Gemini Developer API vs Muse Ember

Gemini Developer API 83

Model reading. gemini-4-argon went GA on 13 October and the newest changelog entry, on 30 October, takes the Computer Use tool to GA (30). The deprecations page lists earliest possible shutdown dates and promises advance notice, with no stated minimum, and deep-research-pro-preview-12-2025 was announced on 8 October for shutdown on 23 October (4 of 12). Shutdown dates in the 90 days from 3 August include Imagen 4 on 17 August, Robotics ER 1.6 on 31 August, antigravity-preview-05-2026 on 5 October, the Veo 3.1 previews and gemini-omni-flash-preview on 22 October and deep-research-pro-preview-12-2025 on 23 October, each in the table with a replacement, and 3.7 and 3.5 Flash were deprecated on 8 October with requests routed to newer models (4 of 8). 16 dated changelog entries from 13 August to 30 October (15 of 15). SDK repository replies not sampled (5 of 10). Current official SDKs, google-genai 2.34.0 and @google/genai 2.32.0, both tagged on 29 October, with releases about weekly through October (15). Supported runtimes stated, Python 3.11 and later since 2.34.0 dropped 3.10, Node 20 and later (10).

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.

Gemini Developer API 85

A keyless Discovery document at generativelanguage.googleapis.com/$discovery/rest?version=v1beta (revision 20261101, re-read on 1 November) types 86 methods and 225 schemas for GenerateContent, files, batches, caching and models, but not the Interactions API the guides now lead with (20 of 25). llms.txt at ai.google.dev/gemini-api/docs/llms.txt, with Markdown twins of each page (10). Reference not read in full, and the changelog and latest-model guide name the recommended models (15 of 20). Structured output accepts JSON Schema with enums, minimum, maximum, prefixItems and $ref, but the server ignores minLength, maxLength, minProperties, maxProperties and uniqueItems, per the structured output page re-read on 1 November (10 of 15). Examples on every guide and an API errors page with HTTP, blocked and content codes (15). Dated changelog and model versions (15).

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.

Gemini Developer API 93

Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Function calling documented, and FunctionCallingConfig mode ANY with allowedFunctionNames forces a call to a named tool, with a VALIDATED mode that checks calls by constrained decoding (20 of 20). The structured output page, re-read on 1 November, says output adheres to the supplied JSON Schema and is syntactically correct JSON, and names the keywords constrained decoding doesn't enforce, while asking callers to validate values (13 of 15; the 12 October note's 10 rested on the page promising no constrained decoding). Context caching at 0.1x input, $0.075 per million on 3.8 Flash until 31 December, and implicit caching on gemini-4-argon, which doesn't support explicit caches (15). 1,048,576-token context on the default and flagship models (15). Batch half price (10). Official SDKs for Python and JavaScript (10). Documented error codes with backoff guidance (10 of 15, because 400, 402 and 403 are flagged as not retryable but recovery advice per code sits on a separate page we only skimmed).

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.

Gemini Developer API 40

No machine payment protocol (0). Per-token prices published without a login, re-read on 1 November (20). Free tier on 3.8 Flash, 3.6 Flash, 3.5 Flash-Lite and 3.1 Flash-Lite, not on gemini-4-argon or 3.1 Pro preview, and the rate-limits page needs only an active project for the free tier and a linked billing account from Tier 1, so the free tier needs no card (20). A Google account and AI Studio are needed for a key (0).

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.

Gemini Developer API 72

Closed service with clear terms, SDKs Apache-2.0 (15). Terms, pricing page and logs policy agree that free-tier data improves Google products and paid data doesn't, but abuse retention on paid services has no number, and the 26 October changelog entry turns on request storage by default for new paid projects while existing projects keep their setting (20 of 30). Deprecations table with earliest shutdown dates, exact dates promised later (15 of 20). Terms say data may be cached in any country where Google has facilities. No subprocessor list checked (5 of 20).

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.

Gemini Developer API 50

Model reading. Keys live in a Cloud project. Since 28 May 2026 new keys are authorisation keys bound to a service account and restricted to the Gemini API, keys can be limited by IP or origin, unrestricted standard keys are rejected, and the docs give a leak checklist, per the API key page re-read on 1 November. No permission scopes, so 25 of 30, less 10 because the API reads a token from the URL. The Discovery document (revision 20261101) lists access_token, oauth_token and key as query parameters, and on 1 November a generateContent request with no credential answered 403 'Method doesn't allow unregistered callers' while one with a made-up ?access_token= answered 401 'Request had invalid authentication credentials' (ACCESS_TOKEN_TYPE_UNSUPPORTED), the deduction Google APIs took on 17 October and 1 November and Gemini Embedding and Gemini Live carry (15 of 30). Terms (effective 23 March 2026, re-read 1 November) say free-tier prompts and responses are used to improve Google products and human reviewers may read them, paid tier isn't used (10 of 20). Abuse monitoring on paid services is kept 'a limited period' with no number, grounding data 30 days, and since 26 October new paid projects store Generate Content requests by default unless store=false. No zero-retention route on this API was found (5 of 15). Request logs in AI Studio for billed projects (15). security.txt on google.com valid to 2030-04-01 with a vulnerability reward programme, re-read on 1 November. No certification naming the Developer API found, the reading Gemini Embedding takes (5 of 20).

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.