{ "data": { "a": { "slug": "elorian-glimpse", "name": "Glimpse", "vendor": "Elorian", "vendorUrl": "https://elorian.ai/models.html", "kind": "model", "category": "inference", "summary": "Glimpse is Elorian's visual reasoning model, released as a research preview on 16 October 2026. It takes text, images and video and returns text, through Elorian's own API and chat app and through OpenRouter.", "url": "https://www.anchorterminal.com/tools/elorian-glimpse", "markdownUrl": "https://www.anchorterminal.com/tools/elorian-glimpse.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/elorian-glimpse.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/elorian-glimpse.json", "dns": "elorian-glimpse.grade.anchorterminal.com", "license": "Closed model and service under the Elorian AI, Inc. terms of service. Weights not released.", "transports": [ "http" ], "remoteUrl": "https://openrouter.ai/api/v1", "packages": [], "auth": "api-key", "authNotes": "On the graded route, an OpenRouter bearer key, created after a browser sign-up and drawing on prepaid credit. Together dedicated deployments use a Together API key. Elorian's own console sits behind a sign-in. No scopes were found.", "pricing": "usage", "pricingNotes": "$0.60 per million input tokens and $3.00 per million output tokens, Elorian's published rates (launch post, 16 October 2026). On OpenRouter the top-up fee applies. Together lists dedicated endpoints with pricing on request. Elorian says Glimpse can be tried free on its own platform, and volume access is through sales.", "priceSummary": "from $0.60 / 1M in", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in OpenRouter's docs as read on 17 October 2026, in Elorian's launch post or on Together's model page (checked 2026-11-04).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-17" }, "docsUrl": "https://openrouter.ai/elorian/glimpse", "capabilities": [ "inference.llm" ], "tags": [ "hosted", "model", "closed-source", "usage-priced", "prepaid", "multimodal", "video", "preview", "openai-compatible", "new" ], "lastRelease": "2026-10-16", "graded": true, "anchor": { "graded": true, "score": 35.1, "grade": "F", "agentReady": false, "rank": 1403, "ranked": true, "rankOf": 1515, "categoryRank": 42, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 20, "maintenance": 51, "payments": 25, "reliability": 23, "schema": 40, "security": 56, "transparency": 38 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-04" }, "negative": 0, "verdict": "Glimpse reads images and video at $0.60 input and $3.00 output per million tokens, through OpenRouter or a dedicated Together deployment. It is a research preview with no public Elorian docs, model card or status page, its context and tool support aren't stated on a readable first-hand page, and Elorian's privacy policy trains on free use by default.", "bestFor": "Visual question answering, video captioning and counting over images and video at a low per-token price, where a research preview reached through OpenRouter or Together is acceptable.", "strengths": [ "Takes text, images and video and returns text, per Elorian's launch post and Together's model page", "$0.60 per million input tokens and $3.00 per million output tokens, published without a login", "OpenRouter documents Retry-After on 429 and 503, video input as `video_url` and per-key credit limits", "Available both through OpenRouter and as a dedicated Together deployment", "Elorian's own benchmark table puts it above GPT-6 Astra on four of twelve visual evaluations. Vendor-reported" ], "weaknesses": [ "Labelled a research preview, with no public API docs, model card, changelog or deprecation policy from Elorian", "Context length, tool calling and structured output for Glimpse are not stated on any first-hand page we could read", "Elorian's privacy policy trains on Inputs and Outputs from free use by default, with an email opt-out", "Elorian's acceptable use policy bars publishing benchmark or performance information without its consent", "No status page from Elorian and no published rate limit for this model" ], "agentNotes": [ "Call it through OpenRouter as `elorian/glimpse` at https://openrouter.ai/api/v1/chat/completions. Elorian's own API docs sit behind a console sign-in", "Send video as a `video_url` content part, as a public URL or a base64 data URL", "Set `max_tokens` yourself. Reasoning tokens bill as output, and visual reasoning spends many of them", "Honour Retry-After on 429 and 503, as OpenRouter's error reference documents", "Check counts and timestamps against the source image or video before acting on them" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "F", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 35.1 } ], "editorialScores": { "ergonomics": 20, "maintenance": 51, "payments": 25, "reliability": 23, "schema": 40, "security": 56, "transparency": 31 }, "provenanceScore": 45, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://openrouter.ai/api/v1/chat/completions \\\n -H \"Authorization: Bearer $OPENROUTER_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"elorian/glimpse\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"How many open pliers are in this photo?\"},{\"type\":\"image_url\",\"image_url\":{\"url\":\"https://example.com/photo.jpg\"}}]}]}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/elorian-glimpse" }, "area": "models", "unitPrices": [ { "item": "Glimpse input", "unit": "1m-tokens", "usd": 0.6 }, { "item": "Glimpse output", "unit": "1m-tokens", "usd": 3, "note": "Reasoning tokens are output." } ], "provenance": { "legalEntity": "Elorian AI, Inc.", "domain": "elorian.ai", "domainRegistered": "2025-12-03", "endpointOnVendorDomain": false, "terms": "https://platform.elorian.ai/terms", "privacy": "https://elorian.ai/privacy", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "The privacy policy and support page name Elorian AI, Inc., with EDPO as EU and UK representative, per the 17 October 2026 check.", "The graded route is OpenRouter's (openrouter.ai), served by Together, so it is not on Elorian's domain.", "elorian.ai/.well-known/security.txt returned 404 on 17 October 2026, and elorian.ai has no robots.txt (404 on 4 November 2026).", "platform.elorian.ai, which holds the terms and the console docs, answered robots.txt with HTTP 403 S3 AccessDenied on 17 October and 4 November 2026. This run reads that as a refusal, so the 17 October reading of the terms from the platform's script is struck.", "Elorian's acceptable use policy (19 October 2026) bars accessing the Services by unauthorised means such as scraping or crawling, so since 4 November 2026 we request nothing on elorian.ai beyond that policy and keep earlier readings as recorded.", "No status page or changelog found." ], "score": 45 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/elorian-glimpse.json", "live": { "slug": "elorian-glimpse", "probe": { "target": "https://openrouter.ai/api/v1", "method": "get", "lastAt": "2026-11-09T20:49:49.542401048Z", "lastOk": true, "lastStatus": 404, "lastMs": 250, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 198, "p95ms24h": 312, "samples24h": 244, "samples30d": 5656, "days": [ { "date": "2026-10-17", "probes": 21, "ok": 21 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "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": "2026-10-17T00:00:00Z" }, "securityTxt": { "url": "https://elorian.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-09T16:05:12.513021684Z" }, "domain": { "domain": "elorian.ai", "registered": "2025-12-03", "source": "https://rdap.identitydigital.services/rdap/domain/elorian.ai", "checkedAt": "2026-11-08T15:04:18.634811613Z" }, "pages": [ { "url": "https://elorian.ai/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-09T15:40:20.234152101Z", "changedAt": "2026-11-04T08:23:25.754444261Z", "fingerprint": "bfdfaa0be214" }, { "url": "https://platform.elorian.ai/terms", "kind": "terms", "status": 304, "checkedAt": "2026-11-09T15:47:40.97801165Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e3b0c44298fc" } ], "models": { "elorian/glimpse": { "openrouterId": "elorian/glimpse", "tools": true, "structuredOutputs": true, "jsonMode": true, "reasoning": true, "input": [ "image", "text", "video" ], "promptCaching": true, "contextTokens": 262144, "maxOutput": 256000, "checkedAt": "2026-11-08T23:49:27.027409601Z" } }, "updatedAt": "2026-11-09T20:49:49.542401048Z" }, "streak": { "days": 23, "from": "2026-10-17", "sinceWatching": true, "best": 23 } }, "answer": "Muse Ember scores 51.8 (D) on agent readiness against Glimpse's 35.1 (F), and leads in 5 of 7 scored categories. Glimpse leads on payments \u0026 pricing and maintenance \u0026 community.", "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": 52, "category": "ergonomics", "leads": "muse-ember", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). On 17 October the tool, `tool_choice`, `response_format`, `structured_outputs`, cached-price, context, output-limit and batch readings for this model all came from OpenRouter's endpoints API, which this run doesn't use, so they are struck. No readable first-hand page states them today. Elorian's docs sit on a host that refuses our crawler, and Together's model page says only text, image and video in and text out on a dedicated deployment. Tool use (0 of 20), structured output (0 of 15), prompt caching (0 of 15), context length (0 of 15), batch (0 of 10). OpenRouter's SDKs in TypeScript, Python and Go, and any OpenAI client works (10 of 10, per the 17 October check, not re-read on 4 November 2026). OpenRouter's documented error codes with `limit_source` and remedy hints, nothing specific to video or image limits (10 of 15, per the 17 October check, not re-read on 4 November 2026). 0 + 0 + 0 + 0 + 0 + 10 + 10 = 20.", "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": 20, "b": 72 } }, { "by": 20, "category": "schema", "leads": "muse-ember", "name": "Schema \u0026 documentation", "reasons": { "a": "Model reading. Elorian publishes no API reference, model card or llms.txt in public. Its docs sit at platform.elorian.ai/docs, a host whose robots.txt answers access denied. The 17 October contract reading rested on OpenRouter's OpenAPI-documented chat endpoint, with no recorded visible download link on a host now paused, and on the parameter list from OpenRouter's endpoints API, both struck (0 of 25). OpenRouter's llms.txt and Markdown docs, including video input (10, per the 17 October check, not re-read on 4 November 2026). The launch post and Together's model page name the jobs (visual search, video captioning, dense counting, robotics planning) and the post states limits (token cost, no action outputs yet), but nothing says when not to use it or how video is sampled (6 of 20). Typed parameters for OpenRouter's chat endpoint in its API reference, with no reasoning effort levels documented for this model (10 of 15, per the 17 October check, not re-read on 4 November 2026; the 17 October `tool_choice` reading came from the struck endpoints API). OpenRouter's examples and error reference, with no Glimpse-specific examples or limits on video length or image count (7 of 15). OpenRouter's dated changelog, with no changelog from Elorian (7 of 15, held as partly met; the dated canonical slug came from the struck endpoints API). 0 + 10 + 6 + 10 + 7 + 7 = 40.", "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": 40, "b": 60 } }, { "by": 17, "category": "reliability", "leads": "muse-ember", "name": "Reliability", "reasons": { "a": "Hosted lines, read on the OpenRouter route. OpenRouter's status host refuses our crawler in robots.txt, so the 17 October reading of it is struck, and Elorian has no status page found (0 of 20). No 90-day incident record could be read. The 17 October uptime figures came from OpenRouter's endpoints API, a JSON data API this run doesn't use, and are struck (5). OpenRouter's limits page documents credit, budget and rate limits and a key endpoint that reports what's left, but sets no request cap on paid models, and no limit for Glimpse was found (8 of 15, per the 17 October check, not re-read on 4 November 2026, openrouter.ai paused on its terms). The errors page documents Retry-After on 429 and 503 and on 402 in-flight budget errors, and says the official SDKs honour it, with no safe-retry guidance or idempotency keys recorded (10, Retry-After alone, the value this run gives backoff or Retry-After guidance by itself; per the 17 October check, not re-read on 4 November 2026). No SLA from Elorian or for this endpoint (0). Elorian and Together label Glimpse a research preview (0). 0 + 5 + 8 + 10 + 0 + 0 = 23.", "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": 23, "b": 40 } }, { "by": 15, "category": "transparency", "leads": "muse-ember", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed model with weights not released and the open-weight base model unnamed. Elorian's terms sit on platform.elorian.ai, whose robots.txt answers access denied, so they were not read; published terms on a refusing host keep the closed-service value, held at 13 of 30. The privacy policy says Elorian trains on submitted content from free use and gives no retention periods, and the acceptable use policy, updated 19 October 2026, is still titled Privacy Policy and still carries a drafting comment from a terms outline in its markup (10 of 30, held as partly met; the 17 October comparison with the terms rested on the struck script reading). No deprecation policy or dated notices (0 of 20). Services hosted in the United States and subprocessors named by category only, and OpenRouter shows Together as the provider with its data policy (8 of 20). 13 + 10 + 0 + 8 = 31.", "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": 38, "b": 53 } }, { "by": 8, "category": "security", "leads": "muse-ember", "name": "Security \u0026 auth", "reasons": { "a": "Model reading. OpenRouter bearer keys with per-key credit limits, management keys and OAuth PKCE, no permission scopes (25 of 30, per the 17 October check, not re-read on 4 November 2026). Training on API data on this route is off according to OpenRouter's policy display for Together (no training, no prompt retention). Elorian's privacy policy trains on Inputs and Outputs from free access by default and says different terms may apply to paid and API use. The 17 October reading of Elorian's terms came from a script on a host that now refuses our crawler and is struck. Whether Elorian receives prompts from the Together deployment was not established (8 of 20, held as partly met). OpenRouter's zero-retention filter and Together's no-retention flag, against Elorian's retention 'for as long as reasonably necessary' with no period (8 of 15). OpenRouter's per-generation activity records for the operator (10 of 15). OpenRouter's security.txt was valid at its last check. Elorian has no security.txt, disclosure policy, bug bounty or certification found (5 of 20, held as partly met). 25 + 8 + 8 + 10 + 5 = 56. Readings of OpenRouter and Elorian pages per the 17 October check, not re-read on 4 November 2026.", "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": 56, "b": 64 } }, { "by": 5, "category": "payments", "leads": "elorian-glimpse", "name": "Payments \u0026 pricing", "reasons": { "a": "No machine payment protocol on OpenRouter or from Elorian (0). Per-token prices of $0.60 input and $3.00 output per million tokens published without a login in Elorian's launch post (20). Together lists Glimpse on dedicated endpoints with pricing on request. Elorian's post says it can be tried free on Elorian's platform, which needs a sign-in, and whether a card is needed was not established (5 of 20). A person signs up in a browser on every route (0). 0 + 20 + 5 + 0 = 25. Elorian's and OpenRouter's pages per the 17 October check, not re-read on 4 November 2026.", "b": "Published rubric. No payment protocol (0). Per-token prices for both tiers published without a login, read 9 November (20). No free API allowance found; billing needs a card, per the platform reading (0). Browser sign-up (0). 0 + 20 + 0 + 0 = 20." }, "scores": { "a": 25, "b": 20 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Elorian", "b": "Meta", "name": "Vendor" }, { "a": "https://openrouter.ai/api/v1", "b": "https://api.meta.ai/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "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": "Closed model and service under the Elorian AI, Inc. terms of service. Weights not released.", "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": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-16", "b": "2026-11-09", "name": "Last release" }, { "a": "couldn't be read", "b": "2026-10-02", "name": "Terms last updated" }, { "a": "2026-10-12", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "yes", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "2.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Muse Ember scores 51.8 (D) on agent readiness against Glimpse's 35.1 (F), and leads in 5 of 7 scored categories. Glimpse leads on payments \u0026 pricing and maintenance \u0026 community.", "question": "Which is better for AI agents, Glimpse or Muse Ember?" }, { "answer": "Both need an API key.", "question": "Do Glimpse and Muse Ember need an API key?" }, { "answer": "Yes. Glimpse has a hosted endpoint at https://openrouter.ai/api/v1 and Muse Ember at https://api.meta.ai/v1.", "question": "Can an agent call Glimpse and Muse Ember without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 25 against 20", "Maintenance \u0026 community, 51 against 46" ], "also": null, "goodFor": "Visual question answering, video captioning and counting over images and video at a low per-token price, where a research preview reached through OpenRouter or Together is acceptable.", "slug": "elorian-glimpse", "watchFor": "Labelled a research preview, with no public API docs, model card, changelog or deprecation policy from Elorian" }, { "aheadOn": [ "Reliability, 40 against 23", "Schema \u0026 documentation, 60 against 40", "Agent ergonomics, 72 against 20", "Security \u0026 auth, 64 against 56", "Transparency \u0026 trust, 53 against 38" ], "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": { "elorian-glimpse": [ { "causes": [ "correction" ], "date": "2026-11-04", "delta": -13.7, "from": 48.8, "fromGrade": "D", "to": 35.1, "toGrade": "F" }, { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.2, "from": 49, "fromGrade": "D", "to": 48.8, "toGrade": "D" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.4, "from": 48.6, "fromGrade": "D", "to": 49, "toGrade": "D" } ], "muse-ember": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse.json", "title": "Amazon Bedrock vs Glimpse", "url": "https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse" }, { "json": 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"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": 17, "edge": "muse-ember", "elorian-glimpse": 23, "key": "reliability", "muse-ember": 40, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 20, "edge": "muse-ember", "elorian-glimpse": 40, "key": "schema", "muse-ember": 60, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 52, "edge": "muse-ember", "elorian-glimpse": 20, "key": "ergonomics", "muse-ember": 72, "name": "Agent ergonomics", "weight": 13 }, { "by": 8, "edge": "muse-ember", "elorian-glimpse": 56, "key": "security", "muse-ember": 64, "name": "Security \u0026 auth", "weight": 14 }, { "by": 5, "edge": "elorian-glimpse", "elorian-glimpse": 25, "key": "payments", "muse-ember": 20, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 5, "edge": "elorian-glimpse", "elorian-glimpse": 51, "key": "maintenance", "muse-ember": 46, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 15, "edge": "muse-ember", "elorian-glimpse": 38, "key": "transparency", "muse-ember": 53, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Muse Ember scores 51.8 (D) on agent readiness against Glimpse's 35.1 (F), and leads in 5 of 7 scored categories. Glimpse leads on payments \u0026 pricing and maintenance \u0026 community. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "elorian-glimpse": "Glimpse reads images and video at $0.60 input and $3.00 output per million tokens, through OpenRouter or a dedicated Together deployment. It is a research preview with no public Elorian docs, model card or status page, its context and tool support aren't stated on a readable first-hand page, and Elorian's privacy policy trains on free use by default.", "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/elorian-glimpse-vs-muse-ember", "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember.min.md" }, "markdown": "Muse Ember scores 51.8 (D) on agent readiness against Glimpse's 35.1 (F), and leads in 5 of 7 scored categories. Glimpse leads on payments \u0026 pricing and maintenance \u0026 community. Both do llm inference.\n\n- Glimpse: grade F, 35.1/100, rank #1403 of 1515. Markdown https://www.anchorterminal.com/tools/elorian-glimpse.md · JSON https://www.anchorterminal.com/api/v1/tools/elorian-glimpse.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### Glimpse (F)\n\nGood for: Visual question answering, video captioning and counting over images and video at a low per-token price, where a research preview reached through OpenRouter or Together is acceptable.\n\nAhead on:\n- Payments \u0026 pricing, 25 against 20\n- Maintenance \u0026 community, 51 against 46\n\nWatch for: Labelled a research preview, with no public API docs, model card, changelog or deprecation policy from Elorian\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 23\n- Schema \u0026 documentation, 60 against 40\n- Agent ergonomics, 72 against 20\n- Security \u0026 auth, 64 against 56\n- Transparency \u0026 trust, 53 against 38\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### Agent ergonomics: Muse Ember +52\n\n- Glimpse (20): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). On 17 October the tool, `tool_choice`, `response_format`, `structured_outputs`, cached-price, context, output-limit and batch readings for this model all came from OpenRouter's endpoints API, which this run doesn't use, so they are struck. No readable first-hand page states them today. Elorian's docs sit on a host that refuses our crawler, and Together's model page says only text, image and video in and text out on a dedicated deployment. Tool use (0 of 20), structured output (0 of 15), prompt caching (0 of 15), context length (0 of 15), batch (0 of 10). OpenRouter's SDKs in TypeScript, Python and Go, and any OpenAI client works (10 of 10, per the 17 October check, not re-read on 4 November 2026). OpenRouter's documented error codes with `limit_source` and remedy hints, nothing specific to video or image limits (10 of 15, per the 17 October check, not re-read on 4 November 2026). 0 + 0 + 0 + 0 + 0 + 10 + 10 = 20.\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### Schema \u0026 documentation: Muse Ember +20\n\n- Glimpse (40): Model reading. Elorian publishes no API reference, model card or llms.txt in public. Its docs sit at platform.elorian.ai/docs, a host whose robots.txt answers access denied. The 17 October contract reading rested on OpenRouter's OpenAPI-documented chat endpoint, with no recorded visible download link on a host now paused, and on the parameter list from OpenRouter's endpoints API, both struck (0 of 25). OpenRouter's llms.txt and Markdown docs, including video input (10, per the 17 October check, not re-read on 4 November 2026). The launch post and Together's model page name the jobs (visual search, video captioning, dense counting, robotics planning) and the post states limits (token cost, no action outputs yet), but nothing says when not to use it or how video is sampled (6 of 20). Typed parameters for OpenRouter's chat endpoint in its API reference, with no reasoning effort levels documented for this model (10 of 15, per the 17 October check, not re-read on 4 November 2026; the 17 October `tool_choice` reading came from the struck endpoints API). OpenRouter's examples and error reference, with no Glimpse-specific examples or limits on video length or image count (7 of 15). OpenRouter's dated changelog, with no changelog from Elorian (7 of 15, held as partly met; the dated canonical slug came from the struck endpoints API). 0 + 10 + 6 + 10 + 7 + 7 = 40.\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### Reliability: Muse Ember +17\n\n- Glimpse (23): Hosted lines, read on the OpenRouter route. OpenRouter's status host refuses our crawler in robots.txt, so the 17 October reading of it is struck, and Elorian has no status page found (0 of 20). No 90-day incident record could be read. The 17 October uptime figures came from OpenRouter's endpoints API, a JSON data API this run doesn't use, and are struck (5). OpenRouter's limits page documents credit, budget and rate limits and a key endpoint that reports what's left, but sets no request cap on paid models, and no limit for Glimpse was found (8 of 15, per the 17 October check, not re-read on 4 November 2026, openrouter.ai paused on its terms). The errors page documents Retry-After on 429 and 503 and on 402 in-flight budget errors, and says the official SDKs honour it, with no safe-retry guidance or idempotency keys recorded (10, Retry-After alone, the value this run gives backoff or Retry-After guidance by itself; per the 17 October check, not re-read on 4 November 2026). No SLA from Elorian or for this endpoint (0). Elorian and Together label Glimpse a research preview (0). 0 + 5 + 8 + 10 + 0 + 0 = 23.\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### Transparency \u0026 trust: Muse Ember +15\n\n- Glimpse (38): Closed model with weights not released and the open-weight base model unnamed. Elorian's terms sit on platform.elorian.ai, whose robots.txt answers access denied, so they were not read; published terms on a refusing host keep the closed-service value, held at 13 of 30. The privacy policy says Elorian trains on submitted content from free use and gives no retention periods, and the acceptable use policy, updated 19 October 2026, is still titled Privacy Policy and still carries a drafting comment from a terms outline in its markup (10 of 30, held as partly met; the 17 October comparison with the terms rested on the struck script reading). No deprecation policy or dated notices (0 of 20). Services hosted in the United States and subprocessors named by category only, and OpenRouter shows Together as the provider with its data policy (8 of 20). 13 + 10 + 0 + 8 = 31.\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### Security \u0026 auth: Muse Ember +8\n\n- Glimpse (56): Model reading. OpenRouter bearer keys with per-key credit limits, management keys and OAuth PKCE, no permission scopes (25 of 30, per the 17 October check, not re-read on 4 November 2026). Training on API data on this route is off according to OpenRouter's policy display for Together (no training, no prompt retention). Elorian's privacy policy trains on Inputs and Outputs from free access by default and says different terms may apply to paid and API use. The 17 October reading of Elorian's terms came from a script on a host that now refuses our crawler and is struck. Whether Elorian receives prompts from the Together deployment was not established (8 of 20, held as partly met). OpenRouter's zero-retention filter and Together's no-retention flag, against Elorian's retention 'for as long as reasonably necessary' with no period (8 of 15). OpenRouter's per-generation activity records for the operator (10 of 15). OpenRouter's security.txt was valid at its last check. Elorian has no security.txt, disclosure policy, bug bounty or certification found (5 of 20, held as partly met). 25 + 8 + 8 + 10 + 5 = 56. Readings of OpenRouter and Elorian pages per the 17 October check, not re-read on 4 November 2026.\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### Payments \u0026 pricing: Glimpse +5\n\n- Glimpse (25): No machine payment protocol on OpenRouter or from Elorian (0). Per-token prices of $0.60 input and $3.00 output per million tokens published without a login in Elorian's launch post (20). Together lists Glimpse on dedicated endpoints with pricing on request. Elorian's post says it can be tried free on Elorian's platform, which needs a sign-in, and whether a card is needed was not established (5 of 20). A person signs up in a browser on every route (0). 0 + 20 + 5 + 0 = 25. Elorian's and OpenRouter's pages per the 17 October check, not re-read on 4 November 2026.\n- Muse Ember (20): Published rubric. No payment protocol (0). Per-token prices for both tiers published without a login, read 9 November (20). No free API allowance found; billing needs a card, per the platform reading (0). Browser sign-up (0). 0 + 20 + 0 + 0 = 20.\n\n## Score by category\n\n| Category | Weight | Glimpse | Muse Ember | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 23 | 40 | Muse Ember +17 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 40 | 60 | Muse Ember +20 |\n| Agent ergonomics | 13% (16.2 this run) | 20 | 72 | Muse Ember +52 |\n| Security \u0026 auth | 14% (17.5 this run) | 56 | 64 | Muse Ember +8 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 25 | 20 | Glimpse +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 51 | 46 | Glimpse +5 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 38 | 53 | Muse Ember +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **35.1 · F** | **51.8 · D** | |\n\n## Facts side by side\n\n| Fact | Glimpse | Muse Ember |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Elorian | Meta |\n| Hosted endpoint | `https://openrouter.ai/api/v1` | `https://api.meta.ai/v1` |\n| Transports | HTTP | |\n| Auth | API key | API key |\n| Pricing | Pay per use | Pay per use |\n| x402 | no | no |\n| Licence | Closed model and service under the Elorian AI, Inc. terms of service. Weights not released. | 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 | no | yes |\n| Last release | 2026-10-16 | 2026-11-09 |\n| Terms last updated | couldn't be read | 2026-10-02 |\n| Privacy policy last updated | 2026-10-12 | couldn't be read |\n| Customer content may train models | yes, with an opt-out | yes |\n| Terms restrict automated access | couldn't be read | not found in the text |\n| Terms restrict benchmarking | couldn't be read | yes |\n| Terms or service can change without notice | couldn't be read | not found in the text |\n| Arbitration or class-action waiver | couldn't be read | yes |\n| Agent reviews | 2.5/5 (4) | none |\n\n## How the scores have moved\n\n### Glimpse\n\n- -13.7 on 4 November 2026 (D to F): correction\n- -0.2 on 30 October 2026: checklist\n- +0.4 on 27 October 2026: checklist\n\n### Muse Ember\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Glimpse.** Glimpse reads images and video at $0.60 input and $3.00 output per million tokens, through OpenRouter or a dedicated Together deployment. It is a research preview with no public Elorian docs, model card or status page, its context and tool support aren't stated on a readable first-hand page, and Elorian's privacy policy trains on free use by default.\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### Glimpse\n\n1. Call it through OpenRouter as `elorian/glimpse` at https://openrouter.ai/api/v1/chat/completions. Elorian's own API docs sit behind a console sign-in\n2. Send video as a `video_url` content part, as a public URL or a base64 data URL\n3. Set `max_tokens` yourself. Reasoning tokens bill as output, and visual reasoning spends many of them\n4. Honour Retry-After on 429 and 503, as OpenRouter's error reference documents\n5. Check counts and timestamps against the source image or video before acting on them\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, Glimpse or Muse Ember?\n\nMuse Ember scores 51.8 (D) on agent readiness against Glimpse's 35.1 (F), and leads in 5 of 7 scored categories. Glimpse leads on payments \u0026 pricing and maintenance \u0026 community.\n\n### Do Glimpse and Muse Ember need an API key?\n\nBoth need an API key.\n\n### Can an agent call Glimpse and Muse Ember without installing anything?\n\nYes. Glimpse has a hosted endpoint at https://openrouter.ai/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/elorian-glimpse-vs-muse-ember.json, and with the fewest tokens: https://www.anchorterminal.com/compare/elorian-glimpse-vs-muse-ember.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"elorian-glimpse\", \"b\": \"muse-ember\"}`. From a terminal: `anchor compare elorian-glimpse muse-ember`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/elorian-glimpse.json and https://www.anchorterminal.com/api/v1/tools/muse-ember.json\n\n## Other comparisons with Glimpse or Muse Ember\n\n- [Amazon Bedrock vs Glimpse](https://www.anchorterminal.com/compare/amazon-bedrock-vs-elorian-glimpse.md)\n- [Amazon Bedrock vs Muse Ember](https://www.anchorterminal.com/compare/amazon-bedrock-vs-muse-ember.md)\n- [Claude API vs Glimpse](https://www.anchorterminal.com/compare/anthropic-api-vs-elorian-glimpse.md)\n- [Claude API vs Muse Ember](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-ember.md)\n- [Antseed vs Glimpse](https://www.anchorterminal.com/compare/antseed-vs-elorian-glimpse.md)\n- [Antseed vs Muse Ember](https://www.anchorterminal.com/compare/antseed-vs-muse-ember.md)\n- [Azure OpenAI in Foundry Models vs Glimpse](https://www.anchorterminal.com/compare/azure-openai-vs-elorian-glimpse.md)\n- 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RouterPlus](https://www.anchorterminal.com/compare/muse-ember-vs-routerplus.md)\n- [Muse Ember vs SambaCloud](https://www.anchorterminal.com/compare/muse-ember-vs-sambanova.md)\n- [Muse Ember vs SiliconFlow](https://www.anchorterminal.com/compare/muse-ember-vs-siliconflow.md)\n- [Muse Ember vs Simplismart](https://www.anchorterminal.com/compare/muse-ember-vs-simplismart.md)\n- [Muse Ember vs StepFun API](https://www.anchorterminal.com/compare/muse-ember-vs-stepfun-api.md)\n- [Muse Ember vs SWE-2 Flash](https://www.anchorterminal.com/compare/muse-ember-vs-swe-2-flash.md)\n- [Muse Ember vs Tencent Cloud 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": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Glimpse vs Muse Ember", 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