model: "openvibe/economy"The lowest cost per successful answer.
- cheapest in, per M
- $0.10
- cheapest out, per M
- $0.50
- context, tokens
- 1,048,576
- typical first answer
- –
- uptime, 7 days
- –
Measured
From OpenVibe.Report: real calls in the last 30 days, with no prompt and no person in them.
Not measured yet: a model is measured after 20 calls in 30 days.
Every offer that serves it
Price in, out and cached per million tokens; speed and uptime from the last seven days of real requests; the privacy label and the provider’s own data policy.
| Offer | Status | In / out per M | Speed | First token | Uptime | Errors | Privacy | Data policy | Try |
|---|---|---|---|---|---|---|---|---|---|
| Meta Model API | Down off until the owner turns it on | $0.10 / $0.50 | – p50 · – p95 | – | – | – | Anonymized interactive/background/batch only | training not stated · no retention | Try it |
Compare Muse Ember 1.0 with another model →
Measured performance
No completed day has twenty qualifying runs for this model.
Bench rating: chat.arena
No single model rating has twenty qualifying games.
Source: OpenVibe.Bench. Latency and cost come from OpenVibe.AI receipts.
Presets
A preset fixes the router’s floor, ceiling and policy, and you name it as the model.
model: "openvibe/fast"The quickest measured offer.
model: "openvibe/private"Only capacity OpenVibe runs or that sits on a local machine.
model: "openvibe/auto"Cost, health and latency weighed together. The default.
These four aliases work today. A saved preset (model: "@preset/private") is the router’s floor, ceiling, quantization, region and data policy written down once. The private preset is the strict one: only offers that keep nothing and train on nothing, or OpenVibe’s own deployments, may answer, and the router refuses rather than fall back.
Try it
Use it from code
curl https://api.openvibe.exchange/v1/chat/completions \
-H "Authorization: Bearer $OPENVIBE_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"meta/muse-ember-1.0","messages":[{"role":"user","content":"Hello"}]}'import OpenAI from 'openai';
const ai = new OpenAI({ baseURL: 'https://api.openvibe.exchange/v1', apiKey: process.env.OPENVIBE_KEY });
const r = await ai.chat.completions.create({ model: 'meta/muse-ember-1.0', messages: [{ role: 'user', content: 'Hello' }] });The endpoint, keys and usage: the API.