{ "data": { "a": { "slug": "minimax-api", "name": "MiniMax API", "vendor": "MiniMax", "vendorUrl": "https://www.minimax.io", "kind": "model", "category": "inference", "summary": "MiniMax's API for its M-series text models, M3.1 Flash and M3, in the Anthropic Messages, OpenAI Chat Completions and OpenAI Responses formats, with 1M-token context and automatic prompt caching.", "url": "https://www.anchorterminal.com/tools/minimax-api", "markdownUrl": "https://www.anchorterminal.com/tools/minimax-api.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minimax-api.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minimax-api.json", "repo": "https://github.com/MiniMax-AI/MiniMax-M3", "license": "Proprietary API under MiniMax's platform terms. MiniMax-M3 weights are on Hugging Face under the MiniMax community licence", "transports": [ "http" ], "remoteUrl": "https://api.minimax.io", "packages": [], "auth": "api-key", "authNotes": "Bearer key from platform.minimax.io, charged to a prepaid balance. M Plan subscribers get a separate Subscription Key that draws on the plan's usage windows, and the two kinds of key can't be swapped. Mainland China accounts use api.minimaxi.com with a separate key. MiniMax says it may disable a key that leaks publicly.", "pricing": "usage", "pricingNotes": "Prepaid balance, pay as you go. MiniMax-M3.1-Flash is $0.15 per million input tokens, $0.60 per million output tokens and $0.015 per million cache-read tokens at any input length. MiniMax-M3 is $0.30 in and $1.20 out up to 512K input tokens and $0.60 and $2.40 above, with cache reads at $0.06 and $0.12, and a Priority tier at 1.5 times that M3.1 Flash doesn't take. Caching is automatic. The web_search server tool (beta) is $0.01 a request. M Plan subscriptions for coding tools are Go $22, Explore $55 and Build $132 a month, and annual billing pays for 10 months (https://platform.minimax.io/docs/pricing/overview, https://platform.minimax.io/docs/m-plan/monthly-offer, checked 19 October 2026).", "priceSummary": "from $0.15 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, llms.txt or pricing page. Prepaid balance top-up or an M Plan subscription (checked 2026-10-19).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 493, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://platform.minimax.io/docs/guides/text-generation", "rateLimitsUrl": "https://platform.minimax.io/docs/guides/rate-limits", "llmsTxt": "https://platform.minimax.io/docs/llms.txt", "openapi": "https://platform.minimax.io/docs/api-reference/text/api/openapi-chat-anthropic.json", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "hosted", "model", "open-weights", "prepaid", "openapi", "llms-txt" ], "lastRelease": "2026-10-19", "graded": true, "anchor": { "graded": true, "score": 55.2, "grade": "C", "agentReady": false, "rank": 751, "ranked": true, "rankOf": 1175, "categoryRank": 19, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 59, "maintenance": 45, "payments": 20, "reliability": 75, "schema": 82, "security": 30, "transparency": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-19" }, "negative": 0, "verdict": "M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 23 short LLM incidents in the week to 19 October 2026.", "bestFor": "Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.", "strengths": [ "M3.1 Flash at $0.15 in, $0.60 out and $0.015 for cache reads per million tokens, flat at any input length", "Anthropic Messages, OpenAI Chat Completions and OpenAI Responses formats, each with an OpenAPI 3.1 file", "1M-token context and up to 524,288 output tokens on M3.1 Flash and M3", "Automatic prompt caching and a token-count endpoint", "MiniMax-M3 weights on Hugging Face under the MiniMax community licence" ], "weaknesses": [ "The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found", "No free tier, SLA, batch API, JSON Schema output mode or security.txt", "23 LLM error incidents on the status page from 13 to 19 October 2026, each under 45 minutes", "M2.5 and M2.7 retire on 18 November 2026, 30 days after new users lost them, and plan requests to them already go to M3.1 Flash", "The model list calls M2.5 and M2.7 retired while the notice on the same page gives 18 November 2026" ], "agentNotes": [ "Use the Anthropic-format base URL `https://api.minimax.io/anthropic` for tool calls. The OpenAI-format schema has no `tool_choice` or `response_format`", "Set `output_config.effort` (or `reasoning_effort`) below `max` for routine calls. M3.1 Flash defaults to max, can't turn thinking off, and counts thinking against `max_tokens`", "Don't rely on `stop_sequences` or `top_k`. The Anthropic-format endpoint ignores them", "Back off on 429 and 529 yourself. No Retry-After header is documented", "Use a pay-as-you-go key for production. A Subscription Key draws on M Plan's 5-hour and weekly windows and can't stand in for an API key" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 55.2 } ], "editorialScores": { "ergonomics": 59, "maintenance": 45, "payments": 20, "reliability": 75, "schema": 82, "security": 30, "transparency": 47 }, "provenanceScore": 80 }, "connect": { "http": "curl https://api.minimax.io/anthropic/v1/messages \\\n -H \"Authorization: Bearer $MINIMAX_API_KEY\" -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"MiniMax-M3.1-Flash\",\"output_config\":{\"effort\":\"low\"},\"max_tokens\":4096,\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/minimax-api" }, "sameCompany": [ "minimax-video", "minimax-voice-cloning", "minimax-code" ], "area": "models", "unitPrices": [ { "item": "web_search server tool (beta)", "unit": "1k-requests", "usd": 10 }, { "item": "M Plan Go", "unit": "month", "usd": 22, "note": "M3.1 Flash, image and audio, no video. Annual billing pays for 10 months" }, { "item": "M Plan Explore", "unit": "month", "usd": 55, "note": "3 times Go's usage, adds H3 video" }, { "item": "M Plan Build", "unit": "month", "usd": 132, "note": "7.5 times Go's usage, adds H3 video" } ], "provenance": { "legalEntity": "Nanonoble Pte. Ltd.", "domain": "minimax.io", "domainRegistered": "2021-03-27", "endpointOnVendorDomain": true, "terms": "https://platform.minimax.io/protocol/terms-of-service", "privacy": "https://platform.minimax.io/protocol/privacy-policy", "statusPage": "https://status.minimax.io", "changelog": "https://platform.minimax.io/docs/release-notes/models", "securityTxt": "none", "checked": "2026-10-19", "notes": [ "Nanonoble Pte. Ltd., 152 Beach Road, #14-02 Gateway East, Singapore, is named in the terms (effective 30 March 2026) and the privacy policy (updated 30 March 2026), read on 19 October 2026 from the document text the pages carry for the browser. The policy reader recorded both pages as unreadable on 8 October, and that reading is kept.", "RDAP for minimax.io gives a registration date of 2021-03-27 and a transfer on 2025-01-31, as recorded on the MiniMax Video API listing.", "platform.minimax.io and api.minimax.io answer 404 for /.well-known/security.txt, and www.minimax.io redirects it to the home page.", "The API release notes page has no entry after 28 October 2025. Model releases are dated on a separate page, which has the 19 October 2026 entry." ], "score": 80 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/minimax-api.json", "live": { "slug": "minimax-api", "probe": { "target": "https://api.minimax.io", "method": "get", "lastAt": "2026-10-19T18:43:17.575383015Z", "lastOk": true, "lastStatus": 404, "lastMs": 299, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 258, "p95ms24h": 445, "samples24h": 38, "samples30d": 38, "days": [ { "date": "2026-10-19", "probes": 38, "ok": 38 } ] }, "vendorStatus": { "page": "https://status.minimax.io", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-19T18:45:19.534162785Z" }, "securityTxt": { "url": "https://minimax.io/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-19T15:55:03.5197794Z" }, "updatedAt": "2026-10-19T18:45:19.534162785Z" } }, "answer": "MiniMax API scores 55.2 (C) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 3 of 7 scored categories. Muse Spark Open leads on agent ergonomics, security \u0026 auth, payments \u0026 pricing and maintenance \u0026 community.", "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": 805, "ranked": true, "rankOf": 1175, "categoryRank": 23, "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", "securityTxt": { "url": "https://meta.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-19T15:54:43.705827903Z" }, "llmsTxt": { "url": "https://dev.meta.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-19T14:28:24.000990732Z" }, "domain": { "domain": "meta.ai", "registered": "2017-12-16", "source": "https://rdap.identitydigital.services/rdap/domain/meta.ai", "checkedAt": "2026-10-18T13:39:00.851805812Z" }, "pages": [ { "url": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B/blob/main/LICENSE.md", "kind": "terms", "status": 200, "checkedAt": "2026-10-18T23:31:51.107277175Z", "changedAt": "2026-10-18T23:31:51.107277175Z", "fingerprint": "e544b54f12af" } ], "updatedAt": "2026-10-19T15:54:43.705827903Z" } }, "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "MiniMax", "b": "Meta", "name": "Vendor" }, { "a": "https://api.minimax.io", "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": "Proprietary API under MiniMax's platform terms. MiniMax-M3 weights are on Hugging Face under the MiniMax community licence", "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": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-19", "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": "493 stars", "b": "none", "name": "Popularity" }, { "a": "2.8/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "MiniMax API scores 55.2 (C) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 3 of 7 scored categories. Muse Spark Open leads on agent ergonomics, security \u0026 auth, payments \u0026 pricing and maintenance \u0026 community.", "question": "Which is better for AI agents, MiniMax API or Muse Spark Open?" }, { "answer": "MiniMax API needs an API key. Muse Spark Open needs no key.", "question": "Do MiniMax API and Muse Spark Open need an API key?" }, { "answer": "MiniMax API has a hosted endpoint at https://api.minimax.io. No hosted endpoint is listed for Muse Spark Open.", "question": "Can an agent call MiniMax API and Muse Spark Open without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 75 against 42", "Schema \u0026 documentation, 82 against 61", "Transparency \u0026 trust, 64 against 53" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.", "slug": "minimax-api", "watchFor": "The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found" }, { "aheadOn": [ "Agent ergonomics, 69 against 59", "Security \u0026 auth, 44 against 30", "Payments \u0026 pricing, 50 against 20", "Maintenance \u0026 community, 60 against 45" ], "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" } ], "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api.json", "title": "Claude API vs MiniMax API", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-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-minimax-api.json", "title": "Antseed vs MiniMax API", "url": "https://www.anchorterminal.com/compare/antseed-vs-minimax-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-minimax-api.json", "title": "BlockRun.AI vs MiniMax API", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-minimax-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/cerebras-inference-vs-minimax-api.json", "title": "Cerebras Inference vs MiniMax API", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open.json", "title": "Cerebras Inference vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-minimax-api.json", "title": "Cloudflare AI Gateway vs MiniMax API", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-minimax-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-minimax-api.json", "title": "Cloudflare Workers AI vs MiniMax API", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-minimax-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-minimax-api.json", "title": "Cohere Chat API (Command models) vs MiniMax API", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-minimax-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-minimax-api.json", "title": "DeepInfra vs MiniMax API", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-minimax-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-minimax-api.json", "title": "DeepSeek API vs MiniMax API", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-minimax-api" }, { "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/elorian-glimpse-vs-minimax-api.json", "title": "Glimpse vs MiniMax API", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-spark-open.json", "title": "Glimpse vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-minimax-api.json", "title": "Fireworks AI Inference vs MiniMax API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open.json", "title": "Fireworks AI Inference vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-minimax-api.json", "title": "Gemini Developer API vs MiniMax API", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-minimax-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-minimax-api.json", "title": "GroqCloud vs MiniMax API", "url": "https://www.anchorterminal.com/compare/groq-vs-minimax-api" }, { "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/jais-3-vs-minimax-api.json", "title": "Jais 3 vs MiniMax API", "url": "https://www.anchorterminal.com/compare/jais-3-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-muse-spark-open.json", "title": "Jais 3 vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/jais-3-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-minimax-api.json", "title": "Meta Model API vs MiniMax API", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-minimax-api" }, { "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/minimax-api-vs-mistral-api.json", "title": "MiniMax API vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-nemotron-3-5-super-vl.json", "title": "MiniMax API vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-novita-ai.json", "title": "MiniMax API vs Novita AI", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-openai-api.json", "title": "MiniMax API vs OpenAI API", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-openrouter.json", "title": "MiniMax API vs OpenRouter", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-prism-inference.json", "title": "MiniMax API vs Prism Inference", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam.json", "title": "MiniMax API vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-routerplus.json", "title": "MiniMax API vs RouterPlus", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-sambanova.json", "title": "MiniMax API vs SambaCloud", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow.json", "title": "MiniMax API vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-stepfun-api.json", "title": "MiniMax API vs StepFun API", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-together-inference.json", "title": "MiniMax API vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway.json", "title": "MiniMax API vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway" }, { "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-nemotron-3-5-super-vl.json", "title": "Muse Spark Open vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-nemotron-3-5-super-vl" }, { "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-reflection-beam.json", "title": "Muse Spark Open vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-reflection-beam" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.json", "title": "Muse Spark Open vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway.json", "title": "Muse Spark Open vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway" } ], "scores": [ { "by": 33, "edge": "minimax-api", "key": "reliability", "minimax-api": 75, "muse-spark-open": 42, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 21, "edge": "minimax-api", "key": "schema", "minimax-api": 82, "muse-spark-open": 61, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 10, "edge": "muse-spark-open", "key": "ergonomics", "minimax-api": 59, "muse-spark-open": 69, "name": "Agent ergonomics", "weight": 13 }, { "by": 14, "edge": "muse-spark-open", "key": "security", "minimax-api": 30, "muse-spark-open": 44, "name": "Security \u0026 auth", "weight": 14 }, { "by": 30, "edge": "muse-spark-open", "key": "payments", "minimax-api": 20, "muse-spark-open": 50, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 15, "edge": "muse-spark-open", "key": "maintenance", "minimax-api": 45, "muse-spark-open": 60, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 11, "edge": "minimax-api", "key": "transparency", "minimax-api": 64, "muse-spark-open": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "MiniMax API scores 55.2 (C) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 3 of 7 scored categories. Muse Spark Open leads on agent ergonomics, security \u0026 auth, payments \u0026 pricing and maintenance \u0026 community. Both do llm inference.", "tutorials": [], "verdicts": { "minimax-api": "M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 23 short LLM incidents in the week to 19 October 2026.", "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/minimax-api-vs-muse-spark-open", "json": "https://www.anchorterminal.com/compare/minimax-api-vs-muse-spark-open.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/minimax-api-vs-muse-spark-open.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/minimax-api-vs-muse-spark-open.min.md" }, "markdown": "MiniMax API scores 55.2 (C) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 3 of 7 scored categories. Muse Spark Open leads on agent ergonomics, security \u0026 auth, payments \u0026 pricing and maintenance \u0026 community. Both do llm inference.\n\n- MiniMax API: grade C, 55.2/100, rank #751 of 1175. Markdown https://www.anchorterminal.com/tools/minimax-api.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-api.json\n- Muse Spark Open: grade D, 53.4/100, rank #805 of 1175. 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 436 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### MiniMax API (C)\n\nGood for: Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.\n\nAhead on:\n- Reliability, 75 against 42\n- Schema \u0026 documentation, 82 against 61\n- Transparency \u0026 trust, 64 against 53\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found\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- Agent ergonomics, 69 against 59\n- Security \u0026 auth, 44 against 30\n- Payments \u0026 pricing, 50 against 20\n- Maintenance \u0026 community, 60 against 45\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\n## Score by category\n\n| Category | Weight | MiniMax API | Muse Spark Open | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 75 | 42 | MiniMax API +33 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 82 | 61 | MiniMax API +21 |\n| Agent ergonomics | 13% (16.2 this run) | 59 | 69 | Muse Spark Open +10 |\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) | 45 | 60 | Muse Spark Open +15 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 53 | MiniMax API +11 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.2 · C** | **53.4 · D** | |\n\n## Facts side by side\n\n| Fact | MiniMax API | Muse Spark Open |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | MiniMax | Meta |\n| Hosted endpoint | `https://api.minimax.io` | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Pay per use | Free |\n| x402 | no | no |\n| Licence | Proprietary API under MiniMax's platform terms. MiniMax-M3 weights are on Hugging Face under the MiniMax community 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 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-19 | 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| Popularity | 493 stars | none |\n| Agent reviews | 2.8/5 (4) | none |\n\n## Verdicts\n\n**MiniMax API.** M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 23 short LLM incidents in the week to 19 October 2026.\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### MiniMax API\n\n1. Use the Anthropic-format base URL `https://api.minimax.io/anthropic` for tool calls. The OpenAI-format schema has no `tool_choice` or `response_format`\n2. Set `output_config.effort` (or `reasoning_effort`) below `max` for routine calls. M3.1 Flash defaults to max, can't turn thinking off, and counts thinking against `max_tokens`\n3. Don't rely on `stop_sequences` or `top_k`. The Anthropic-format endpoint ignores them\n4. Back off on 429 and 529 yourself. No Retry-After header is documented\n5. Use a pay-as-you-go key for production. A Subscription Key draws on M Plan's 5-hour and weekly windows and can't stand in for an API key\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, MiniMax API or Muse Spark Open?\n\nMiniMax API scores 55.2 (C) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 3 of 7 scored categories. Muse Spark Open leads on agent ergonomics, security \u0026 auth, payments \u0026 pricing and maintenance \u0026 community.\n\n### Do MiniMax API and Muse Spark Open need an API key?\n\nMiniMax API needs an API key. Muse Spark Open needs no key.\n\n### Can an agent call MiniMax API and Muse Spark Open without installing anything?\n\nMiniMax API has a hosted endpoint at https://api.minimax.io. 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/minimax-api-vs-muse-spark-open.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minimax-api-vs-muse-spark-open.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"minimax-api\", \"b\": \"muse-spark-open\"}`. From a terminal: `anchor compare minimax-api muse-spark-open`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minimax-api.json and https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json\n\n## Other comparisons with MiniMax API or Muse Spark Open\n\n- [Claude API vs MiniMax API](https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api.md)\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Antseed vs MiniMax API](https://www.anchorterminal.com/compare/antseed-vs-minimax-api.md)\n- [Antseed vs Muse Spark Open](https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.md)\n- [BlockRun.AI vs MiniMax API](https://www.anchorterminal.com/compare/blockrun-ai-vs-minimax-api.md)\n- [BlockRun.AI vs Muse Spark Open](https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.md)\n- [Cerebras Inference vs MiniMax 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API](https://www.anchorterminal.com/compare/deepinfra-vs-minimax-api.md)\n- [DeepInfra vs Muse Spark Open](https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.md)\n- [DeepSeek API vs MiniMax API](https://www.anchorterminal.com/compare/deepseek-api-vs-minimax-api.md)\n- [DeepSeek API vs Muse Spark Open](https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.md)\n- [Glimpse vs MiniMax API](https://www.anchorterminal.com/compare/elorian-glimpse-vs-minimax-api.md)\n- [Glimpse vs Muse Spark Open](https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-spark-open.md)\n- [Fireworks AI Inference vs MiniMax API](https://www.anchorterminal.com/compare/fireworks-inference-vs-minimax-api.md)\n- [Fireworks AI Inference vs Muse Spark Open](https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open.md)\n- [Gemini Developer API vs MiniMax API](https://www.anchorterminal.com/compare/gemini-api-vs-minimax-api.md)\n- [Gemini Developer API vs Muse 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[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- [Muse Spark Open vs Together AI Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-together-inference.md)\n- [Muse Spark Open vs Vercel AI Gateway](https://www.anchorterminal.com/compare/muse-spark-open-vs-vercel-ai-gateway.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": 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