Intelligence
Index v5.0
Custom pricing for production workloads
Run tool calls, coding-agent subtasks and routing in repeated agent loops on Meta's smallest reasoning model
Muse Ember is Meta's reasoning model for repeated coding subtasks, tool calls, routing and extraction.
meta/muse-emberhttps://api.aimlapi.com/v1Muse Ember is Meta's smallest reasoning model. It is built for coding subtasks, tool calls, routing, extraction and long-document processing. Meta recommends pairing it with Muse Wonder or Muse Spark: use Muse Wonder or Muse Spark for planning and Muse Ember for repeated execution.
The context window holds 1,048,576 tokens. Meta documents a maximum response of 524,288 output tokens. Set max_tokens to the size your task needs: extracting a few fields does not need the same output budget as producing a long document.
The AI/ML API endpoint lists text, image and video inputs, plus file input, tools, structured output, streaming and reasoning. Use structured output when another step needs to read the answer as data. Set reasoning_effort per request and test the smallest effort that completes your task reliably.
Run focused coding subtasks inside a larger agent workflow.
Extract fields from long documents into structured output.
Route requests and make repeated tool calls.
Process images, video frames and files alongside text instructions.
See how Muse Ember compares in intelligence and cost per task. Data retrieved Nov 9, 2026.
Index v5.0
USD / benchmark task
| Usage | Price | Unit |
|---|---|---|
| Input | $0.1058 | 1M tokens |
| Output | $0.529 | 1M tokens |
| Cached input | $0.0042 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 10, 2026.
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
| $0.1058 | $0.529 | |
| $0.3703 | $1.59 | |
| $1.32 | $4.5 | |
| $1.32 | $4.5 | |
| $4.23 | $21.16 |
Give your agent the model details, code and documentation.
export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "meta/muse-ember",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "meta/muse-ember",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "meta/muse-ember",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Muse Ember costs $0.1058 / 1M tokens for input and $0.529 / 1M tokens for output on AI/ML API. Cached input is billed at $0.004232 / 1M tokens.
The AI/ML API endpoint lists text, image and video inputs and supports file input. Meta documents PDF support for Muse Ember. The model returns text.
Set reasoning_effort in the request to control how much reasoning the model uses. Test the setting on your own coding, routing or extraction tasks before using it across an agent workflow.
Yes. The capabilities listed for this endpoint are file input, reasoning, streaming, structured output, tools and vision.
Meta designed Muse Ember for repeated tool calls, coding subtasks, routing, extraction and long-document processing.
Use meta/muse-ember as the model parameter. Requests go to the OpenAI-compatible endpoint with your AI/ML API key.
Muse Ember accepts up to 1,048,576 tokens of context and returns up to 524,288 output tokens.