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Muse Ember

text+image+file+audio+video->text

Muse Ember is a general-purpose chat-tuned model. Available via Meta. 1,048,576-token context. Efficient pricing.

Muse Ember is a multimodal AI model from Meta. It costs $0.1000 per million input tokens and $0.5000 per million output tokens (blended $0.2200/M), with a 1,048,576-token context window.

Modalities text, vision, audio, videoAPI docs ↗Pricing source ↗Compare with another model →Estimate monthly cost →

RatesUSD per million tokens. Blend is 70% input, 30% output, our calculation.

INPUT
$0.1000/M
per million input tokens
OUTPUT
$0.5000/M
per million output tokens
BLENDED 70/30
$0.2200/M
unchanged since 3 May
default reference rate · how it is calculated →
CONTEXT
1,048,576
tokens

From OpenRouter's listing, read on 11 Nov 2026.

What it is good at
  • Solid general chat performance
  • Reasonable instruction following
  • Multimodal: handles images alongside text
Typical use cases
  • General chat
  • Drafting and rewriting
  • Personal productivity

Benchmarks

No published benchmark scores tracked for this model yet. Frontier and reasoning models from major providers have scores; smaller models and inference-host variants typically inherit the underlying open-weights score.

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Llama 4 Scout
Efficient · 512,000 ctx
in $0.1000/Mout $0.3000/M
Llama 3.3 70B
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in $0.2300/Mout $0.4000/M
Llama 3.1 405B
Large · 128,000 ctx
in $0.8000/Mout $0.8000/M
Llama 3.1 70B
Balanced · 128,000 ctx
in $0.3500/Mout $0.4000/M

Frequently asked questions

How much does Muse Ember cost?

Muse Ember costs $0.1000 per million input tokens and $0.5000 per million output tokens, for a blended reference rate of $0.2200 per million tokens.

What is Muse Ember's context window?

Muse Ember supports up to 1,048,576 tokens of context in a single request.

What is Muse Ember best for?

Muse Ember is well suited to Solid general chat performance, Reasonable instruction following and Multimodal: handles images alongside text.

Who makes Muse Ember?

Muse Ember is developed and served by Meta.

Terms used on this page

Full glossary →
TokenInput tokensOutput tokensPrice per million tokensContext windowPrompt cachingBatch APIBlended cost