Meta models: available, used, and future ideas
A one-time look (2026-11-02) at every model Meta offered me, what Arya uses
today, and what it could use later. The models in use are described in
assistant/docs/MODEL-POLICY.md and
docs/quest/META-PRODUCTS.md. This page adds the
models I did not use. The model list comes from Meta's models page
(dev.meta.ai/docs/models) as read on 2026-11-02, and the code from
assistant/api/meta_client.py. Where I could not confirm something, it says
"unconfirmed". Everything under "Future" is an idea, not built and not promised.
Which Meta models does Arya use today?
The models in use, with ids and jobs: For judges, Meta model map.
Which Meta models are available but not used?
| Model | What it is | Fit for Arya | Cost and effort |
|---|---|---|---|
Spark 1.3 Contributor (muse-spark-1.3-contributor) | Same model on a lower-price tier with different data terms (see Meta's models page) | Cuts AI cost by roughly 10x on input and 20x on output (list prices: $0.10 / $0.20 vs $1.25 / $4.25 per 1M tokens). The code supports it (ARYA_SPARK_TIER), but Arya runs Standard on purpose. Future idea: a community tier where a user opts in, for non-personal jobs only | Needs an opt-in screen, routing rule and privacy text first. Rate limit 150 requests/min vs 3,000 on Standard, which also caps scale |
| Muse Glimmer (open weights) | 30B dense, text and image in, text out, Apache 2.0, distilled from Spark; runs on your own hardware via vLLM, SGLang, llama.cpp, Ollama | Future idea: a self-hosted "household stays at home" reader, or a cheap pre-filter before Spark for name cleanup and labels. Text and image only, so no audio or PDF. Accuracy on receipts is not measured by me | No per-token price from Meta; I would pay for a GPU or a host. Whether Baseten serves it is unconfirmed. Needs its own eval against the 98-line receipt set before any job moves |
| Muse Spark 1.2 / 1.1 | Older Spark versions. Meta recommends 1.2 for audio input | Not needed: I send audio to Voice Transcribe | None |
| Muse Wonder Full | Higher Wonder variant | Muse Code plans only, not on the Model API, so unavailable to the app | n/a |
Smaller API features I have not used: web-search grounding ($2.50 per 1,000 searches; it could ground "is this a good price", but it would send queries out, which conflicts with the personal-data rule), computer use (no fit), and the Files API with background responses (a possible fit for very long scan videos). Image generation is only used offline for the characters. A live "dinner render" idea sits in MODEL-POLICY and is not built.
Why can I not use store video and photos?
The best raw material for better store maps and shelf help already exists
online: walkthrough videos and in-store photos on YouTube, TikTok and similar
sites. Arya cannot use them. They belong to their creators and the platforms,
and the platform terms forbid bulk collection. Arya's own rule is that no
store map is built from footage I do not have the right to use. The
Trader Joe's walkthrough experiment was removed for exactly this reason (see
docs/quest/META-PRODUCTS.md). Today every store map comes from a shopper
walking their own store with the guided scan.
Future idea: a data partnership. A store chain, a licensed-content provider or a platform that can legally supply in-store video and photos (aisle walkthroughs, shelf signs, layout) would let Arya:
- start each store with a first map instead of an empty one;
- test and tune the shelf-reading step (SAM plus Spark) on many layouts, not one household's;
- give community shoppers better "where is it" help from day one.
Any partnership would need written permission, store consent, the existing
people-pixelating rule, and a takedown route. See
docs/ROADMAP.md ("Store data and community").