StepFunStep 1X Edit V1p1 Diffusers
Step 1X Edit V1p1 Diffusers is an open-source image editing model developed by StepFun. It performs image editing based on user instructions, leveraging a MLLM for instruction parsing and a DiT-based network for image generation.
Input
Output
Context
-
Max Output
n/a
Parameters
12.4B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Estimated GPU requirements for Step 1X Edit V1p1 Diffusers
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Step 1X Edit V1p1 Diffusers
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
StepFun has not published a context window for Step 1X Edit V1p1 Diffusers, so the catalog shows it as not available rather than estimating one.
Yes. Step 1X Edit V1p1 Diffusers is an open-weight model released under the Apache 2.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Step 1X Edit V1p1 Diffusers accepts Image and produces Image. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Step 1X Edit V1p1 Diffusers is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Step 1X Edit V1p1 Diffusers is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 12.7 GB at INT8 for the weights and a default context, from the catalog's 12.4B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Nov 4, 2026
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