StepFun API
Access StepFun instantly with Puter.js, and add AI to any app in a few lines of code without backend or API keys.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain AI like I'm five!", {
model: "stepfun/step-3.5-flash"
}).then(response => {
console.log(response);
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain AI like I'm five!", {
model: "stepfun/step-3.5-flash"
}).then(response => {
console.log(response);
});
</script>
</body>
</html>
List of StepFun Models
Step 3.7 Flash
stepfun/step-3.7-flash
Step 3.7 Flash is a multimodal Mixture-of-Experts model from StepFun, combining a 196B-parameter language backbone with a 1.8B vision encoder and activating roughly 11B parameters per token. It natively processes text and images, supporting a 256K-token context window. The model is designed for agentic coding, tool orchestration, long-context reasoning, and search-intensive workflows. It exposes tunable reasoning tiers (low, medium, high) so developers can trade inference cost against answer depth on a per-call basis. Compared to Step 3.5 Flash, Step 3.7 Flash adds native vision input, improves cross-harness consistency, and achieves stronger performance on coding agent and terminal benchmarks. It targets developers building production pipelines that combine perception, retrieval, and multi-step execution.
ChatStep 3.5 Flash
stepfun/step-3.5-flash
Step 3.5 Flash is an open-source reasoning model from StepFun, built on a sparse Mixture-of-Experts (MoE) architecture with 196B total parameters but only 11B active per token. It supports a 256K-token context window and native tool calling. The model is purpose-built for agentic and coding workflows, with generation throughput of 100–300 tokens/sec in typical usage. It scores 74.4% on SWE-bench Verified, 97.3 on AIME 2025, 86.4% on LiveCodeBench-V6, and 88.2 on τ²-Bench. Step 3.5 Flash is a strong choice for developers building AI agents, code assistants, or multi-step reasoning pipelines who need frontier-level intelligence at low per-token cost.
ChatStep3
stepfun-ai/step3
Step3 is a multimodal reasoning model from StepFun, built on a Mixture-of-Experts architecture with 321B total parameters and 38B active per token. It accepts both text and image inputs, making it suitable for vision-language tasks. The model is engineered for cost-effective decoding through two co-designed innovations: Multi-Matrix Factorization Attention (MFA) to reduce KV cache size, and Attention-FFN Disaggregation (AFD) for more efficient distributed inference. StepFun reports it achieves significantly higher tokens-per-GPU throughput than DeepSeek-V3 at comparable context lengths. Step3 targets use cases that require grounded multimodal reasoning — interpreting diagrams, documents, and images alongside text — with reduced hallucination.
Frequently Asked Questions
The StepFun API gives you access to models for AI chat. Through Puter.js, you can start using StepFun models instantly with zero setup or configuration.
Puter.js supports a variety of StepFun models, including Step 3.7 Flash, Step 3.5 Flash, and Step3. Find all AI models supported by Puter.js in the AI model list.
With the User-Pays model, users cover their own AI costs through their Puter account. This means you can build apps without worrying about infrastructure expenses.
Puter.js is a JavaScript library that provides access to AI, storage, and other cloud services directly from a single API. It handles authentication, infrastructure, and scaling so you can focus on building your app.
Yes — the StepFun API through Puter.js works with any JavaScript framework, Node.js, or plain HTML. Just include the library and start building. See the documentation for more details.