{ "data": { "a": { "slug": "inkling-2-small", "name": "Inkling 2 Small", "vendor": "Thinking Machines Lab", "vendorUrl": "https://thinkingmachines.ai", "kind": "model", "category": "inference", "summary": "Inkling 2 Small is Thinking Machines Lab's mixture-of-experts model, 594B total and 17B active parameters, taking text and images and returning text. It runs on Tinker for inference and fine-tuning, with open weights promised.", "url": "https://www.anchorterminal.com/tools/inkling-2-small", "markdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json", "dns": "inkling-2-small.grade.anchorterminal.com", "license": "Proprietary for now, used through Tinker under the Tinker Terms of Use and Thinking Machines' Model Acceptable Use Policy, per the model card. Thinking Machines says it will publish the weights under Apache 2.0 the week after launch, once outside safety testing is done", "transports": [], "remoteUrl": "https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1", "packages": [], "auth": "api-key", "authNotes": "A Tinker API key from the Tinker console, read from TINKER_API_KEY and passed as the OpenAI client's api_key on the OpenAI-compatible endpoint, or used by the Tinker Python SDK. Sign-up is a browser flow at auth.thinkingmachines.ai, and the quickstart asks for payment details in Billing before training, per the tinker listing.", "pricing": "usage", "pricingNotes": "Serverless inference (beta) is $0.30 per million input tokens, $0.03 cached and $1.00 output, at 256K context. On the training side prefill is the same $0.30, sampling $1.00, and training $1.50 per million at 64K or $3.00 at 256K. No free tier is listed (checked 2026-11-06).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on Tinker's models and pricing page or its OpenAI-compatible API page, and Tinker bills against an account with payment details (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-06" }, "docsUrl": "https://thinkingmachines.ai/model-card/inkling-2-small/", "llmsTxt": "https://tinker-docs.thinkingmachines.ai/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "moe", "multimodal", "vision", "reasoning", "openai-compatible", "usage-priced", "card-required", "beta", "llms-txt", "new" ], "lastRelease": "2026-11-05", "graded": true, "anchor": { "graded": true, "score": 52.1, "grade": "D", "agentReady": false, "rank": 1001, "ranked": true, "rankOf": 1515, "categoryRank": 35, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 62, "maintenance": 75, "payments": 20, "reliability": 30, "schema": 70, "security": 57, "transparency": 64 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "A new multimodal mixture-of-experts model from Thinking Machines, callable today through Tinker's OpenAI-compatible endpoint at $0.30 and $1.00 per million tokens, with strong vendor-reported coding and agent scores. Tinker's serverless inference is beta, with no status page or SLA, and the weights aren't public yet.", "bestFor": "Developers who want a capable multimodal open-family model through an OpenAI-compatible API today, or to fine-tune it on Tinker, and who can live with a beta surface until the weights are published.", "strengths": [ "OpenAI-compatible chat and completions endpoint, so the OpenAI SDKs work with a Tinker key", "$0.30 input, $0.03 cached and $1.00 output per million tokens, published without a login", "Text and image input, a 256K context on Tinker and up to 1M per the model card", "reasoning_effort from none to xhigh or a number, with reasoning returned separately", "A model card with intended use, limitations, training data sources and safety testing that includes outside red-teaming", "Thinking Machines says Apache 2.0 weights follow a week after launch" ], "weaknesses": [ "Serverless inference and the OpenAI-compatible API are both labelled beta, with a waitlist for higher throughput", "No status page, SLA or published rate limits for serverless inference", "Tool-calling format and structured output aren't documented for this model", "No free tier, and sign-up is a browser flow with payment details", "Benchmark results are Thinking Machines' own, with no independent results yet" ], "agentNotes": [ "Call https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1 with an OpenAI client and TINKER_API_KEY, using /chat/completions", "The serverless model ID is thinkingmachines/Inkling-2-Small:peft:262144:sampling-nvfp4, per Tinker's pricing page. The OpenAI page's examples use your own checkpoint paths, so confirm it before relying on it", "Pass reasoning_effort as none to xhigh or 0.0 to 0.99 (default 0.9); reasoning arrives in reasoning_content unless separate_reasoning is false", "Keep images between 40 and 4096 px a side, per the model card", "Validate JSON yourself, since structured output and the tool-call format aren't documented", "Plan for a move to open weights. When they publish, the open-weights listing will carry sizes and runtimes" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.1 } ], "editorialScores": { "ergonomics": 62, "maintenance": 75, "payments": 20, "reliability": 30, "schema": 70, "security": 57, "transparency": 60 }, "provenanceScore": 68, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1/chat/completions \\\n -H \"Authorization: Bearer $TINKER_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"thinkingmachines/Inkling-2-Small:peft:262144:sampling-nvfp4\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n \"reasoning_effort\": \"low\"\n }'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/inkling-2-small" }, "sameCompany": [ "inkling", "inkling-small" ], "sameModel": [ "tinker" ], "area": "models", "provenance": { "legalEntity": "Thinking Machines Lab, Inc. (named as provider on the model card)", "domain": "thinkingmachines.ai", "domainRegistered": "", "domainNote": "Not looked up: RDAP isn't requested under the 1 November 2026 rules.", "endpointOnVendorDomain": true, "terms": "https://thinkingmachines.ai/legal/terms/", "privacy": "https://thinkingmachines.ai/legal/privacy/", "statusPage": "", "changelog": "https://tinker-docs.thinkingmachines.ai/changelog/", "securityTxt": "valid", "checked": "2026-11-06", "notes": [ "The launch post and model card are on thinkingmachines.ai and name Thinking Machines Lab, Inc. as provider. The OpenAI-compatible endpoint is on thinkingmachines.dev, which Tinker's own docs give as the production base URL, so it's read as a domain the vendor controls; its registration wasn't looked up.", "Thinking Machines' terms bar scraping the Services, which the 4 November re-check read as a ban and paused. The founder decided on 6 November 2026 that reading at a person's pace is fine, so four pages were read one at a time: the launch post, the model card, the models and pricing page and the OpenAI-compatible API page. tinker-docs.thinkingmachines.ai has no robots.txt; thinkingmachines.ai's has no rules.", "security.txt lists security-reports@thinkingmachines.ai and expires 2029-07-13, per the 2 November reading.", "No status page was found." ], "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-2-small.json", "live": { "slug": "inkling-2-small", "probe": { "target": "https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1", "method": "get", "lastAt": "2026-11-09T20:49:56.005739467Z", "lastOk": true, "lastStatus": 404, "lastMs": 405, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 413, "p95ms24h": 489, "samples24h": 244, "samples30d": 884, "days": [ { "date": "2026-11-06", "probes": 186, "ok": 186 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 243, "ok": 243 }, { "date": "2026-11-09", "probes": 212, "ok": 212 } ], "since": "2026-11-06T00:00:00Z" }, "securityTxt": { "url": "https://thinkingmachines.ai/.well-known/security.txt", "state": "valid", "expires": "2029-07-13T07:00:00.000Z", "checkedAt": "2026-11-09T16:06:03.245615664Z" }, "llmsTxt": { "url": "https://tinker-docs.thinkingmachines.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-09T15:39:48.124098616Z" }, "domain": { "domain": "thinkingmachines.ai", "registered": "2024-07-09", "source": "https://rdap.identitydigital.services/rdap/domain/thinkingmachines.ai", "checkedAt": "2026-11-08T15:05:10.558189316Z" }, "pages": [ { "url": "https://tinker-docs.thinkingmachines.ai/changelog/", "kind": "changelog", "status": 200, "checkedAt": "2026-11-09T15:53:07.734989467Z", "changedAt": "2026-11-07T14:22:17.310423056Z", "fingerprint": "a3a2317910fe" }, { "url": "https://thinkingmachines.ai/legal/privacy/", "kind": "privacy", "status": 200, "checkedAt": "2026-11-09T15:53:04.532396634Z", "changedAt": "2026-11-06T13:43:40.660240815Z", "fingerprint": "3c33a4a74c61" }, { "url": "https://thinkingmachines.ai/legal/terms/", "kind": "terms", "status": 200, "checkedAt": "2026-11-09T15:53:06.78701967Z", "changedAt": "2026-11-06T13:43:42.918165055Z", "fingerprint": "08c6ceca5dbb" } ], "updatedAt": "2026-11-09T20:49:56.005739467Z" }, "streak": { "days": 3, "from": "2026-11-06", "sinceWatching": true, "best": 3 } }, "answer": "Inkling 2 Small and Muse Ember score within a point of each other on agent readiness, 52.1 (D) and 51.8 (D). Muse Ember leads on reliability, agent ergonomics and security \u0026 auth.", "b": { "slug": "muse-ember", "name": "Muse Ember", "vendor": "Meta", "vendorUrl": "https://dev.meta.ai", "kind": "model", "category": "inference", "summary": "Muse Ember is Meta's smallest and most efficient hosted model, built for sub-agent tasks, tool calls, routing and work over large collections of files and images, taking text, images, video, audio and PDF with a 1M-token context.", "url": "https://www.anchorterminal.com/tools/muse-ember", "markdownUrl": "https://www.anchorterminal.com/tools/muse-ember.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/muse-ember.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/muse-ember.json", "dns": "muse-ember.grade.anchorterminal.com", "license": "Closed model, used through Meta Model API and Muse Code under the Meta Model API Terms of Service (last updated 9 October 2026). No open weights; Meta's open-weight models are Muse Spark Open and Muse Glimmer", "transports": [], "remoteUrl": "https://api.meta.ai/v1", "packages": [], "auth": "api-key", "authNotes": "A bearer key from the API keys tab of the Model API dashboard, read from MODEL_API_KEY in Meta's examples, after a browser sign-up with email, mobile number, Facebook, Google or GitHub. Keys belong to a team and share its limits, with no scopes found, per the meta-model-api listing.", "pricing": "usage", "pricingNotes": "$0.10 per million input tokens, $0.004 cached and $0.50 output for requests up to 200K input tokens, and $0.30, $0.012 and $1.50 for the whole request above that. Standard mode only, no Contributor discount. Web search grounding $2.50 per 1,000 queries. Included in every Muse Code plan. No free API allowance found (checked 2026-11-09).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on Meta's pricing page, which bills tokens to a team account with a card (checked 2026-11-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-09" }, "docsUrl": "https://dev.meta.ai/docs/muse-ember", "llmsTxt": "https://dev.meta.ai/llms.txt", "capabilities": [ "inference.llm" ], "tags": [ "official", "hosted", "model", "multimodal", "vision", "reasoning", "long-context", "tool-calling", "openai-compatible", "anthropic-compatible", "usage-priced", "card-required", "closed-source", "llms-txt", "new" ], "lastRelease": "2026-11-09", "graded": true, "anchor": { "graded": true, "score": 51.8, "grade": "D", "agentReady": false, "rank": 1017, "ranked": true, "rankOf": 1515, "categoryRank": 36, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 72, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-09" }, "negative": 0, "verdict": "A cheap, capable model for the repeated parts of agent work, at $0.10 and $0.50 per million tokens with a 1M context and Meta's figures putting it level with Claude Haiku 5.5 on fewer tokens. Launched today on an API with no readable status page, SLA or deprecation policy, and closed, with no weights.", "bestFor": "Agents that hand out many small, bounded tasks (sub-agents, tool loops, routing, extraction over thousands of files) and want a cheap multimodal model with a 1M context behind the same API as a bigger Muse model.", "strengths": [ "$0.10 input, $0.004 cached and $0.50 output per million tokens up to 200K input, published without a login", "Text, image, video, audio and PDF in, a 1,048,576-token context and up to 524,288 output tokens", "The same request body as Muse Spark and Muse Wonder on Responses, Chat Completions and Messages endpoints", "Tool calling, structured output, computer use and search grounding", "Reasoning effort from minimal to max, with clear guidance on what to hand it and what not to", "3,000 requests and 4,000,000 tokens a minute per team, published" ], "weaknesses": [ "No weights and no parameter count published, so it can't be run locally", "Requests over 200K input tokens are billed at three times the rate for the whole request", "Default reasoning effort is max, which spends output tokens on simple routing calls unless set lower", "No readable status page, SLA, deprecation policy or API changelog, per the meta-model-api listing", "Benchmark and cost figures are Meta's own, several on internal benchmarks" ], "agentNotes": [ "Call https://api.meta.ai/v1/responses (or /chat/completions or /messages) with model muse-ember-1.0 and a bearer MODEL_API_KEY", "Set the effort explicitly, reasoning.effort on Responses or reasoning_effort on Chat Completions. It defaults to max, and none isn't accepted; minimal or low suits classification and routing", "Keep input under 200K tokens a request, cached tokens and previous_response_id history included, or the whole request bills at the long-context rate", "Use it for sub-agents and bounded repeated tasks, and a larger Muse model for the plan, as Meta advises", "Use strict structured output for extraction and routing steps", "In Claude Code, map the haiku alias and sub-agent model to muse-ember-1.0, per Meta's guide" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 51.8 } ], "editorialScores": { "ergonomics": 72, "maintenance": 46, "payments": 20, "reliability": 40, "schema": 60, "security": 64, "transparency": 41 }, "provenanceScore": 64, "checked": { "categories": { "ergonomics": "2026-11-09", "maintenance": "2026-11-09", "payments": "2026-11-09", "reliability": "2026-11-09", "schema": "2026-11-09", "security": "2026-11-09", "transparency": "2026-11-09" }, "last": "2026-11-09", "oldest": "2026-11-09", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl -X POST \"https://api.meta.ai/v1/responses\" \\\n -H \"Authorization: Bearer $MODEL_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"muse-ember-1.0\",\n \"input\": \"Classify this support ticket as billing, bug, or feature request.\",\n \"reasoning\": {\"effort\": \"low\"}\n}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/muse-ember" }, "sameCompany": [ "muse-spark-open", "muse-code", "muse-glimmer-30b" ], "sameModel": [ "meta-model-api" ], "area": "models", "unitPrices": [ { "item": "Muse Ember input", "unit": "1m-tokens", "usd": 0.1, "note": "Up to 200K input tokens a request; $0.30 above, for the whole request" }, { "item": "Muse Ember cached input", "unit": "1m-tokens", "usd": 0.004, "note": "$0.012 above 200K input tokens" }, { "item": "Muse Ember output", "unit": "1m-tokens", "usd": 0.5, "note": "$1.50 above 200K input tokens" } ], "provenance": { "legalEntity": "Meta Platforms, Inc.", "domain": "meta.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": true, "terms": "https://dev.meta.ai/legal/terms-of-service", "privacy": "https://www.facebook.com/privacy/policy/", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-09", "notes": [ "Company and platform facts are the meta-model-api listing's (checked 4 November 2026): Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, under the 9 October 2026 terms; no readable status page; no Model API changelog; no security.txt on dev.meta.ai.", "dev.meta.ai's and research.meta.ai's robots.txt allow our reader on the pages read on 9 November. domainRegistered is carried from the meta-model-api listing's RDAP reading." ], "score": 64 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/muse-ember.json", "live": { "slug": "muse-ember", "probe": { "target": "https://api.meta.ai/v1", "method": "get", "lastAt": "2026-11-09T20:50:02.257490788Z", "lastOk": true, "lastStatus": 404, "lastMs": 46, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 48, "p95ms24h": 72, "samples24h": 10, "samples30d": 10, "days": [ { "date": "2026-11-09", "probes": 10, "ok": 10 } ], "since": "2026-11-09T19:55:51.172718582Z" }, "updatedAt": "2026-11-09T20:50:02.257490788Z" }, "streak": { "days": 0, "from": "2026-11-09", "sinceWatching": true, "best": 0 } }, "edges": [ { "by": 29, "category": "maintenance", "leads": "inkling-2-small", "name": "Maintenance \u0026 community", "reasons": { "a": "Model reading. Released 5 November 2026 (30). Churn and notice in place of release counts: Inkling, Inkling-Small (30 July) and Inkling 2 Small in about four months, and a deprecations page with dated retirements and a promise to 'aim to give advance notice' by email, with no stated period, per the tinker listing (10 of 20). A public changelog and a support address and Discord, per the tinker listing (10 of 15). Current official SDKs, Tinker's Python SDK and the OpenAI-compatible endpoint (15). SDK and cookbook CI, per the tinker listing (10). 30 + 10 + 10 + 15 + 10 = 75.", "b": "Model reading. Released 9 November 2026 (30). No deprecation policy or notice period found, per the platform reading (0 of 12). Dated launches on the API, the latest Muse Wonder on 12 October and Muse Ember on 9 November (8 of 8). No Model API changelog; a help centre with tickets (8 of 15). No SDK of Meta's own (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46." }, "scores": { "a": 75, "b": 46 } }, { "by": 11, "category": "transparency", "leads": "inkling-2-small", "name": "Transparency \u0026 trust", "reasons": { "a": "Editorial half. Closed for now under the Tinker Terms of Use and the Model Acceptable Use Policy, per the model card, with Apache 2.0 weights promised the week after launch (15). Terms commit not to use Customer Content for training, keep it only as needed, with a DPA and deletion on request; the privacy notice wasn't re-read, per the tinker listing (15). Dated deprecation notices with no stated period (15). The DPA annex names Google Cloud, Cloudflare, WorkOS and OpenAI with service and location (15). 15 + 15 + 15 + 15 = 60.", "b": "Editorial half. Closed model under the Model API terms, with clear terms and law; no weights and no parameter count, unlike Muse Spark Open and Muse Glimmer (15). Standard content isn't used for training, retention periods not stated outside zero retention (18 of 30). No deprecation policy or dated notices (0). A subprocessor list linked but not read, no data locations (8 of 20). 15 + 18 + 0 + 8 = 41." }, "scores": { "a": 64, "b": 53 } }, { "by": 10, "category": "reliability", "leads": "muse-ember", "name": "Reliability", "reasons": { "a": "Model reading, for the surface it's called on, Tinker's serverless inference and OpenAI-compatible API. No status page found, per the tinker listing's checks of 1 October and 4 November (0), so no readable incident history (5). The only published limit is the in-flight sample cap of 2,000, per the tinker listing's 1 October check; the OpenAI-compatible page gives no numbers and says higher or more stable throughput needs the waitlist (10). The SDK retries sampling with stable request IDs, per the tinker listing's reading of the SDK repository; the OpenAI-compatible page has no retry guidance (15). No SLA found (0). Serverless inference is 'currently in beta' on the models and pricing page and the OpenAI-compatible API is labelled Beta, read 6 November (0). 0 + 5 + 10 + 15 + 0 + 0 = 30.", "b": "Model reading, for the surface it's called on, Meta Model API. No status page with readable history, per the meta-model-api listing's 4 November check (0), so no readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-ember-1.0, read 9 November (15). 429 and 503 with Retry-After, backoff guidance and rate-limit headers, per the meta-model-api listing (15). No SLA found (0). Muse Ember carries no preview label, but the API opened as a public preview in July and no general-availability notice was found, so half, as for the platform (5). 0 + 5 + 15 + 15 + 0 + 5 = 40." }, "scores": { "a": 30, "b": 40 } }, { "by": 10, "category": "schema", "leads": "inkling-2-small", "name": "Schema \u0026 documentation", "reasons": { "a": "Model reading. No OpenAPI file of its own; the OpenAI-compatible chat and completions endpoints and the typed Python SDK are the contract, as the tinker listing reads it (15). llms.txt on the docs host, per the tinker listing's 1 October check (10). The model card states intended use (agentic and tool-use systems, coding assistants, chatbots, RAG), inputs, outputs and limitations, and the launch post its benchmarks (16 of 20). Model IDs, context lengths and the reasoning_effort values (none to xhigh, or 0.0 to 0.99) are documented; the tool-call format and structured output aren't, for this model (8 of 15). A Python example and an HTTP 400 for models without reasoning_effort, with no error page (6 of 15). A dated Tinker changelog and a model deprecations page, per the tinker listing (15). 15 + 10 + 16 + 8 + 6 + 15 = 70.", "b": "Model reading. No OpenAPI file; the Markdown reference is the contract, per the meta-model-api listing (0). llms.txt and Markdown copies of every page (10). The Muse Ember page and choose-a-model page say what to hand it and what not to (hard single-shot coding, knowledge-heavy questions, visual coding), with model ID, inputs, context, max output and effort range (18 of 20). JSON Schema tools and output, reasoning effort an enum, per the platform reading (12 of 15). Curl, Python and TypeScript examples and the platform's error guide (15). A versioned model ID and a dated launch post, with no API changelog (5 of 15). 0 + 10 + 18 + 12 + 15 + 5 = 60." }, "scores": { "a": 70, "b": 60 } }, { "by": 10, "category": "ergonomics", "leads": "muse-ember", "name": "Agent ergonomics", "reasons": { "a": "Model reading (tool use, structured output, caching, context, batch, SDKs). A 256K served context, max_tokens and a priced cache at $0.03 per million; tool use isn't documented for this model (15 of 25). Output-size controls through max_tokens, reasoning_effort and separate_reasoning (15 of 20). One documented error, the 400 for unsupported reasoning_effort (5 of 20). Stable request IDs make SDK sampling retries safe, per the tinker listing (15 of 20). OpenAI's SDKs work against the endpoint, with Tinker's Python SDK besides, and reasoning defaults to 0.9 (12 of 15). 15 + 15 + 5 + 15 + 12 = 62.", "b": "Model reading. Tool calls, parallel calls, computer use and search grounding, with tool_choice limited to auto per the platform reading (15 of 20). Strict structured output (15). Automatic prompt caching, cached input at 4% of the input price (15). A 1,048,576-token context, but requests over 200K input tokens bill at three times the rate for the whole request (12 of 15). No batch endpoint (0). No SDK of Meta's own; OpenAI and Anthropic SDKs against compatible endpoints (0). OpenAI-style errors with fixes and retryable codes (15). 15 + 15 + 15 + 12 + 0 + 0 + 15 = 72." }, "scores": { "a": 62, "b": 72 } }, { "by": 7, "category": "security", "leads": "muse-ember", "name": "Security \u0026 auth", "reasons": { "a": "Platform readings are the tinker listing's. Revocable API keys from the console, with no per-key scopes found (20). Org, team and project permissions with no read-only role (5). The model returns its own completions, no third-party content (10). get_audit_log() for admins (15). security.txt with a reporting address and no stated acknowledgement time (7). For the model reading, Tinker's terms commit not to use Customer Content for training, recorded under transparency. 20 + 5 + 10 + 15 + 7 = 57.", "b": "Platform readings are the meta-model-api listing's of 4 November. Team keys, named, revocable, no scopes (20 of 30). Standard mode only, so content isn't used to train Meta models under the terms, with safety use reserved (17 of 20). Retention 'as needed' with zero retention through sales (10 of 15). Usage dashboard by model, no per-call log (5 of 15). No security.txt on dev.meta.ai, a bug bounty and a security commitments page, no named certification (12 of 20). 20 + 17 + 10 + 5 + 12 = 64." }, "scores": { "a": 57, "b": 64 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Thinking Machines Lab", "b": "Meta", "name": "Vendor" }, { "a": "https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1", "b": "https://api.meta.ai/v1", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Pay per use", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary for now, used through Tinker under the Tinker Terms of Use and Thinking Machines' Model Acceptable Use Policy, per the model card. Thinking Machines says it will publish the weights under Apache 2.0 the week after launch, once outside safety testing is done", "b": "Closed model, used through Meta Model API and Muse Code under the Meta Model API Terms of Service (last updated 9 October 2026). No open weights; Meta's open-weight models are Muse Spark Open and Muse Glimmer", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-11-05", "b": "2026-11-09", "name": "Last release" }, { "a": "not read yet", "b": "2026-10-02", "name": "Terms last updated" }, { "a": "not read yet", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "yes", "name": "Customer content may train models" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "yes", "name": "Arbitration or class-action waiver" } ], "faq": [ { "answer": "Inkling 2 Small and Muse Ember score within a point of each other on agent readiness, 52.1 (D) and 51.8 (D). Muse Ember leads on reliability, agent ergonomics and security \u0026 auth.", "question": "Which is better for AI agents, Inkling 2 Small or Muse Ember?" }, { "answer": "Both need an API key.", "question": "Do Inkling 2 Small and Muse Ember need an API key?" }, { "answer": "Yes. Inkling 2 Small has a hosted endpoint at https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1 and Muse Ember at https://api.meta.ai/v1.", "question": "Can an agent call Inkling 2 Small and Muse Ember without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 70 against 60", "Maintenance \u0026 community, 75 against 46", "Transparency \u0026 trust, 64 against 53" ], "also": null, "goodFor": "Developers who want a capable multimodal open-family model through an OpenAI-compatible API today, or to fine-tune it on Tinker, and who can live with a beta surface until the weights are published.", "slug": "inkling-2-small", "watchFor": "Serverless inference and the OpenAI-compatible API are both labelled beta, with a waitlist for higher throughput" }, { "aheadOn": [ "Reliability, 40 against 30", "Agent ergonomics, 72 against 62", "Security \u0026 auth, 64 against 57" ], "also": null, "goodFor": "Agents that hand out many small, bounded tasks (sub-agents, tool loops, routing, extraction over thousands of files) and want a cheap multimodal model with a 1M context behind the same API as a bigger Muse model.", "slug": "muse-ember", "watchFor": "No weights and no parameter count published, so it can't be run locally" } ], "history": null, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small.json", "title": "Amazon Bedrock vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember.json", "title": "Amazon Bedrock vs Muse Ember", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small.json", "title": "Claude API vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.json", "title": "Claude API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-inkling-2-small.json", "title": "Antseed vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/antseed-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-muse-ember.json", "title": "Antseed vs Muse Ember", "url": "https://www.anchorterminal.com/compare/antseed-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small.json", "title": "Azure OpenAI in Foundry Models vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/azure-openai-vs-muse-ember.json", "title": "Azure OpenAI in Foundry Models vs Muse Ember", "url": "https://www.anchorterminal.com/compare/azure-openai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-inkling-2-small.json", "title": "BlockRun.AI vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-ember.json", "title": "BlockRun.AI vs Muse Ember", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-inkling-2-small.json", "title": "Cerebras Inference vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-ember.json", "title": "Cerebras Inference vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-inkling-2-small.json", "title": "Cloudflare AI Gateway vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-ember.json", "title": "Cloudflare AI Gateway vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-inkling-2-small.json", "title": "Cloudflare Workers AI vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-ember.json", "title": "Cloudflare Workers AI vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-inkling-2-small.json", "title": "Cohere Chat API (Command models) vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-ember.json", "title": "Cohere Chat API (Command models) vs Muse Ember", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-inkling-2-small.json", "title": "DeepInfra vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-ember.json", "title": "DeepInfra vs Muse Ember", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-inkling-2-small.json", "title": "DeepSeek API vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-ember.json", "title": "DeepSeek API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small.json", "title": "Eden AI vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-ember.json", "title": "Eden AI vs Muse Ember", "url": "https://www.anchorterminal.com/compare/eden-ai-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-inkling-2-small.json", "title": "Glimpse vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember.json", "title": "Glimpse vs Muse Ember", "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-inkling-2-small.json", "title": "Fireworks AI Inference vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-ember.json", "title": "Fireworks AI Inference vs Muse Ember", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-inkling-2-small.json", "title": "Gemini Developer API vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-ember.json", "title": "Gemini Developer API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-inkling-2-small.json", "title": "GroqCloud vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/groq-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/groq-vs-muse-ember.json", "title": "GroqCloud vs Muse Ember", "url": "https://www.anchorterminal.com/compare/groq-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-inkling-2-small.json", "title": "Hugging Face Inference Providers vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-ember.json", "title": "Hugging Face Inference Providers vs Muse Ember", "url": "https://www.anchorterminal.com/compare/hugging-face-inference-providers-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-jais-3.json", "title": "Inkling 2 Small vs Jais 3", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-meta-model-api.json", "title": "Inkling 2 Small vs Meta Model API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-api.json", "title": "Inkling 2 Small vs MiniMax API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mistral-api.json", "title": "Inkling 2 Small vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-spark-open.json", "title": "Inkling 2 Small vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-super-vl.json", "title": "Inkling 2 Small vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-novita-ai.json", "title": "Inkling 2 Small vs Novita AI", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-openai-api.json", "title": "Inkling 2 Small vs OpenAI API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-openrouter.json", "title": "Inkling 2 Small vs OpenRouter", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-prism-inference.json", "title": "Inkling 2 Small vs Prism Inference", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ramp-router.json", "title": "Inkling 2 Small vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam.json", "title": "Inkling 2 Small vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-routerplus.json", "title": "Inkling 2 Small vs RouterPlus", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sambanova.json", "title": "Inkling 2 Small vs SambaCloud", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-siliconflow.json", "title": "Inkling 2 Small vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-simplismart.json", "title": "Inkling 2 Small vs Simplismart", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-stepfun-api.json", "title": "Inkling 2 Small vs StepFun API", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swe-2-flash.json", "title": "Inkling 2 Small vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-tencent-tokenhub.json", "title": "Inkling 2 Small vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-together-inference.json", "title": "Inkling 2 Small vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vercel-ai-gateway.json", "title": "Inkling 2 Small vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai.json", "title": "Inkling 2 Small vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-xai-api.json", "title": "Inkling 2 Small vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-xai-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-muse-ember.json", "title": "Jais 3 vs Muse Ember", "url": "https://www.anchorterminal.com/compare/jais-3-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-ember.json", "title": "Meta Model API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-muse-ember.json", "title": "MiniMax API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-ember.json", "title": "Mistral AI API vs Muse Ember", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-muse-ember" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-muse-spark-open.json", "title": "Muse Ember vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-nemotron-3-5-super-vl.json", "title": "Muse Ember vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-novita-ai.json", "title": "Muse Ember vs Novita AI", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-openai-api.json", "title": "Muse Ember vs OpenAI API", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-openrouter.json", "title": "Muse Ember vs OpenRouter", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-prism-inference.json", "title": "Muse Ember vs Prism Inference", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-ramp-router.json", "title": "Muse Ember vs Router.com (Ramp Router)", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-ramp-router" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam.json", "title": "Muse Ember vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-routerplus.json", "title": "Muse Ember vs RouterPlus", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-sambanova.json", "title": "Muse Ember vs SambaCloud", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-siliconflow.json", "title": "Muse Ember vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-simplismart.json", "title": "Muse Ember vs Simplismart", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-simplismart" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api.json", "title": "Muse Ember vs StepFun API", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-swe-2-flash.json", "title": "Muse Ember vs SWE-2 Flash", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-swe-2-flash" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-tencent-tokenhub.json", "title": "Muse Ember vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-together-inference.json", "title": "Muse Ember vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-vercel-ai-gateway.json", "title": "Muse Ember vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-vertex-ai.json", "title": "Muse Ember vs Vertex AI (Gemini Enterprise Agent Platform)", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-vertex-ai" }, { "json": "https://www.anchorterminal.com/compare/muse-ember-vs-xai-api.json", "title": "Muse Ember vs xAI API (Grok)", "url": "https://www.anchorterminal.com/compare/muse-ember-vs-xai-api" } ], "panel": null, "scores": [ { "by": 10, "edge": "muse-ember", "inkling-2-small": 30, "key": "reliability", "muse-ember": 40, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 10, "edge": "inkling-2-small", "inkling-2-small": 70, "key": "schema", "muse-ember": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 10, "edge": "muse-ember", "inkling-2-small": 62, "key": "ergonomics", "muse-ember": 72, "name": "Agent ergonomics", "weight": 13 }, { "by": 7, "edge": "muse-ember", "inkling-2-small": 57, "key": "security", "muse-ember": 64, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "inkling-2-small": 20, "key": "payments", "muse-ember": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 29, "edge": "inkling-2-small", "inkling-2-small": 75, "key": "maintenance", "muse-ember": 46, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 11, "edge": "inkling-2-small", "inkling-2-small": 64, "key": "transparency", "muse-ember": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Inkling 2 Small and Muse Ember score within a point of each other on agent readiness, 52.1 (D) and 51.8 (D). Muse Ember leads on reliability, agent ergonomics and security \u0026 auth. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "inkling-2-small": "A new multimodal mixture-of-experts model from Thinking Machines, callable today through Tinker's OpenAI-compatible endpoint at $0.30 and $1.00 per million tokens, with strong vendor-reported coding and agent scores. Tinker's serverless inference is beta, with no status page or SLA, and the weights aren't public yet.", "muse-ember": "A cheap, capable model for the repeated parts of agent work, at $0.10 and $0.50 per million tokens with a 1M context and Meta's figures putting it level with Claude Haiku 5.5 on fewer tokens. Launched today on an API with no readable status page, SLA or deprecation policy, and closed, with no weights." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember", "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember.min.md" }, "markdown": "Inkling 2 Small and Muse Ember score within a point of each other on agent readiness, 52.1 (D) and 51.8 (D). Muse Ember leads on reliability, agent ergonomics and security \u0026 auth. Both do llm inference.\n\n- Inkling 2 Small: grade D, 52.1/100, rank #1001 of 1515. Markdown https://www.anchorterminal.com/tools/inkling-2-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json\n- Muse Ember: grade D, 51.8/100, rank #1017 of 1515. Markdown https://www.anchorterminal.com/tools/muse-ember.md · JSON https://www.anchorterminal.com/api/v1/tools/muse-ember.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 871 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Inkling 2 Small (D)\n\nGood for: Developers who want a capable multimodal open-family model through an OpenAI-compatible API today, or to fine-tune it on Tinker, and who can live with a beta surface until the weights are published.\n\nAhead on:\n- Schema \u0026 documentation, 70 against 60\n- Maintenance \u0026 community, 75 against 46\n- Transparency \u0026 trust, 64 against 53\n\nWatch for: Serverless inference and the OpenAI-compatible API are both labelled beta, with a waitlist for higher throughput\n\n### Muse Ember (D)\n\nGood for: Agents that hand out many small, bounded tasks (sub-agents, tool loops, routing, extraction over thousands of files) and want a cheap multimodal model with a 1M context behind the same API as a bigger Muse model.\n\nAhead on:\n- Reliability, 40 against 30\n- Agent ergonomics, 72 against 62\n- Security \u0026 auth, 64 against 57\n\nWatch for: No weights and no parameter count published, so it can't be run locally\n\n\n## Why the edge\n\n### Maintenance \u0026 community: Inkling 2 Small +29\n\n- Inkling 2 Small (75): Model reading. Released 5 November 2026 (30). Churn and notice in place of release counts: Inkling, Inkling-Small (30 July) and Inkling 2 Small in about four months, and a deprecations page with dated retirements and a promise to 'aim to give advance notice' by email, with no stated period, per the tinker listing (10 of 20). A public changelog and a support address and Discord, per the tinker listing (10 of 15). Current official SDKs, Tinker's Python SDK and the OpenAI-compatible endpoint (15). SDK and cookbook CI, per the tinker listing (10). 30 + 10 + 10 + 15 + 10 = 75.\n- Muse Ember (46): Model reading. Released 9 November 2026 (30). No deprecation policy or notice period found, per the platform reading (0 of 12). Dated launches on the API, the latest Muse Wonder on 12 October and Muse Ember on 9 November (8 of 8). No Model API changelog; a help centre with tickets (8 of 15). No SDK of Meta's own (0 of 15, 0 of 10). 30 + 0 + 8 + 8 + 0 = 46.\n\n### Transparency \u0026 trust: Inkling 2 Small +11\n\n- Inkling 2 Small (64): Editorial half. Closed for now under the Tinker Terms of Use and the Model Acceptable Use Policy, per the model card, with Apache 2.0 weights promised the week after launch (15). Terms commit not to use Customer Content for training, keep it only as needed, with a DPA and deletion on request; the privacy notice wasn't re-read, per the tinker listing (15). Dated deprecation notices with no stated period (15). The DPA annex names Google Cloud, Cloudflare, WorkOS and OpenAI with service and location (15). 15 + 15 + 15 + 15 = 60.\n- Muse Ember (53): Editorial half. Closed model under the Model API terms, with clear terms and law; no weights and no parameter count, unlike Muse Spark Open and Muse Glimmer (15). Standard content isn't used for training, retention periods not stated outside zero retention (18 of 30). No deprecation policy or dated notices (0). A subprocessor list linked but not read, no data locations (8 of 20). 15 + 18 + 0 + 8 = 41.\n\n### Reliability: Muse Ember +10\n\n- Inkling 2 Small (30): Model reading, for the surface it's called on, Tinker's serverless inference and OpenAI-compatible API. No status page found, per the tinker listing's checks of 1 October and 4 November (0), so no readable incident history (5). The only published limit is the in-flight sample cap of 2,000, per the tinker listing's 1 October check; the OpenAI-compatible page gives no numbers and says higher or more stable throughput needs the waitlist (10). The SDK retries sampling with stable request IDs, per the tinker listing's reading of the SDK repository; the OpenAI-compatible page has no retry guidance (15). No SLA found (0). Serverless inference is 'currently in beta' on the models and pricing page and the OpenAI-compatible API is labelled Beta, read 6 November (0). 0 + 5 + 10 + 15 + 0 + 0 = 30.\n- Muse Ember (40): Model reading, for the surface it's called on, Meta Model API. No status page with readable history, per the meta-model-api listing's 4 November check (0), so no readable incident history (5). Rate limits published per team and per model, 3,000 RPM and 4,000,000 TPM for muse-ember-1.0, read 9 November (15). 429 and 503 with Retry-After, backoff guidance and rate-limit headers, per the meta-model-api listing (15). No SLA found (0). Muse Ember carries no preview label, but the API opened as a public preview in July and no general-availability notice was found, so half, as for the platform (5). 0 + 5 + 15 + 15 + 0 + 5 = 40.\n\n### Schema \u0026 documentation: Inkling 2 Small +10\n\n- Inkling 2 Small (70): Model reading. No OpenAPI file of its own; the OpenAI-compatible chat and completions endpoints and the typed Python SDK are the contract, as the tinker listing reads it (15). llms.txt on the docs host, per the tinker listing's 1 October check (10). The model card states intended use (agentic and tool-use systems, coding assistants, chatbots, RAG), inputs, outputs and limitations, and the launch post its benchmarks (16 of 20). Model IDs, context lengths and the reasoning_effort values (none to xhigh, or 0.0 to 0.99) are documented; the tool-call format and structured output aren't, for this model (8 of 15). A Python example and an HTTP 400 for models without reasoning_effort, with no error page (6 of 15). A dated Tinker changelog and a model deprecations page, per the tinker listing (15). 15 + 10 + 16 + 8 + 6 + 15 = 70.\n- Muse Ember (60): Model reading. No OpenAPI file; the Markdown reference is the contract, per the meta-model-api listing (0). llms.txt and Markdown copies of every page (10). The Muse Ember page and choose-a-model page say what to hand it and what not to (hard single-shot coding, knowledge-heavy questions, visual coding), with model ID, inputs, context, max output and effort range (18 of 20). JSON Schema tools and output, reasoning effort an enum, per the platform reading (12 of 15). Curl, Python and TypeScript examples and the platform's error guide (15). A versioned model ID and a dated launch post, with no API changelog (5 of 15). 0 + 10 + 18 + 12 + 15 + 5 = 60.\n\n### Agent ergonomics: Muse Ember +10\n\n- Inkling 2 Small (62): Model reading (tool use, structured output, caching, context, batch, SDKs). A 256K served context, max_tokens and a priced cache at $0.03 per million; tool use isn't documented for this model (15 of 25). Output-size controls through max_tokens, reasoning_effort and separate_reasoning (15 of 20). One documented error, the 400 for unsupported reasoning_effort (5 of 20). Stable request IDs make SDK sampling retries safe, per the tinker listing (15 of 20). OpenAI's SDKs work against the endpoint, with Tinker's Python SDK besides, and reasoning defaults to 0.9 (12 of 15). 15 + 15 + 5 + 15 + 12 = 62.\n- Muse Ember (72): Model reading. Tool calls, parallel calls, computer use and search grounding, with tool_choice limited to auto per the platform reading (15 of 20). Strict structured output (15). Automatic prompt caching, cached input at 4% of the input price (15). A 1,048,576-token context, but requests over 200K input tokens bill at three times the rate for the whole request (12 of 15). No batch endpoint (0). No SDK of Meta's own; OpenAI and Anthropic SDKs against compatible endpoints (0). OpenAI-style errors with fixes and retryable codes (15). 15 + 15 + 15 + 12 + 0 + 0 + 15 = 72.\n\n### Security \u0026 auth: Muse Ember +7\n\n- Inkling 2 Small (57): Platform readings are the tinker listing's. Revocable API keys from the console, with no per-key scopes found (20). Org, team and project permissions with no read-only role (5). The model returns its own completions, no third-party content (10). get_audit_log() for admins (15). security.txt with a reporting address and no stated acknowledgement time (7). For the model reading, Tinker's terms commit not to use Customer Content for training, recorded under transparency. 20 + 5 + 10 + 15 + 7 = 57.\n- Muse Ember (64): Platform readings are the meta-model-api listing's of 4 November. Team keys, named, revocable, no scopes (20 of 30). Standard mode only, so content isn't used to train Meta models under the terms, with safety use reserved (17 of 20). Retention 'as needed' with zero retention through sales (10 of 15). Usage dashboard by model, no per-call log (5 of 15). No security.txt on dev.meta.ai, a bug bounty and a security commitments page, no named certification (12 of 20). 20 + 17 + 10 + 5 + 12 = 64.\n\n## Score by category\n\n| Category | Weight | Inkling 2 Small | Muse Ember | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 30 | 40 | Muse Ember +10 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 70 | 60 | Inkling 2 Small +10 |\n| Agent ergonomics | 13% (16.2 this run) | 62 | 72 | Muse Ember +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 57 | 64 | Muse Ember +7 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 20 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 75 | 46 | Inkling 2 Small +29 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 64 | 53 | Inkling 2 Small +11 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **52.1 · D** | **51.8 · D** | |\n\n## Facts side by side\n\n| Fact | Inkling 2 Small | Muse Ember |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Thinking Machines Lab | Meta |\n| Hosted endpoint | `https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1` | `https://api.meta.ai/v1` |\n| Transports | | |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Proprietary for now, used through Tinker under the Tinker Terms of Use and Thinking Machines' Model Acceptable Use Policy, per the model card. Thinking Machines says it will publish the weights under Apache 2.0 the week after launch, once outside safety testing is done | Closed model, used through Meta Model API and Muse Code under the Meta Model API Terms of Service (last updated 9 October 2026). No open weights; Meta's open-weight models are Muse Spark Open and Muse Glimmer |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-11-05 | 2026-11-09 |\n| Terms last updated | not read yet | 2026-10-02 |\n| Privacy policy last updated | not read yet | couldn't be read |\n| Customer content may train models | not read yet | yes |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | yes |\n| Terms or service can change without notice | not read yet | not found in the text |\n| Arbitration or class-action waiver | not read yet | yes |\n\n## Verdicts\n\n**Inkling 2 Small.** A new multimodal mixture-of-experts model from Thinking Machines, callable today through Tinker's OpenAI-compatible endpoint at $0.30 and $1.00 per million tokens, with strong vendor-reported coding and agent scores. Tinker's serverless inference is beta, with no status page or SLA, and the weights aren't public yet.\n\n**Muse Ember.** A cheap, capable model for the repeated parts of agent work, at $0.10 and $0.50 per million tokens with a 1M context and Meta's figures putting it level with Claude Haiku 5.5 on fewer tokens. Launched today on an API with no readable status page, SLA or deprecation policy, and closed, with no weights.\n\n## Before you call either\n\n### Inkling 2 Small\n\n1. Call https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1 with an OpenAI client and TINKER_API_KEY, using /chat/completions\n2. The serverless model ID is thinkingmachines/Inkling-2-Small:peft:262144:sampling-nvfp4, per Tinker's pricing page. The OpenAI page's examples use your own checkpoint paths, so confirm it before relying on it\n3. Pass reasoning_effort as none to xhigh or 0.0 to 0.99 (default 0.9); reasoning arrives in reasoning_content unless separate_reasoning is false\n4. Keep images between 40 and 4096 px a side, per the model card\n5. Validate JSON yourself, since structured output and the tool-call format aren't documented\n6. Plan for a move to open weights. When they publish, the open-weights listing will carry sizes and runtimes\n\n### Muse Ember\n\n1. Call https://api.meta.ai/v1/responses (or /chat/completions or /messages) with model muse-ember-1.0 and a bearer MODEL_API_KEY\n2. Set the effort explicitly, reasoning.effort on Responses or reasoning_effort on Chat Completions. It defaults to max, and none isn't accepted; minimal or low suits classification and routing\n3. Keep input under 200K tokens a request, cached tokens and previous_response_id history included, or the whole request bills at the long-context rate\n4. Use it for sub-agents and bounded repeated tasks, and a larger Muse model for the plan, as Meta advises\n5. Use strict structured output for extraction and routing steps\n6. In Claude Code, map the haiku alias and sub-agent model to muse-ember-1.0, per Meta's guide\n\n## Questions\n\n### Which is better for AI agents, Inkling 2 Small or Muse Ember?\n\nInkling 2 Small and Muse Ember score within a point of each other on agent readiness, 52.1 (D) and 51.8 (D). Muse Ember leads on reliability, agent ergonomics and security \u0026 auth.\n\n### Do Inkling 2 Small and Muse Ember need an API key?\n\nBoth need an API key.\n\n### Can an agent call Inkling 2 Small and Muse Ember without installing anything?\n\nYes. Inkling 2 Small has a hosted endpoint at https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1 and Muse Ember at https://api.meta.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-2-small-vs-muse-ember.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling-2-small\", \"b\": \"muse-ember\"}`. From a terminal: `anchor compare inkling-2-small muse-ember`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json and https://www.anchorterminal.com/api/v1/tools/muse-ember.json\n\n## Other comparisons with Inkling 2 Small or Muse Ember\n\n- [Amazon Bedrock vs Inkling 2 Small](https://www.anchorterminal.com/compare/amazon-bedrock-vs-inkling-2-small.md)\n- [Amazon Bedrock vs Muse Ember](https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember.md)\n- [Claude API vs Inkling 2 Small](https://www.anchorterminal.com/compare/anthropic-api-vs-inkling-2-small.md)\n- [Claude API vs Muse Ember](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.md)\n- [Antseed vs Inkling 2 Small](https://www.anchorterminal.com/compare/antseed-vs-inkling-2-small.md)\n- [Antseed vs Muse Ember](https://www.anchorterminal.com/compare/antseed-vs-muse-ember.md)\n- [Azure OpenAI in Foundry Models vs Inkling 2 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TokenHub](https://www.anchorterminal.com/compare/muse-ember-vs-tencent-tokenhub.md)\n- [Muse Ember vs Together AI Inference](https://www.anchorterminal.com/compare/muse-ember-vs-together-inference.md)\n- [Muse Ember vs Vercel AI Gateway](https://www.anchorterminal.com/compare/muse-ember-vs-vercel-ai-gateway.md)\n- [Muse Ember vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/muse-ember-vs-vertex-ai.md)\n- [Muse Ember vs xAI API (Grok)](https://www.anchorterminal.com/compare/muse-ember-vs-xai-api.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": "2026-11-09", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": 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