" } }, "answer": "Muse Spark Open scores 53.4 (D) on agent readiness against SiliconFlow's 46.7 (D), and leads in 6 of 7 scored categories.", "b": { "slug": "siliconflow", "name": "SiliconFlow", "vendor": "SiliconFlow Labs Pte. Ltd.", "vendorUrl": "https://www.siliconflow.com", "kind": "model", "category": "inference", "summary": "SiliconFlow is a hosted inference API for open-weight models, covering chat, vision, embeddings, reranking, image, video and speech. It answers OpenAI-style and Anthropic-style calls at api.siliconflow.com with a Bearer key.", "url": "https://www.anchorterminal.com/tools/siliconflow", "markdownUrl": "https://www.anchorterminal.com/tools/siliconflow.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/siliconflow.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/siliconflow.json", "license": "Proprietary service under the SiliconFlow Terms of Use", "transports": [ "http" ], "remoteUrl": "https://api.siliconflow.com/v1", "packages": [], "auth": "api-key", "authNotes": "Self-serve Bearer key from the console at https://cloud.siliconflow.com/account/ak after a browser sign-up with a Google or GitHub account. The Anthropic-style `/messages` route also takes the key in `x-api-key`. No scopes, expiry or per-key limits are documented, and rate limits apply to the account, not the key. The error page says some models answer 403 until real-name authentication is done.", "pricing": "usage", "pricingNotes": "Pay per token, image, video or byte of speech text, with $1 in free credits for a new account. Whether a card is needed to claim the credit was not established. DeepSeek-V4.1-Flash costs $0.15 in, $0.003 cached and $0.60 out per 1M tokens. The FAQ says monthly spending limits can be set in the dashboard (https://www.siliconflow.com/pricing, checked 2026-10-09).", "priceSummary": "from $0.15 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI file or the pricing page (checked 2026-10-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://docs.siliconflow.com/en/userguide/quickstart", "rateLimitsUrl": "https://docs.siliconflow.com/cn/userguide/rate-limits/rate-limit-and-upgradation", "llmsTxt": "https://docs.siliconflow.com/llms.txt", "openapi": "https://docs.siliconflow.com/cn/api-reference/openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights", "embed.text", "rerank", "image.generate", "video.generate", "speech.tts", "speech.stt" ], "tags": [ "hosted", "model", "open-weights", "usage-based", "free-credit", "openapi", "llms-txt", "openai-compatible", "anthropic-compatible", "singapore" ], "lastRelease": "2026-09-14", "graded": true, "anchor": { "graded": true, "score": 46.7, "grade": "D", "agentReady": false, "rank": 921, "ranked": true, "rankOf": 1095, "categoryRank": 20, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 60, "maintenance": 47, "payments": 35, "reliability": 33, "schema": 65, "security": 39, "transparency": 51 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-09" }, "negative": 0, "verdict": "Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice.", "bestFor": "Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.", "strengths": [ "Per-token, per-image and per-video prices are public for every listed model, such as DeepSeek-V4.1-Flash at $0.15 in and $0.60 out per 1M tokens", "One Bearer key reaches 22 operations in a public OpenAPI 3.0 file, with OpenAI-style `/chat/completions` and Anthropic-style `/messages`", "`llms.txt` and a Markdown copy of every docs page, in English and Chinese", "Rate limits are published by spend tier, from 1,000 requests and 40,000 tokens a minute at L0 to 10,000 and 2,000,000 at L5", "The terms say SiliconFlow will not access Interaction Data, has no obligation to store it, and uses it only to supply the service" ], "weaknesses": [ "No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment", "Release notes stop at 11 June 2026. Six notices from December 2025 to June 2026 give a removal date equal to the notice date", "The Terms of Use of 9 September 2026 forbid use for any commercial purposes, scraping tools and benchmarking. This matters before any probe is run", "The OpenAPI model list and the function calling guide name models already removed, and omit every model added since July 2026", "No security.txt, disclosure policy, certification, DPA or sub-processor list was found, and no official SDK is published" ], "agentNotes": [ "Set the OpenAI client's base URL to `https://api.siliconflow.com/v1`, or the Anthropic client's to `https://api.siliconflow.com/`, and send the key as a Bearer token", "Take model ids from the model pages or `GET /v1/models`, not from the OpenAPI enum or the function calling guide, which list removed models", "Check the `model` field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models", "Use `response_format` of `json_object` only where the model page says JSON Mode is supported, and keep `max_tokens` about 10,000 below the context length", "Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 46.7 } ], "editorialScores": { "ergonomics": 60, "maintenance": 47, "payments": 35, "reliability": 33, "schema": 65, "security": 39, "transparency": 34 }, "provenanceScore": 68 }, "connect": { "install": "pip install --upgrade openai", "http": "curl --request POST \\\n --url https://api.siliconflow.com/v1/chat/completions \\\n --header 'authorization: Bearer $SILICONFLOW_API_KEY' \\\n --header 'content-type: application/json' \\\n --data '{\"model\":\"deepseek-ai/DeepSeek-V4.1-Flash\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}],\"max_tokens\":128}'", "claudeCode": "export ANTHROPIC_BASE_URL=\"https://api.siliconflow.com/\"\nexport ANTHROPIC_MODEL=\"your-preferred-model\"\nexport ANTHROPIC_API_KEY=\"sk-your-api-key-here\"" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/siliconflow" }, "area": "models", "unitPrices": [ { "item": "Z-Image-Turbo, one image", "unit": "image", "usd": 0.005 }, { "item": "FLUX.1-dev, one image", "unit": "image", "usd": 0.014 }, { "item": "FLUX 1.1 [pro], one image", "unit": "image", "usd": 0.04 }, { "item": "Wan2.2-T2V-A14B, one video", "unit": "call", "usd": 0.29, "note": "Priced per video generated" } ], "provenance": { "legalEntity": "SiliconFlow Labs Pte. Ltd.", "domain": "siliconflow.com", "domainRegistered": "2019-02-14", "endpointOnVendorDomain": true, "terms": "https://docs.siliconflow.com/en/legals/terms-of-service", "privacy": "https://docs.siliconflow.com/en/legals/privacy-policy", "statusPage": "", "changelog": "https://docs.siliconflow.com/en/release-notes/overview", "securityTxt": "none", "checked": "2026-10-09", "notes": [ "The Terms of Use, updated 9 September 2026, name SILICONFLOW LABS PTE. LTD., apply Singapore law and set SIAC arbitration in Singapore. They govern the platform in its web, API and mobile versions, and no separate API agreement was found.", "The Privacy Policy, updated 9 September 2026, names the same entity and cites Singapore's Personal Data Protection Act 2012. It keeps square brackets around several values, such as [Stripe] and [Google and GitHub].", "No status page is linked from the site, the docs index or the pages read.", "https://www.siliconflow.com/.well-known/security.txt answered 404.", "RDAP for siliconflow.com gives a registration date of 2019-02-14.", "The API answers at api.siliconflow.com, the docs at docs.siliconflow.com and the console at cloud.siliconflow.com. The terms point users in mainland China to siliconflow.cn.", "No SLA, DPA or sub-processor list was found." ], "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/siliconflow.json", "live": { "slug": "siliconflow", "probe": { "target": "https://api.siliconflow.com/v1", "method": "get", "lastAt": "2026-10-15T22:43:01.088070668Z", "lastOk": true, "lastStatus": 404, "lastMs": 252, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 265, "p95ms24h": 348, "samples24h": 253, "samples30d": 1563, "days": [ { "date": "2026-10-09", "probes": 85, "ok": 85 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 240, "ok": 240 } ] }, "securityTxt": { "url": "https://siliconflow.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-15T15:49:26.003950517Z" }, "llmsTxt": { "url": "https://docs.siliconflow.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-15T14:17:43.868888066Z" }, "domain": { "domain": "siliconflow.com", "registered": "2019-02-14", "source": "https://rdap.verisign.com/com/v1/domain/siliconflow.com", "checkedAt": "2026-10-11T13:14:05.623574089Z" }, "pages": [ { "url": "https://docs.siliconflow.com/en/release-notes/overview", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-15T21:56:19.844336469Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "020d6d5c5cb2" }, { "url": "https://www.siliconflow.com/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-15T22:14:06.438427926Z", "changedAt": "2026-10-15T22:14:06.438427926Z", "fingerprint": "b003b231f4d8" }, { "url": "https://docs.siliconflow.com/en/legals/privacy-policy", "kind": "privacy", "status": 304, "checkedAt": "2026-10-15T21:56:15.74118145Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "d7eb9964dc83" }, { "url": "https://docs.siliconflow.com/en/legals/terms-of-service", "kind": "terms", "status": 304, "checkedAt": "2026-10-15T21:56:17.834245718Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "299aa0be9f28" } ], "updatedAt": "2026-10-15T22:43:01.088070668Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Meta", "b": "SiliconFlow Labs Pte. Ltd.", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.siliconflow.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "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", "b": "Proprietary service under the SiliconFlow Terms of Use", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-15", "b": "2026-09-14", "name": "Last release" }, { "a": "", "b": "no date given", "name": "Terms last updated" }, { "a": "no document linked", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "", "b": "yes", "name": "Terms restrict automated access" }, { "a": "", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Muse Spark Open scores 53.4 (D) on agent readiness against SiliconFlow's 46.7 (D), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Muse Spark Open or SiliconFlow?" }, { "answer": "Muse Spark Open needs no key. SiliconFlow needs an API key.", "question": "Do Muse Spark Open and SiliconFlow need an API key?" }, { "answer": "No hosted endpoint is listed for Muse Spark Open. SiliconFlow has a hosted endpoint at https://api.siliconflow.com/v1.", "question": "Can an agent call Muse Spark Open and SiliconFlow without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 42 against 33", "Agent ergonomics, 69 against 60", "Security \u0026 auth, 44 against 39", "Payments \u0026 pricing, 50 against 35", "Maintenance \u0026 community, 60 against 47" ], "also": [ "No key needed to call it" ], "goodFor": "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.", "slug": "muse-spark-open", "watchFor": "The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight" }, { "aheadOn": null, "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.", "slug": "siliconflow", "watchFor": "No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment" } ], "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.json", "title": "Claude API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.json", "title": "Claude API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.json", "title": "Antseed vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-siliconflow.json", "title": "Antseed vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/antseed-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.json", "title": "BlockRun.AI vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow.json", "title": "BlockRun.AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open.json", "title": "Cloudflare AI Gateway vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow.json", "title": "Cloudflare AI Gateway vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open.json", "title": "Cloudflare Workers AI vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow.json", "title": "Cloudflare Workers AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.json", "title": "Cohere Chat API (Command models) vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow.json", "title": "Cohere Chat API (Command models) vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.json", "title": "DeepInfra vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow.json", "title": "DeepInfra vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.json", "title": "DeepSeek API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.json", "title": "DeepSeek API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.json", "title": "Gemini Developer API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.json", "title": "Gemini Developer API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.json", "title": "GroqCloud vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-siliconflow.json", "title": "GroqCloud vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/groq-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.json", "title": "Meta Model API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json", "title": "Meta Model API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.json", "title": "Mistral AI API vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.json", "title": "Mistral AI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai.json", "title": "Muse Spark Open vs Novita AI", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.json", "title": "Muse Spark Open vs OpenAI API", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter.json", "title": "Muse Spark Open vs OpenRouter", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference.json", "title": "Muse Spark Open vs Prism Inference", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus.json", "title": "Muse Spark Open vs RouterPlus", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.json", "title": "Muse Spark Open vs SambaCloud", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.json", "title": "Muse Spark Open vs StepFun API", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.json", "title": "Novita AI vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.json", "title": "OpenAI API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/openai-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow.json", "title": "OpenRouter vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/openrouter-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow.json", "title": "Prism Inference vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-siliconflow.json", "title": "RouterPlus vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/routerplus-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.json", "title": "SambaCloud vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api.json", "title": "SiliconFlow vs StepFun API", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api" } ], "scores": [ { "by": 9, "edge": "muse-spark-open", "key": "reliability", "muse-spark-open": 42, "name": "Reliability", "siliconflow": 33, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 4, "edge": "siliconflow", "key": "schema", "muse-spark-open": 61, "name": "Schema \u0026 documentation", "siliconflow": 65, "weight": 13 }, { "by": 9, "edge": "muse-spark-open", "key": "ergonomics", "muse-spark-open": 69, "name": "Agent ergonomics", "siliconflow": 60, "weight": 13 }, { "by": 5, "edge": "muse-spark-open", "key": "security", "muse-spark-open": 44, "name": "Security \u0026 auth", "siliconflow": 39, "weight": 14 }, { "by": 15, "edge": "muse-spark-open", "key": "payments", "muse-spark-open": 50, "name": "Payments \u0026 pricing", "siliconflow": 35, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 13, "edge": "muse-spark-open", "key": "maintenance", "muse-spark-open": 60, "name": "Maintenance \u0026 community", "siliconflow": 47, "weight": 7 }, { "by": 2, "edge": "muse-spark-open", "key": "transparency", "muse-spark-open": 53, "name": "Transparency \u0026 trust", "siliconflow": 51, "weight": 7 } ], "summary": "Muse Spark Open scores 53.4 (D) on agent readiness against SiliconFlow's 46.7 (D), and leads in 6 of 7 scored categories. Both do llm inference.", "verdicts": { "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.", "siliconflow": "Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow", "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.md", "slim": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.min.md" }, "markdown": "Muse Spark Open scores 53.4 (D) on agent readiness against SiliconFlow's 46.7 (D), and leads in 6 of 7 scored categories. Both do llm inference.\n\n- Muse Spark Open: grade D, 53.4/100, rank #760 of 1095. Markdown https://www.anchorterminal.com/tools/muse-spark-open.md · JSON https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json\n- SiliconFlow: grade D, 46.7/100, rank #921 of 1095. Markdown https://www.anchorterminal.com/tools/siliconflow.md · JSON https://www.anchorterminal.com/api/v1/tools/siliconflow.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 210 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Muse Spark Open (D)\n\nGood 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.\n\nAhead on:\n- Reliability, 42 against 33\n- Agent ergonomics, 69 against 60\n- Security \u0026 auth, 44 against 39\n- Payments \u0026 pricing, 50 against 35\n- Maintenance \u0026 community, 60 against 47\n\nAlso in its favour:\n- No key needed to call it\n\nWatch for: The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight\n\n### SiliconFlow (D)\n\nGood for: Agents that want recent open-weight chat models, plus image, video and speech, behind one OpenAI-style key at low per-token prices, and can live without a status page or SLA.\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: No status page, incident history or SLA was found, and the terms disclaim any uptime or availability commitment\n\n\n## Score by category\n\n| Category | Weight | Muse Spark Open | SiliconFlow | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 42 | 33 | Muse Spark Open +9 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 61 | 65 | SiliconFlow +4 |\n| Agent ergonomics | 13% (16.2 this run) | 69 | 60 | Muse Spark Open +9 |\n| Security \u0026 auth | 14% (17.5 this run) | 44 | 39 | Muse Spark Open +5 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 50 | 35 | Muse Spark Open +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 60 | 47 | Muse Spark Open +13 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 53 | 51 | Muse Spark Open +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **53.4 · D** | **46.7 · D** | |\n\n## Facts side by side\n\n| Fact | Muse Spark Open | SiliconFlow |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Meta | SiliconFlow Labs Pte. Ltd. |\n| Hosted endpoint | no (local only) | `https://api.siliconflow.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | 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 | Proprietary service under the SiliconFlow Terms of Use |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-15 | 2026-09-14 |\n| Terms last updated | | no date given |\n| Privacy policy last updated | no document linked | no date given |\n| Customer content may train models | | not found in the text |\n| Terms restrict automated access | | yes |\n| Terms restrict benchmarking | | yes |\n| Terms or service can change without notice | | yes |\n| Arbitration or class-action waiver | | yes |\n| Agent reviews | none | 2.5/5 (4) |\n\n## Verdicts\n\n**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.\n\n**SiliconFlow.** Per-token prices for every listed model are public, and one key reaches chat, embeddings, reranking, image, video and speech through OpenAI-style and Anthropic-style routes. No status page, SLA, security page or official SDK was found, release notes stop at 11 June 2026, and several model removals are dated the same day as their notice.\n\n## Before you call either\n\n### Muse Spark Open\n\n1. 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\n2. 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\n3. Stop only on `\u003c|eot|\u003e` and end of text. Stopping on `\u003c|eom|\u003e` cuts off tool calls and final answers\n4. Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`\n5. 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`\n\n### SiliconFlow\n\n1. Set the OpenAI client's base URL to `https://api.siliconflow.com/v1`, or the Anthropic client's to `https://api.siliconflow.com/`, and send the key as a Bearer token\n2. Take model ids from the model pages or `GET /v1/models`, not from the OpenAPI enum or the function calling guide, which list removed models\n3. Check the `model` field of each response. On 11 June 2026 traffic for GLM-5 and Kimi-K2.5 was routed to successor models\n4. Use `response_format` of `json_object` only where the model page says JSON Mode is supported, and keep `max_tokens` about 10,000 below the context length\n5. Set the Claude Code environment variables by hand. The automated route pipes a script from an Amazon S3 bucket into bash\n\n## Questions\n\n### Which is better for AI agents, Muse Spark Open or SiliconFlow?\n\nMuse Spark Open scores 53.4 (D) on agent readiness against SiliconFlow's 46.7 (D), and leads in 6 of 7 scored categories.\n\n### Do Muse Spark Open and SiliconFlow need an API key?\n\nMuse Spark Open needs no key. SiliconFlow needs an API key.\n\n### Can an agent call Muse Spark Open and SiliconFlow without installing anything?\n\nNo hosted endpoint is listed for Muse Spark Open. SiliconFlow has a hosted endpoint at https://api.siliconflow.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.json, and with the fewest tokens: https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"muse-spark-open\", \"b\": \"siliconflow\"}`. From a terminal: `anchor compare muse-spark-open siliconflow`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json and https://www.anchorterminal.com/api/v1/tools/siliconflow.json\n\n## Other comparisons with Muse Spark Open or SiliconFlow\n\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Claude API vs SiliconFlow](https://www.anchorterminal.com/compare/anthropic-api-vs-siliconflow.md)\n- [Antseed vs Muse Spark Open](https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.md)\n- [Antseed vs SiliconFlow](https://www.anchorterminal.com/compare/antseed-vs-siliconflow.md)\n- [BlockRun.AI vs Muse Spark Open](https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.md)\n- [BlockRun.AI vs SiliconFlow](https://www.anchorterminal.com/compare/blockrun-ai-vs-siliconflow.md)\n- [Cloudflare AI Gateway vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open.md)\n- [Cloudflare AI Gateway vs SiliconFlow](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-siliconflow.md)\n- [Cloudflare Workers AI vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open.md)\n- [Cloudflare Workers AI vs SiliconFlow](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-siliconflow.md)\n- [Cohere Chat API (Command models) vs Muse Spark Open](https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.md)\n- [Cohere Chat API (Command models) vs SiliconFlow](https://www.anchorterminal.com/compare/cohere-chat-vs-siliconflow.md)\n- [DeepInfra vs Muse Spark Open](https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.md)\n- [DeepInfra vs SiliconFlow](https://www.anchorterminal.com/compare/deepinfra-vs-siliconflow.md)\n- [DeepSeek API vs Muse Spark Open](https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.md)\n- [DeepSeek API vs SiliconFlow](https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.md)\n- [Gemini Developer API vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.md)\n- [Gemini Developer API vs SiliconFlow](https://www.anchorterminal.com/compare/gemini-api-vs-siliconflow.md)\n- [GroqCloud vs Muse Spark Open](https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.md)\n- [GroqCloud vs SiliconFlow](https://www.anchorterminal.com/compare/groq-vs-siliconflow.md)\n- [Meta Model API vs Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)\n- [Meta Model API vs SiliconFlow](https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.md)\n- [Mistral AI API vs Muse Spark Open](https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.md)\n- [Mistral AI API vs SiliconFlow](https://www.anchorterminal.com/compare/mistral-api-vs-siliconflow.md)\n- [Muse Spark Open vs Novita AI](https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai.md)\n- [Muse Spark Open vs OpenAI API](https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.md)\n- [Muse Spark Open vs OpenRouter](https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter.md)\n- [Muse Spark Open vs Prism Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference.md)\n- [Muse Spark Open vs RouterPlus](https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus.md)\n- [Muse Spark Open vs SambaCloud](https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.md)\n- [Muse Spark Open vs StepFun API](https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.md)\n- [Novita AI vs SiliconFlow](https://www.anchorterminal.com/compare/novita-ai-vs-siliconflow.md)\n- [OpenAI API vs SiliconFlow](https://www.anchorterminal.com/compare/openai-api-vs-siliconflow.md)\n- [OpenRouter vs SiliconFlow](https://www.anchorterminal.com/compare/openrouter-vs-siliconflow.md)\n- [Prism Inference vs SiliconFlow](https://www.anchorterminal.com/compare/prism-inference-vs-siliconflow.md)\n- [RouterPlus vs SiliconFlow](https://www.anchorterminal.com/compare/routerplus-vs-siliconflow.md)\n- [SambaCloud vs SiliconFlow](https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.md)\n- [SiliconFlow vs StepFun API](https://www.anchorterminal.com/compare/siliconflow-vs-stepfun-api.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-15", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Muse Spark Open vs SiliconFlow", "url": "" } ], "description": "Muse Spark Open scores 53.4 (D) to SiliconFlow's 46.7 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Muse Spark Open D 53.4", "SiliconFlow D 46.7", "scores" ], "h1": "Muse Spark Open vs SiliconFlow", "image": "https://www.anchorterminal.com/assets/og/compare-muse-spark-open-vs-siliconflow.png", "path": "/compare/muse-spark-open-vs-siliconflow", "published": "2026-10-01", "section": "tools", "title": "Muse Spark Open vs SiliconFlow for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow" }, "tokens": { "markdown": 3000, "slim": 730 }, "version": 1 }