Ember-1

Fireworks AI

Ember-1 is a Fireworks Research specialized reasoning model built on Moonshot's Kimi K3 that shortens reasoning traces by roughly 40% while matching K3-max quality on Fireworks' internal evaluations. It is a mixture-of-experts model with 2.78T parameters, a 1.04M-token context, and function calling, offered as a Research Preview on Fireworks Serverless under the model path `accounts/fireworks/models/ember-1`. List pricing is $3.00 input / $0.30 cached input / $15.00 output per million tokens, the same as public Kimi K3 API pricing. The four catalog scores are self-reported from the Fireworks launch blog (Terminal-Bench 2.1 82.0%, SWE-bench Verified 92.2%, DeepSWE 1.1 75.2%, tau2-bench Airline 66%).

Key Specifications

Parameters
2.8T
Context
1.0M
Release Date
September 23, 2026
Average Score
78.8%

Timeline

Key dates in the model's history
Announcement
September 23, 2026
Last Update
October 8, 2026
Today
October 12, 2026

Technical Specifications

Parameters
2.8T
Training Tokens
-
Knowledge Cutoff
-
Family
-
Fine-tuned from
kimi-k3
Capabilities
MultimodalZeroEval

Pricing & Availability

Input (per 1M tokens)
$3.00
Output (per 1M tokens)
$15.00
Max Input Tokens
1.0M
Max Output Tokens
-
Supported Features
Function CallingStructured OutputCode ExecutionWeb SearchBatch InferenceFine-tuning

Benchmark Results

Model performance metrics across various tests and benchmarks

Programming

Programming skills tests
SWE-Bench Verified
Fireworks launch blog industry-benchmark table; Ember-1 column; N=500 • Self-reported
92.2%

Other Tests

Specialized benchmarks
DeepSWE 1.1
Fireworks launch blog industry-benchmark table; Ember-1 column; N=113 • Self-reported
75.2%
Tau2 Airline
Fireworks launch blog industry-benchmark table; tau-2 Bench Airline; Ember-1 column; N=50 • Self-reported
66.0%
Terminal-Bench 2.1
Fireworks launch blog industry-benchmark table; Ember-1 column; N=89 • Self-reported
82.0%

License & Metadata

License
proprietary
Announcement Date
September 23, 2026
Last Updated
October 8, 2026

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