LLM Reference

StepFun

Researched 2d ago
RAGAgentsLong contextVisionJSON / Tool use

StepFun exposes 3 tracked models (0 with output token pricing in seed data). Task coverage across this catalog includes rag, agents, and long context; open any model detail page for benchmarks, batch tiers, and migration prompts.

Portfolio context: 5 decision-task tags, 3 catalog rows, latest research stamp 2026-05-19.

Use this portfolio page for

  • Operators routing rag, agents, and long context workloads through this API

Do not stop here for

  • Final benchmark picks without opening the relevant model detail page
  • Strict price-per-token comparisons until output pricing is sourced

Catalog rows

3

Models linked to this provider in seed data

Priced output routes

0

Add output pricing to unlock comparisons

Cheapest output

Unknown

Need positive token_out rows

Batch-ready SKUs

0

No batch pricing tracked

Latest catalog ship

2024-09-01

627d since dated release field

Freshness

2026-05-19

Researched 2d ago

fresh

Catalog release signal

Latest ISO-dated model.release in this catalog is 2024-09-01 (627d ago).

Where this host wins

  • RAG: 1 tracked model with ruler / needle retrieval benchmarks.
  • Agentic: 1 tracked model with BFCL, tau-bench, and SWE-bench tool-use coverage.
  • Long-context: 3 tracked models with context-token or InfiniteBench-class signal.
  • Vision: 2 tracked models with multimodal benchmark coverage.

Getting started

Official entry points from seed metadata — confirm quotas and regions in vendor docs.

Compliance notes (verbatim seed excerpts)

Not yet verified from seed copy — no SOC/ISO/HIPAA-class sentences detected to quote verbatim.

Platform Overview

StepFun is a Chinese AI company providing API access to its Step series of large language and multimodal models.

Available Models(3)

View all →

All models available as Serverless

Contact provider for pricing

Platform Details

Models3

Organization

StepFun is a Chinese AI company providing API access to its Step series of large language and multimodal models.

Read more →

Links

Website