At a glance

StepFunpricing, performance & catalog

The citable facts about StepFun's 1 model — sourced from provider APIs and refreshed continuously.

Lowest price
Step-3.5-Flash at $0.100 per 1M input tokens
Highest throughput
Step-3.5-Flash at 150 tokens/s
Lowest latency
Step-3.5-Flash at 0.30s
Largest context
Step-3.5-Flash at 66K tokens
Catalog
1 active models from 1 organization

FAQ

Common questions about StepFun.

What is StepFun?

StepFun is an API provider that hosts large language models. Active models: 1; From (input): $0.10 / 1M tok; Avg throughput: 150 tok/s; Avg latency: 0.30 s; Max context: 66K.

How many models does StepFun offer?

StepFun currently serves 1 active models out of 1 historical offerings on LLM Stats.

What is StepFun's API pricing?

StepFun input pricing starts from $0.10 per 1M tokens, with the most expensive offering at $0.1 per 1M tokens. See the Pricing tab above for the full per-model breakdown.

How fast is StepFun?

StepFun averages 150 output tokens per second across its catalog, with average latency of 0.30s. Per-model performance is shown in the Performance tab.

Is StepFun OpenAI compatible?

Most providers expose an OpenAI-compatible /v1/chat/completions endpoint so you can switch from OpenAI to StepFun by changing only the base URL and API key. Check https://platform.stepfun.com for the exact endpoint format and any provider-specific parameters.

Does StepFun support multimodal models?

Yes. StepFun's catalog includes 1 vision-capable models. See the Models and Capabilities tabs for the full per-model breakdown.

Whose models does StepFun host?

StepFun hosts models from StepFun. See the Models tab for the full catalog grouped by creator.

How do I start using StepFun?

Sign up at https://platform.stepfun.com to get an API key, then call StepFun's API directly from your application. Most clients work out of the box by pointing the OpenAI SDK at StepFun's base URL with your key. Use the Pricing and Performance tabs above to pick the right model for your latency, cost, and context-window requirements.