New Model Available: Meta: Muse Image 1.0

Meta has released Muse Image 1.0, an agentic image generation model that reasons before rendering, breaks down multi-part prompts, and invokes web search for factual accuracy. It supports text-to-image generation, targeted editing, multi-image composition, and precise text rendering, with iterative editing by passing previous outputs back with new instructions. The model is available via Meta's provider at $0.01 per count.

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 down multi-part prompts and refining its output within the chain of thought, and invokes web search for factual accuracy on knowledge-intensive prompts. The model supports text-to-image generation, targeted image editing, multi-image composition, reference-image conditioning for style and subject consistency across a series, and precise text rendering within generated images. Iterative editing works by passing the previous output image back with a new instruction. Route requests across multiple providers. Copy a provider slug to set your preference. ProviderCache Hit RateInputOutputCache readContextLatencyThroughput Meta meta --$0.01/countsRead:-/ M tokensWrite:-/ M tokens66K-- Uptime 24hours Direct request success rate on AI Gateway and per-provider. 1D1W Throughput 24hours P50 throughput on live AI Gateway traffic, in tokens per second TPS . 1D1W Latency 24hours P50 time to first token TTFT on live AI Gateway traffic, in milliseconds. 1D1W Activity Token volume and request traffic to this model over time. Token Consumption Apps Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for. View All