StepFun: Step 5 Preview
UnavailableStep 5 Preview is StepFun's next-generation flagship foundation model for real-world tasks, with a focus on coding and professional knowledge work. It natively supports text, image, and video input, offers a 1M-token context window, and is well suited for workflows that require processing large amounts of information, using tools, and driving tasks through to deliverable results.
- By
StepFun
- Input
- Text, Image, Video
- Output
- Text
- Context
- 1M tokens
- Max output
- 1M tokens
- Published
- 2026-09-20
- Capabilities
- ReasoningMultimodalLong context
Providers
The provider that serves this model. Click the provider row to inspect live telemetry, pricing, and supported parameters.
| Provider | Input / 1M | Output / 1M | Context | Latency P50 | Throughput P50 | Success 24h |
|---|---|---|---|---|---|---|
Stepfun stepfun · offline | 55x Rp21.840/1M | 156x Rp62.400/1M | 1M | — | — | — |
Uptime
Share of requests that succeeded, per provider.
| 05:00 PM | no traffic |
|---|---|
| 06:00 PM | no traffic |
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| 04:00 PM | no traffic |
Last 24 hours, per hour. Measured from requests through Morphic; none yet.
Throughput
P50 output tokens per second, whole request.
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Last 24 hours, per hour. Measured from requests through Morphic; none yet.
Latency
P50 time to the full response.
| 05:00 PM | — |
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Last 24 hours, per hour. Measured from requests through Morphic; none yet.
Activity
Tokens processed per day over the last 30 days.
| Oct 4 | 0 |
|---|---|
| Oct 5 | 0 |
| Oct 6 | 0 |
| Oct 7 | 0 |
| Oct 8 | 0 |
| Oct 9 | 0 |
| Oct 10 | 0 |
| Oct 11 | 0 |
| Oct 12 | 0 |
| Oct 13 | 0 |
| Oct 14 | 0 |
| Oct 15 | 0 |
| Oct 16 | 0 |
| Oct 17 | 0 |
| Oct 18 | 0 |
| Oct 19 | 0 |
| Oct 20 | 0 |
| Oct 21 | 0 |
| Oct 22 | 0 |
| Oct 23 | 0 |
| Oct 24 | 0 |
| Oct 25 | 0 |
| Oct 26 | 0 |
| Oct 27 | 0 |
| Oct 28 | 0 |
| Oct 29 | 0 |
| Oct 30 | 0 |
| Oct 31 | 0 |
| Nov 1 | 0 |
| Nov 2 | 0 |
Counts every request routed through Morphic.
Related models
More models from StepFun
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Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parameters per token. It is a reasoning model that is incredibly speed efficient even at long contexts.