StepfunbalancedVisionTool use

Step 5 Preview

Step 5 Preview is StepFun's flagship model for agentic work, built on a sparse Mixture-of-Experts architecture (27B active / 600B total parameters). It performs strongly in software engineering and professional...

1M context·~750K words·64K max output

View context details Compare with Jp Anthropic Claude Sonnet 4 6

Context window1Mtokens

Max output64Ktokens

Context window

This model accepts 1M tokens in one request (~750K words of text).

Context window size1M tokens

4K32K128K1M10M

What fits in one request

Short document
About 1,500 words of text
Fits
Long document
About 37K words of text
Fits
Small codebase
About 150K words of text
Fits
Full novel
About 375K words of text
Fits

Specifications

Context size, pricing, and release info in one place.

Context window: 1,000,000 tokens (1M)
Max output tokens: 64,000 tokens (64K)
Speed tier: balanced
Provider: Stepfun
Release date: Oct 2026

Capabilities

See which features this model supports, such as vision, tools, and streaming.

Supported (6)

Vision: Accepts image inputs alongside text; Supported
Tool use: Can call external tools and APIs; Supported
Function calling: Structured function call interface; Supported
Extended thinking: Shows its chain-of-thought reasoning; Supported
Streaming: Returns tokens as they are generated; Supported
Prompt caching: Reuse repeated prompt prefixes cheaply; Supported

Not supported (2)

Web search: Can browse the web during a request; Not supported
Batch API: Process many requests asynchronously; Not supported

Best for

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Reasoning AI agents Multimodal Long documents RAG

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Frequently asked questions

Short answers about context size and how this model behaves.

Step 5 Preview has a context window of 1M tokens (1,000,000 tokens). This million-token window can process entire codebases, long legal documents, or book-length texts in a single pass.

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Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

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Example: a multi-turn chat session

Without Mem0~128K tokens sent

Full history

Repeated info

Old context

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Key memories

Current turn

80% less to send — works with any model