Muse Ember on Vercel AI Gateway

Muse · AI at Meta

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Last refreshed 2026-11-10. Next refresh: weekly.

Why use Muse Ember on Vercel AI Gateway?

Vercel AI Gateway offers Muse Ember with pay-as-you-go pricing at $0.10/1M input tokens. Vercel AI Gateway is a unified AI proxy providing a single OpenAI-compatible API endpoint to 275+ models from 25+ providers including Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, xAI, Alibaba, Amazon, ByteDance, Cohere, MiniMax, MoonshotAI, KwaiPilot, Black Forest Labs, Recraft, Voyage AI, NVIDIA, and more.

Compare Muse Ember across 3 providers to find the best fit for your use case
Input / 1M
$0.10
Output / 1M
$0.50
Cache
read $0.004
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install openai
Auth
export AI_GATEWAY_API_KEY=...
Call
import os
from openai import OpenAI
client = OpenAI(
    api_key=os.environ["AI_GATEWAY_API_KEY"],
Model ID
meta/muse-ember

Request example

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AI_GATEWAY_API_KEY"],
    base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
    model="meta/muse-ember",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Gotchas

  • Use provider model ID "meta/muse-ember", not the LLMReference slug "muse-ember".
  • creator/model-name e.g. kwaipilot/kat-coder-pro-v2
  • The examples expect AI_GATEWAY_API_KEY; rename it only if your application config maps the new variable.

Compare Muse Ember Across Providers

ProviderInput (per 1M)Output (per 1M)
Meta Model API$0.10$0.50
OpenRouter$0.10$0.50
Vercel AI Gateway$0.10$0.50

Pricing

TypePrice (per 1M)
Input tokens$0.10
Output tokens$0.50

Capabilities

VisionMultimodalReasoningJSON / Tool usePrompt CachingAudioVideo

About Muse Ember

Muse Ember is Meta Superintelligence Labs' smallest and most efficient Muse model, introduced November 9, 2026, for the work agents repeat all day: tool calls, coding subtasks, routing, extraction and long-document parsing. Meta says it is the first model trained using Muse Wonder Full. It takes text, image, audio and video input and returns text, with a 1M-token context window and up to 512K output tokens, and supports the Responses API.

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