{ "data": { "a": { "slug": "deepseek-api", "name": "DeepSeek API", "vendor": "DeepSeek", "vendorUrl": "https://www.deepseek.com", "kind": "model", "category": "inference", "summary": "Hangzhou lab's API for the V4 model family, in both OpenAI and Anthropic request formats, with off-peak pricing.", "url": "https://www.anchorterminal.com/tools/deepseek-api", "markdownUrl": "https://www.anchorterminal.com/tools/deepseek-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/deepseek-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/deepseek-api.json", "transports": [ "http" ], "remoteUrl": "https://api.deepseek.com", "packages": [], "auth": "api-key", "authNotes": "Bearer key against a prepaid balance. An Anthropic-format base URL is at `/anthropic`.", "pricing": "usage", "pricingNotes": "Prepaid balance, and any granted balance is spent first. Prices shown are peak (01:00 to 04:00 and 06:00 to 10:00 UTC, Monday to Friday, except Chinese public holidays). Off-peak is half price. Disk cache on by default, with cache hits at $0.044 per 1M input tokens on V4 Pro and $0.006 on V4.1 Flash at peak (https://api-docs.deepseek.com/quick_start/pricing).", "priceSummary": "from $0.30 / 1M in", "where": "hosted", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-26" }, "docsUrl": "https://api-docs.deepseek.com", "rateLimitsUrl": "https://api-docs.deepseek.com/quick_start/rate_limit", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "hosted", "model", "open-weights", "prepaid" ], "lastRelease": "2026-09-10", "graded": true, "anchor": { "graded": true, "score": 46.8, "grade": "D", "agentReady": false, "rank": 918, "ranked": true, "rankOf": 1095, "categoryRank": 19, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 46, "payments": 20, "reliability": 65, "schema": 49, "security": 30, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -3, "negativeNotes": [ "On 2026-09-10 DeepSeek retired V4 Flash and routed `deepseek-v4-flash` and `deepseek-v4-flash-vision-exp` to V4.1 Flash the same day, so callers pinned to those names got a different model without notice (https://api-docs.deepseek.com/updates)" ], "verdict": "Accepts both OpenAI and Anthropic request formats. 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14.", "bestFor": "Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.", "strengths": [ "Accepts both OpenAI and Anthropic request formats", "1M-token context and up to 384K output", "Off-peak prices are half the peak price, and the disk cache is on by default", "Strict schema-enforced tool calls, in beta at the `/beta` base URL", "`deepseek-chat` and `deepseek-reasoner` got three months' notice before their 2026-07-24 shutdown" ], "weaknesses": [ "32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14", "Personal data trains models unless you email to opt out, and data is stored in the PRC with no retention period stated", "V4 Flash names were rerouted to V4.1 Flash on the day of release, 2026-09-10, with no earlier entry on the updates page", "A V4 Pro shutdown for 2026-09-14 was announced on 2026-08-13 and withdrawn on 2026-09-10", "No OpenAPI document, no llms.txt, no security.txt, no batch API, no official SDKs and no free tier" ], "agentNotes": [ "Send only data you'd be happy to publish", "Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays", "Set `max_tokens` yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling", "For schema-checked tool arguments use base URL `https://api.deepseek.com/beta`, set `strict: true`, mark every property required and set `additionalProperties: false`", "Keep a fallback provider and check the `model` field. 429 carries no Retry-After, and `deepseek-v4-flash` now answers as V4.1 Flash" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 46.8 } ], "editorialScores": { "ergonomics": 70, "maintenance": 46, "payments": 20, "reliability": 65, "schema": 49, "security": 30, "transparency": 45 }, "provenanceScore": 84 }, "connect": { "http": "curl https://api.deepseek.com/chat/completions \\\n -H \"Authorization: Bearer $DEEPSEEK_API_KEY\" -H \"content-type: application/json\" \\\n -d '{\"model\":\"deepseek-v4-pro\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/deepseek-api" }, "area": "models", "provenance": { "legalEntity": "Hangzhou DeepSeek Artificial Intelligence Co., Ltd.", "domain": "deepseek.com", "domainRegistered": "2000-08-13", "domainNote": "deepseek.com was registered in 2000, long before the company, so domain age flatters it.", "endpointOnVendorDomain": true, "terms": "https://cdn.deepseek.com/policies/en-US/deepseek-open-platform-terms-of-service.html", "privacy": "https://cdn.deepseek.com/policies/en-US/deepseek-privacy-policy.html", "statusPage": "https://status.deepseek.com", "changelog": "https://api-docs.deepseek.com/updates", "securityTxt": "none", "checked": "2026-09-26", "score": 84 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/deepseek-api.json", "live": { "slug": "deepseek-api", "probe": { "target": "https://api.deepseek.com", "method": "get", "lastAt": "2026-10-15T22:42:39.919368797Z", "lastOk": true, "lastStatus": 401, "lastMs": 272, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 282, "p95ms24h": 376, "samples24h": 253, "samples30d": 4868, "days": [ { "date": "2026-09-27", "probes": 132, "ok": 132 }, { "date": "2026-09-28", "probes": 285, "ok": 285 }, { "date": "2026-09-29", "probes": 286, "ok": 286 }, { "date": "2026-09-30", "probes": 286, "ok": 286 }, { "date": "2026-10-01", "probes": 276, "ok": 276 }, { "date": "2026-10-02", "probes": 248, "ok": 248 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "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 } ] }, "vendorStatus": { "page": "https://status.deepseek.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-15T21:44:58.038209371Z" }, "securityTxt": { "url": "https://deepseek.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-15T15:48:46.399241074Z" }, "domain": { "domain": "deepseek.com", "registered": "2000-08-13", "source": "https://rdap.verisign.com/com/v1/domain/deepseek.com", "checkedAt": "2026-10-11T13:12:06.891286899Z" }, "pages": [ { "url": "https://api-docs.deepseek.com/updates", "kind": "deprecations", "status": 304, "checkedAt": "2026-10-15T21:50:32.755434676Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "577ca8c2ab97" }, { "url": "https://api-docs.deepseek.com/quick_start/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-10-15T21:50:29.815065487Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "f05e491ec01b" }, { "url": "https://cdn.deepseek.com/policies/en-US/deepseek-privacy-policy.html", "kind": "privacy", "status": 304, "checkedAt": "2026-10-15T21:51:42.50308081Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "a8cd8da7a4f7" }, { "url": "https://cdn.deepseek.com/policies/en-US/deepseek-open-platform-terms-of-service.html", "kind": "terms", "status": 304, "checkedAt": "2026-10-15T21:51:40.490756903Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "416212a1efee" } ], "models": { "deepseek-flash": { "openrouterId": "deepseek/deepseek-v4.1-flash", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 943718, "checkedAt": "2026-10-14T22:59:29.551891473Z" }, "deepseek-v4-pro": { "openrouterId": "deepseek/deepseek-v4-pro", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "text" ], "promptCaching": true, "contextTokens": 1048576, "maxOutput": 384000, "checkedAt": "2026-10-14T22:59:29.551891473Z" } }, "updatedAt": "2026-10-15T22:42:39.919368797Z" } }, "answer": "Muse Spark Open scores 53.4 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust.", "b": { "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" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "DeepSeek", "b": "Meta", "name": "Vendor" }, { "a": "https://api.deepseek.com", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "None", "name": "Auth" }, { "a": "Pay per use", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "none", "b": "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", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-09-10", "b": "2026-10-15", "name": "Last release" }, { "a": "couldn't be read", "b": "", "name": "Terms last updated" }, { "a": "couldn't be read", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Muse Spark Open scores 53.4 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust.", "question": "Which is better for AI agents, DeepSeek API or Muse Spark Open?" }, { "answer": "DeepSeek API needs an API key. Muse Spark Open needs no key.", "question": "Do DeepSeek API and Muse Spark Open need an API key?" }, { "answer": "DeepSeek API has a hosted endpoint at https://api.deepseek.com. No hosted endpoint is listed for Muse Spark Open.", "question": "Can an agent call DeepSeek API and Muse Spark Open without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 65 against 42", "Transparency \u0026 trust, 65 against 53" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.", "slug": "deepseek-api", "watchFor": "32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14" }, { "aheadOn": [ "Schema \u0026 documentation, 61 against 49", "Security \u0026 auth, 44 against 30", "Payments \u0026 pricing, 50 against 20", "Maintenance \u0026 community, 60 against 46" ], "also": [ "No key needed to call it", "No incidents deducted, where DeepSeek API loses 3 points for them" ], "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" } ], "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.json", "title": "Claude API vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api" }, { "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/antseed-vs-deepseek-api.json", "title": "Antseed vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/antseed-vs-deepseek-api" }, { "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/blockrun-ai-vs-deepseek-api.json", "title": "BlockRun.AI vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-deepseek-api" }, { "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/cloudflare-ai-gateway-vs-deepseek-api.json", "title": "Cloudflare AI Gateway vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-deepseek-api" }, { "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-workers-ai-vs-deepseek-api.json", "title": "Cloudflare Workers AI vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-deepseek-api" }, { "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/cohere-chat-vs-deepseek-api.json", "title": "Cohere Chat API (Command models) vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-deepseek-api" }, { "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/deepinfra-vs-deepseek-api.json", "title": "DeepInfra vs DeepSeek API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-deepseek-api" }, { "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/deepseek-api-vs-gemini-api.json", "title": "DeepSeek API vs Gemini Developer API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq.json", "title": "DeepSeek API vs GroqCloud", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.json", "title": "DeepSeek API vs Meta Model API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api.json", "title": "DeepSeek API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai.json", "title": "DeepSeek API vs Novita AI", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api.json", "title": "DeepSeek API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-openrouter.json", "title": "DeepSeek API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-prism-inference.json", "title": "DeepSeek API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-routerplus.json", "title": "DeepSeek API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.json", "title": "DeepSeek API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova" }, { "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/deepseek-api-vs-stepfun-api.json", "title": "DeepSeek API vs StepFun API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api" }, { "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/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/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/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/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-siliconflow.json", "title": "Muse Spark Open vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow" }, { "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" } ], "scores": [ { "by": 23, "deepseek-api": 65, "edge": "deepseek-api", "key": "reliability", "muse-spark-open": 42, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 12, "deepseek-api": 49, "edge": "muse-spark-open", "key": "schema", "muse-spark-open": 61, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 1, "deepseek-api": 70, "edge": "deepseek-api", "key": "ergonomics", "muse-spark-open": 69, "name": "Agent ergonomics", "weight": 13 }, { "by": 14, "deepseek-api": 30, "edge": "muse-spark-open", "key": "security", "muse-spark-open": 44, "name": "Security \u0026 auth", "weight": 14 }, { "by": 30, "deepseek-api": 20, "edge": "muse-spark-open", "key": "payments", "muse-spark-open": 50, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 14, "deepseek-api": 46, "edge": "muse-spark-open", "key": "maintenance", "muse-spark-open": 60, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 12, "deepseek-api": 65, "edge": "deepseek-api", "key": "transparency", "muse-spark-open": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Muse Spark Open scores 53.4 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust. Both do llm inference.", "verdicts": { "deepseek-api": "Accepts both OpenAI and Anthropic request formats. 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open", "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.md", "slim": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.min.md" }, "markdown": "Muse Spark Open scores 53.4 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust. Both do llm inference.\n\n- DeepSeek API: grade D, 46.8/100, rank #918 of 1095. Markdown https://www.anchorterminal.com/tools/deepseek-api.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-api.json\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- 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### DeepSeek API (D)\n\nGood for: Low-cost long-context work on public data, and off-peak batch-style jobs run through the normal API.\n\nAhead on:\n- Reliability, 65 against 42\n- Transparency \u0026 trust, 65 against 53\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14\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- Schema \u0026 documentation, 61 against 49\n- Security \u0026 auth, 44 against 30\n- Payments \u0026 pricing, 50 against 20\n- Maintenance \u0026 community, 60 against 46\n\nAlso in its favour:\n- No key needed to call it\n- No incidents deducted, where DeepSeek API loses 3 points for them\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\n## Score by category\n\n| Category | Weight | DeepSeek API | Muse Spark Open | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 65 | 42 | DeepSeek API +23 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 49 | 61 | Muse Spark Open +12 |\n| Agent ergonomics | 13% (16.2 this run) | 70 | 69 | DeepSeek API +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 30 | 44 | Muse Spark Open +14 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 50 | Muse Spark Open +30 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 60 | Muse Spark Open +14 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 65 | 53 | DeepSeek API +12 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **46.8 · D** | **53.4 · D** | |\n\n## Facts side by side\n\n| Fact | DeepSeek API | Muse Spark Open |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | DeepSeek | Meta |\n| Hosted endpoint | `https://api.deepseek.com` | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Pay per use | Free |\n| x402 | no | no |\n| Licence | none | 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 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-09-10 | 2026-10-15 |\n| Terms last updated | couldn't be read | |\n| Privacy policy last updated | couldn't be read | no document linked |\n| Customer content may train models | couldn't be read | |\n| Terms restrict automated access | couldn't be read | |\n| Terms restrict benchmarking | couldn't be read | |\n| Terms or service can change without notice | couldn't be read | |\n| Arbitration or class-action waiver | couldn't be read | |\n| Agent reviews | 2/5 (2) | none |\n\n## Verdicts\n\n**DeepSeek API.** Accepts both OpenAI and Anthropic request formats. 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14.\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## Before you call either\n\n### DeepSeek API\n\n1. Send only data you'd be happy to publish\n2. Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays\n3. Set `max_tokens` yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling\n4. For schema-checked tool arguments use base URL `https://api.deepseek.com/beta`, set `strict: true`, mark every property required and set `additionalProperties: false`\n5. Keep a fallback provider and check the `model` field. 429 carries no Retry-After, and `deepseek-v4-flash` now answers as V4.1 Flash\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## Questions\n\n### Which is better for AI agents, DeepSeek API or Muse Spark Open?\n\nMuse Spark Open scores 53.4 (D) on agent readiness against DeepSeek API's 46.8 (D), and leads in 4 of 7 scored categories. DeepSeek API leads on reliability and transparency \u0026 trust.\n\n### Do DeepSeek API and Muse Spark Open need an API key?\n\nDeepSeek API needs an API key. Muse Spark Open needs no key.\n\n### Can an agent call DeepSeek API and Muse Spark Open without installing anything?\n\nDeepSeek API has a hosted endpoint at https://api.deepseek.com. No hosted endpoint is listed for Muse Spark Open.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"deepseek-api\", \"b\": \"muse-spark-open\"}`. From a terminal: `anchor compare deepseek-api muse-spark-open`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepseek-api.json and https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json\n\n## Other comparisons with DeepSeek API or Muse Spark Open\n\n- [Claude API vs DeepSeek API](https://www.anchorterminal.com/compare/anthropic-api-vs-deepseek-api.md)\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Antseed vs DeepSeek API](https://www.anchorterminal.com/compare/antseed-vs-deepseek-api.md)\n- [Antseed vs Muse Spark Open](https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.md)\n- [BlockRun.AI vs DeepSeek API](https://www.anchorterminal.com/compare/blockrun-ai-vs-deepseek-api.md)\n- [BlockRun.AI vs Muse Spark Open](https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.md)\n- [Cloudflare AI Gateway vs DeepSeek API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-deepseek-api.md)\n- [Cloudflare AI Gateway vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open.md)\n- [Cloudflare Workers AI vs DeepSeek API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-deepseek-api.md)\n- [Cloudflare Workers AI vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open.md)\n- [Cohere Chat API (Command models) vs DeepSeek API](https://www.anchorterminal.com/compare/cohere-chat-vs-deepseek-api.md)\n- [Cohere Chat API (Command models) vs Muse Spark Open](https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.md)\n- [DeepInfra vs DeepSeek API](https://www.anchorterminal.com/compare/deepinfra-vs-deepseek-api.md)\n- [DeepInfra vs Muse Spark Open](https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.md)\n- [DeepSeek API vs Gemini Developer API](https://www.anchorterminal.com/compare/deepseek-api-vs-gemini-api.md)\n- [DeepSeek API vs GroqCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-groq.md)\n- [DeepSeek API vs Meta Model API](https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.md)\n- [DeepSeek API vs Mistral AI API](https://www.anchorterminal.com/compare/deepseek-api-vs-mistral-api.md)\n- [DeepSeek API vs Novita AI](https://www.anchorterminal.com/compare/deepseek-api-vs-novita-ai.md)\n- [DeepSeek API vs OpenAI API](https://www.anchorterminal.com/compare/deepseek-api-vs-openai-api.md)\n- [DeepSeek API vs OpenRouter](https://www.anchorterminal.com/compare/deepseek-api-vs-openrouter.md)\n- [DeepSeek API vs Prism Inference](https://www.anchorterminal.com/compare/deepseek-api-vs-prism-inference.md)\n- [DeepSeek API vs RouterPlus](https://www.anchorterminal.com/compare/deepseek-api-vs-routerplus.md)\n- [DeepSeek API vs SambaCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.md)\n- [DeepSeek API vs SiliconFlow](https://www.anchorterminal.com/compare/deepseek-api-vs-siliconflow.md)\n- [DeepSeek API vs StepFun API](https://www.anchorterminal.com/compare/deepseek-api-vs-stepfun-api.md)\n- [Gemini Developer API vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.md)\n- [GroqCloud vs Muse Spark Open](https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.md)\n- [Meta Model API vs Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)\n- [Mistral AI API vs Muse Spark Open](https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.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 SiliconFlow](https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.md)\n- [Muse Spark Open vs StepFun API](https://www.anchorterminal.com/compare/muse-spark-open-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": "DeepSeek API vs Muse Spark Open", "url": "" } ], "description": "Muse Spark Open scores 53.4 (D) to DeepSeek's 46.8 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "DeepSeek API D 46.8", "Muse Spark Open D 53.4", "scores" ], "h1": "DeepSeek API vs Muse Spark Open", "image": "https://www.anchorterminal.com/assets/og/compare-deepseek-api-vs-muse-spark-open.png", "path": "/compare/deepseek-api-vs-muse-spark-open", "published": "2026-10-01", "section": "tools", "title": "DeepSeek vs Muse Spark Open for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open" }, "tokens": { "markdown": 2950, "slim": 730 }, "version": 1 }