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Meta: Muse Image

来源介绍(英文)

Muse Image is an agentic image generation model from Meta that generates and edits images from text and reference images. Unlike single-pass image models, it reasons before it renders, breaking...

模型概览

模型规格

上下文
65,536 tokens
最大输出
58,982 tokens
架构
text+image->image
分词器
Other
知识截止时间
暂未提供
内容审核
是
OPENROUTER

完整价格

同步自 OpenRouter。Token 价格均按每百万 Token 展示。

图片输出
$0.01
每张图片
API

快速调用

在本地设置 OPENROUTER_API_KEY。Python 需安装 requests;JavaScript 在 Node.js 中运行。密钥应保存在服务端。

API 文档

curl --fail-with-body https://openrouter.ai/api/v1/images \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"meta/muse-image","prompt":"A sunlit mountain landscape"}'
能力与模态

输入 → 输出

输入
textimage
输出
image
API

支持的 API 参数

max_tokensrepetition_penaltytemperaturetop_ktop_p
可用提供方

1 提供方

核验日期: 2026年9月7日

在 OpenRouter 查看实时 Provider

Provider 可用性、延迟、吞吐量和路由会持续变化,请前往来源页面查看实时运行数据。

OpenRouter

Meta

暂未提供
上下文
66K
最大输出
59K
meta

4 个模型

全部模型
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Meta: Muse Spark Open

Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and deep codebase understanding across the repos developers...

上下文
1.0M
输入
text · image · video · file · audio
输出
text
输入: $1.25输出: $4.25每百万 Token
查看模型详情 →
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Meta: Muse Wonder

Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...

上下文
1.0M
输入
text · image · video · file · audio
输出
text
输入: $4输出: $20每百万 Token
查看模型详情 →
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Meta: Muse Voice Transcribe 1.0

Muse Voice Transcribe 1.0 is a synchronous speech-to-text model from Meta. It is suited for push-to-talk, endpointing, and speaker-aware transcription, with keyword biasing for domain terms and language biasing through...

上下文
暂未提供
输入
audio
输出
transcription
音频时长: $0.00005 每秒
查看模型详情 →
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Meta: Muse Spark 1.3 Contributor

Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...

上下文
1.0M
输入
text · image · video · file
输出
text
输入: $0.1输出: $0.2每百万 Token
查看模型详情 →