Meta / meta/muse-ember-1.0

Muse Ember - access through LLMTR

Muse Ember is Meta's small reasoning model for repeated, bounded work: coding subtasks, tool calls, routing, and document summarization and extraction. It has a 1,048,576-token context window, accepts image, video and PDF alongside text, and returns tool calls, JSON or schema-conforming output. It reasons before every answer and this cannot be turned off; set `reasoning_effort` to minimal, low, medium, high, xhigh or max. Without the field it runs at max, so send `minimal` or `low` for bulk work. Reasoning tokens are billed as output inside `completion_tokens`. A request with more than 200,000 input tokens is billed entirely at the long-context rate. `tool_choice` accepts only `auto`.

Technical specifications

Canonical IDmeta/muse-ember-1.0
ProviderMeta
Context window1,048,576 tokens
OperationsCHAT_COMPLETIONS
Modalitiestext, image, video

Pricing

An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.

OperationMetricUnitPrice
CHAT_COMPLETIONSINPUT_TEXTPER_1M_TOKENS$0.100000
CHAT_COMPLETIONSCACHE_READPER_1M_TOKENS$0.004000
CHAT_COMPLETIONSOUTPUT_TEXTPER_1M_TOKENS$0.500000

Example usage

With existing OpenAI SDK flows, change only the base URL and model identifier.

curl https://llmtr.com/v1/chat/completions   -H "Authorization: Bearer llmtr-your_key"   -H "Content-Type: application/json"   -d '{"model":"meta/muse-ember-1.0","messages":[{"role":"user","content":"Hello"}]}'

Related models