About Muse Ember
Muse Ember is Meta's smallest and fastest Muse model, built for the work that repeats all day: pulling data from documents, sorting requests, calling tools in order and making small code fixes. It reads up to 1 million tokens in one conversation
Ember scores as high as Claude Haiku 5.5 on the Artificial Analysis Intelligence Index at about a third of the cost, and it writes 446 tokens per second, almost twice as fast as Haiku 5.5. It finishes more end-to-end business tasks than Claude Haiku 5.5 and GPT-6 Luna, and it reads screenshots, scanned documents, audio and video
On Overchat AI, Muse Ember works without a Meta developer account. It is in the same chat as Muse Wonder, Claude and GPT-6, so you can plan a hard task with a bigger model and hand the routine steps to Ember
- Developer
- Meta
- Released
- Nov 9, 2026
- Family
- Muse
- Context window
- 1M tokens
- Max output
- 512K tokens
- Input
- Text, images, audio, video, files
See how Muse Ember answers
Pull the details from this invoice into JSON: vendor, invoice number, issue date, due date, line items (description, quantity, unit price) and total. Check that the total adds up. BRIGHTLINE PRINTING CO. Invoice #BL-20931 Issued: Oct 28, 2026 · Due: Nov 27, 2026 Bill to: Harbor & Pine Coffee 500 × Paper cups, 12 oz — $0.18 200 × Menu cards, A5 — $0.95 2 × Window posters, A1 — $24.00 Shipping — $15.00 Total due: $313.00
{
"vendor": "BRIGHTLINE PRINTING CO.",
"invoice_number": "BL-20931",
"issue_date": "2026-10-28",
"due_date": "2026-11-27",
"line_items": [
{
"description": "Paper cups, 12 oz",
"quantity": 500,
"unit_price": 0.18
},
{
"description": "Menu cards, A5",
"quantity": 200,
"unit_price": 0.95
},
{
"description": "Window posters, A1",
"quantity": 2,
"unit_price": 24.00
},
{
"description": "Shipping",
"quantity": 1,
"unit_price": 15.00
}
],
"total": 313.00
}Total check: Does not add up
- 500 × $0.18 = $90.00
- 200 × $0.95 = $190.00
- 2 × $24.00 = $48.00
- Shipping = $15.00
Calculated total: $343.00 Stated total: $313.00 Difference: $30.00
This function should return the orders from the last 7 days, including today, but today's orders never show up. Fix it. from datetime import date, timedelta def last_7_days(orders): start = date.today() - timedelta(days=7) return [o for o in orders if start < o['day'] < date.today()]
The upper bound is exclusive — < date.today() excludes today.
Make both bounds inclusive, and use days=6 if you want *exactly* 7 calendar days including today:
from datetime import date, timedelta
def last_7_days(orders):
today = date.today()
start = today - timedelta(days=6) # today, today-1, ..., today-6
return [o for o in orders if start <= o['day'] <= today]Turn these meeting notes into a task list with an owner and a deadline for each task. Flag anything that has no owner. Launch sync, Nov 10: Maya will finish the pricing page copy by Thursday. The landing page images still need a designer, nobody picked that up. Leo will fix the checkout bug before Friday's release. We agreed to send the beta invite email on Monday, and Sara owns the list. Someone should check the Spanish translation
Here you go — from the Nov 10 launch sync:
Task List
| Task | Owner | Deadline |
|---|---|---|
| Finish the pricing page copy | Maya | Thursday |
| Create landing page images | ⚠️ UNASSIGNED — flagged | Not specified |
| Fix the checkout bug | Leo | Before Friday's release |
| Send the beta invite email | Sara (owns the list) | Monday |
| Check the Spanish translation | ⚠️ UNASSIGNED — flagged | Not specified |
Flagged - no owner:
- Landing page images — still needs a designer, nobody picked it up
- Spanish translation check — "someone should check"
More prompts to try with Muse Ember
Muse Ember vs other models
Compare Muse Ember with Claude Haiku 5.5 and GPT-6 Luna on the same agent, coding and vision tests
| Spec | Muse Ember | Claude Haiku 5.5 |
|---|---|---|
| Developer | Meta | Anthropic |
| Released | Nov 9, 2026 | Oct 7, 2026 |
| Context window? | 1M tokens | 1M tokens |
| Output speed? | 446 tokens/s | 254 tokens/s |
| Spec | Muse Ember | GPT-6 Luna |
|---|---|---|
| Developer | Meta | OpenAI |
| Released | Nov 9, 2026 | Sep 22, 2026 |
| Context window? | 1M tokens | 1M tokens |
| Output speed? | 446 tokens/s | 104 tokens/s |
Sources: Meta, Introducing our smallest, most efficient model: Muse Ember (Nov 9, 2026), Meta Model API, Muse Ember, Artificial Analysis, Muse Ember
Muse Ember main features
Tasks across apps, screenshots and scans, quick code fixes and fast answers
Tasks across apps
Muse Ember carries a task from start to finish: it pulls the records, calls tools in the right order and updates the next app. On AutomationBench, a test of end-to-end business workflows, it scores 37.8% against 20.2% for GPT-6 Luna and 13.9% for Claude Haiku 5.5
Screenshots and scans
Send Muse Ember a screenshot, a photo of a receipt or a scanned document, and it reads the numbers and answers your question about them. It scores 80.6% on PerceptionBench, a test of questions about images and documents, against 78.6% for Claude Haiku 5.5 and 62.8% for GPT-6 Luna
Quick code fixes
Muse Ember reads the failing test, finds the line that breaks it and gives the smallest fix. It scores 40.9% on Terminal-Bench 4.0, a test of coding tasks in a terminal, against 39.2% for Claude Haiku 5.5 and 16.4% for GPT-6 Luna
Fast answers
Muse Ember writes 446 tokens per second on Artificial Analysis's test, against 254 for Claude Haiku 5.5 and 104 for GPT-6 Luna, and its first words arrive in about 4 seconds. That makes it a good fit for many short tasks in a row, such as sorting tickets or tagging rows
Why use Muse Ember on Overchat AI
One account for chat, images and video, on every device
Superchat AI agent
Superchat Agent automatically routes your message to the model best suited for the task. It can generate images and videos, use the AI tools built into Overchat AI, and learn from your interactions to get better over time
Chat with images and files
Upload PDFs, spreadsheets, code and screenshots and ask Muse Ember about them. You can also dictate a message instead of typing it
Go beyond text
Generate images with Nano Banana and GPT Image and videos with Seedance and Kling in the same account, with the same credits as chat
On the web, iPhone and Android
Start a chat on your laptop and finish it on your phone. The Overchat AI app has the same models, and your chats stay in one account on every device
How to use Muse Ember on Overchat AI
Start in the chat at the top of this page or in the Overchat AI app on the web, iOS or Android
- 01
Pick Muse Ember
It is already picked in the chat on this page. In the Overchat AI app, open the model list next to the message field, choose Meta and pick Muse Ember
- 02
Attach a document or a screenshot
Add a PDF, a spreadsheet, a screenshot or your code, and write what you need: the result, the format and what to check
- 03
Keep going in the same chat
Ask a follow-up, ask for a table or a shorter version, or switch to another model without losing the conversation
Explore other models
Models marked Soon are coming to Overchat AI; the rest are available now
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Muse Ember FAQ
If you have any questions,
reach out to us at hello@overchat.ai
Muse Ember is Meta's smallest and most efficient Muse model, released on November 9, 2026. It is built for repeated agent work such as tool calls, data extraction, sorting requests and small coding tasks. It reads text, images, audio, video and files and has a 1-million-token context window
Muse Ember is used for tasks that come in large numbers: pulling fields from invoices and forms, sorting support tickets, reading screenshots and scans, summarizing long documents and fixing small bugs. Meta suggests pairing it with Muse Wonder, which plans the work while Ember does the steps
On most tests in Meta's table, yes: AutomationBench 37.8% against 13.9%, Terminal-Bench 4.0 40.9% against 39.2% and PerceptionBench 80.6% against 78.6%. Claude Haiku 5.5 is ahead on FrontierCode 2.0, a test of long coding tasks, with 34.9% against 27.2%. Both score 36 on the Artificial Analysis Intelligence Index, and Ember writes almost twice as fast
Muse Wonder is Meta's strongest model for the hardest problems. Muse Spark is the mid-size model for coding and agent work. Muse Ember is the smallest and fastest: it scores 36 on the Artificial Analysis Intelligence Index against 37 for Muse Spark 1.3 at a fraction of the cost. All three are in the Overchat AI chat
No. Meta keeps the weights of Muse Ember private, and the model runs only on Meta's hosted infrastructure. Meta's open Muse model is Muse Glimmer
Muse Ember is available in the Meta Model API, where its model ID is muse-ember-1.0, in Muse Code on every plan, on Google Cloud and Oracle Cloud, and in the Overchat AI chat
Muse Ember reads up to 1 million tokens in one conversation, roughly 750,000 words, and its answers can be up to 512,000 tokens long
Type your message in the chat at the top of this page, attach a document or a screenshot if you need to and press Send. After you sign in, Muse Ember answers in the Overchat AI chat, where you can keep the conversation going on the web, iOS or Android and switch to another model at any time
