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fireworks · Frontier

Ember 1

Added Sep 24, 2026

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Use in the app

Fireworks Research reasoning model built on Kimi K3. It accepts text and images, supports tool calling and structured output, and has a 1M-token context window.

  • Reasoning
  • Tools
  • Vision
  • Structured output
Input
Text, Images
Output
Text
Reasoning effort
none · low · high · max
Discovery tier
Frontier

Pricing

USD per 1M tokens
Input
$3.00
Output
$15.00
Cache read
$0.30

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
—
Average output (7 days)
3.3K tokens
Longer than 97% of 473 models

Side by side

Ember 1 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Ember 1fireworksThis modelClaude Sonnet 4.6AnthropicRemove
ProviderfireworksAnthropic
Discovery tierFrontierFrontier
AddedSep 24, 2026Feb 17, 2026
Limits
Context window1.05MBest1M
Max output—128K
Average output3.3K tokens401 tokens
Pricing, USD per 1M tokens
Input$3.00$3.00
Output$15.00$15.00
Cache read$0.30$0.30
Performance
Throughput—87.7 tok/s
Time to first token—1.3 s
Request success (24h)—99.5%
Benchmark indexes
Intelligence Index—24.7
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputNoYes
Reasoning effortnone, low, high, maxlow, medium, high, xhigh, max

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Ember 1
  • Claude Sonnet 4.6

Intelligence Index

  • Ember 1—
  • Claude Sonnet 4.624.7
3.8Catalog models by score55.1

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Ember 1: —
    • Claude Sonnet 4.6: 68.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Ember 1: —
    • Claude Sonnet 4.6: 13.3%
  • GPQA Diamond

    Graduate-level science questions

    • Ember 1: —
    • Claude Sonnet 4.6: 79.9%
  • IFBench

    Following precise output instructions

    • Ember 1: —
    • Claude Sonnet 4.6: 41.2%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Ember 1: —
    • Claude Sonnet 4.6: 46.2%
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Ember 1: —
    • Claude Sonnet 4.6: 79.5%
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Ember 1: —
    • Claude Sonnet 4.6: 68.3%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
82.4%
About $0.77 per 1M input tokens with caching

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "fireworks/ember-1",
    "reasoning_effort": "none",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="fireworks/ember-1",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)