Ember-1 overview
Ember-1 by Fireworks
Ember-1 API: Fireworks Research's reasoning model built on Kimi K3, with a 1,048,576-token context window and shorter reasoning traces.
Ember-1 specs
- Model ID
fireworks/ember-1- Developer
- Fireworks
- Context window
- 1,048,576 tokens
- Max output
- 943,718 tokens
- Input
- Image, Text
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
What Is Ember-1?
Ember-1 is a specialised reasoning model from Fireworks Research, built on top of Kimi K3. Its design goal is narrow and concrete: make every token go further by producing shorter reasoning traces. A reasoning model bills its thinking tokens at the output rate, so a model that reaches the same answer with less deliberation costs less per task even at the same headline price.
It inherits Kimi K3's long context, 1,048,576 tokens in, up to 943,718 out, and accepts images alongside text.
Technical Reference
- Base model: Kimi K3 (Moonshot AI)
- Release date: 23 September 2026
- Endpoint: POST /v1/chat/completions
- Context window: 1,048,576 tokens
- Modalities: Image, Text → Text
- Capabilities: reasoning, tool calling, structured output, streaming, vision
What Ember-1 Brings to the Table
Shorter reasoning traces
The model is tuned to think less per answer rather than to think better. On a reasoning workload the thinking tokens are usually the bulk of the bill, so trace length is the lever that moves cost.
Kimi K3's context, unchanged
A 1,048,576-token window holds whole repositories or document sets in one request, with room for very long replies.
Agentic plumbing
Tool calling, structured output and streaming are all supported, alongside image input.
Where Ember-1 Makes the Most Sense
High-volume reasoning
Pipelines that run many reasoning calls, where the thinking-token bill decides whether the workload is viable.
Long-context analysis
Repository-scale code review and long-document research in a single request.
Agent loops
Multi-step work that plans, calls tools and checks itself, where every step pays for its own reasoning.
Use cases
- High-volume reasoning where thinking tokens dominate the bill
- Repository-scale code review and refactoring
- Long-document research and extraction
- Agent loops that reason at every step
Capabilities
- Reasoning
- Function calling
- Streaming
- Structured outputs
- Vision
Ember-1 API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $3.17 | 1M tokens |
| Output | $15.87 | 1M tokens |
| Cached input | $0.3174 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
Ember-1 vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
| $3.17 | $15.87 | |
| $3.17 | $15.87 | |
| $3.17 | $15.87 | |
| $5.29 | $15.87 | |
| $8.46 | $15.87 |
How to use the Ember-1 API
View docsBuild with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "fireworks/ember-1",
"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": "fireworks/ember-1",
"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": "fireworks/ember-1",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Ember-1 FAQ
What is Ember-1?
Ember-1 is a reasoning model from Fireworks Research, built on Moonshot AI's Kimi K3. It is tuned to produce shorter reasoning traces, to reach an answer while spending fewer thinking tokens on the way there.
How much does the Ember-1 API cost?
Ember-1 costs $3.17 input and $15.87 output per 1M tokens on AI/ML API, billed as you go with no subscription.
What is the context window of Ember-1?
1,048,576 tokens in and up to 943,718 tokens out, inherited from Kimi K3, enough for repository-scale code and very long replies in a single request.
How do I call Ember-1 through the API?
Send a POST request to https://api.aimlapi.com/v1/chat/completions with fireworks/ember-1 as the model id and your AI/ML API key in the Authorization header. The endpoint is OpenAI-compatible, so an existing chat client only needs the base URL swapped.
What is the Ember-1 model ID?
Use fireworks/ember-1 as the model parameter. Requests go to the OpenAI-compatible endpoint with your AI/ML API key.