by MetaFast
Muse Ember
Meta’s efficient Muse model for high-volume agent work — sub-agent tasks, tool loops, routing, extraction, and long-document parsing. Multimodal (text, image, video, audio, PDF) with 1M context; pair with Muse Wonder or Spark when a larger model plans and Ember executes at scale. Long-context surcharge applies above 200K input tokens on Meta’s API.
muse-emberGenerate chat completions with this model.
/api/v1/chat/completionsGET /api/v1/models?type=chat{
"model": "muse-ember",
"messages": [
{
"role": "user",
"content": "Hello!"
}
],
"stream": false,
"thinking": true,
"max_tokens": 4096
}curl -X POST https://kunya.ai/api/v1/chat/completions \
-H "Authorization: Bearer kunya_YOUR_API_KEY" \
-H "Content-Type: application/json"
-d '{"model":"muse-ember","messages":[{"role":"user","content":"Hello!"}],"stream":false,"thinking":true,"max_tokens":4096}'Qwen
Fast vision-language reasoning model — multimodal agents, visual coding, search, and computer interaction with 1M context. Web search via Kunya tools + smart-search fallback when native tool calls stall.
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