Step 3.7 Flash is a fast, low-cost model optimized for high-throughput chat and bulk processing. Reach for it when you need to handle text, image, or video inputs at scale with tool calling and reasoning enabled.
Modalities
Text+Image → Text
Below release
fp8
Weights
Published
stepfun-ai/Step-3.7-Flash
Where it sits in the catalogue Kyma measures
Every number against every text model Kyma prices per token — a stated rule, not a chosen line-up.
$0.27
output $1.553 · cached $0.054
median $0.977 · best $0.0494
$1.553
per 1M tokens generated
median $3.4515 · best $0.2164
98.41%
439 observations since 2026-06-10
median 93.8% · best 100.0%
51.4 tok/s
probe median, one fixed prompt
median 39.4 tok/s · best 314.6 tok/s
2.91 s
probe median, to a complete answer
median 2.53 s · best 0.84 s
256K
max output 8,192
published by StepFun, not measured here
Tick above each rail is this model, below it the other 69. Dashed rule is the field median, solid is its best. Better is left; the axis stops at the 90th percentile, so a few models sit past its right edge.
Usage
How much this model is actually called here.
Rank
#83
of 117 active models
Tokens served
24.4K
all-time
Platform share
0.0%
of all tokens
Pricing
Pay per token. Cached input bills at this model’s own cached rate, listed below.
+ Estimate your workload− Estimate your workload
Estimated monthly cost
$35.61
$1.19 / day on Step 3.7 Flash
Same workload on:
Estimates use list pricing with cached input at this model's own cached rate. Actual bills depend on real token counts, and every response includes its exact cost.
When to use Step 3.7 Flash
Where this model earns its cost — and where it doesn't.
Created by stepfun, it supports a 256,000-token context window and accepts text, image, and video inputs while returning text. It includes native support for tool calling, reasoning, and structured outputs.
On Kyma, requests are routed through an OpenAI-compatible endpoint with automatic failover if a serving path degrades. Prompt prefixes are cached at this model's cached input rate.
The model caps output at 8,192 tokens, making it suitable for conversational and extraction workflows rather than long-form generation.
Bulk Chat Processing
Route high-volume conversational workloads with low latency and minimal overhead.
Multimodal Input Analysis
Extract information from text, images, and video streams in a single request.
Tool-Driven Workflows
Execute function calls and structured data extraction for automated pipelines.
Long-Context Summarization
Process documents up to 256K tokens while maintaining fast response times.
Not ideal for: It is not suited for tasks requiring outputs longer than 8,192 tokens or heavy creative writing where maximum reasoning depth is prioritized over speed and cost.
How it compares
Against the peers people actually weigh it against.
| Spec | Step 3.7 Flash | Qwen 3.8 27B | Llama 4 Maverick |
|---|---|---|---|
| Input /1M | $0.27 | $0.567 | $0.27 |
| Output /1M | $1.553 | $4.05 | $1.08 |
| Context | 256K | 1M | 1M |
| Tools | Yes | Yes | Yes |
| Reasoning | Yes | Yes | No |
| Throughput | 51.4 tok/s | 45.1 tok/s | 35.7 tok/s |
Quick start
Up and running in under two minutes.
- 1
Create an API key
Sign up and grab a key from the dashboard — $0.50 free credit on the free tier, which covers Step 3.7 Flash. No card required.
Get API key → - 2
Make your first request
Drop in your key and send a chat completion — fully OpenAI-compatible.
curl https://kymaapi.com/v1/chat/completions \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "step-3.7-flash", "messages": [ {"role": "user", "content": "Explain prompt caching in one paragraph."} ] }' - 3
Stream responses
Add
"stream": trueto receive tokens as they arrive.curl https://kymaapi.com/v1/chat/completions \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "step-3.7-flash", "stream": true, "messages": [{"role": "user", "content": "Hello!"}] }'
FAQ
Common questions about this model.