Requesty

stepfun/step-3.7-flash

Step 3.7 Flash is a fast reasoning model from StepFun with a 256K context window, supporting function calling and structured output for high volume agentic workloads.

ReasoningTool callingCaching
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Specifications

Context window262K tokens
Max output256K tokens
API typechat
AddedJul 24, 2026
Model IDnovita/stepfun/step-3.7-flash
Data retentionYes
Used for trainingUnknown
Provider location🇺🇸 US

Benchmarks

Released 2026-05-29
Coding Indexcoding
39.6%

Artificial Analysis Coding Index — a composite of coding evaluations including LiveCodeBench, SciCode and Terminal-Bench.

GPQA Diamondreasoning
80.9%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

Intelligence Indexreasoning
30.3%

Artificial Analysis Intelligence Index — a composite of multiple evaluations measuring overall model capability.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality. Always test on your own workload.

Pricing

Prices updated July 24, 2026
Input / 1M
$0.20
Output / 1M
$1.15
Cache write
N/A
Cache read / 1M
$0.04
Estimated cost
100K input + 10K output$0.0315
1M input + 100K output$0.32
10M input + 1M output$3.15

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to novita/stepfun/step-3.7-flash.

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from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="novita/stepfun/step-3.7-flash", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

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Frequently asked questions

How much does stepfun/step-3.7-flash cost?
stepfun/step-3.7-flash is priced at $0.20 per million input tokens and $1.15 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of stepfun/step-3.7-flash?
stepfun/step-3.7-flash has a context window of 262K tokens, with a maximum output of 256K tokens per response. That's roughly 350 words of input you can fit in a single prompt.
How does stepfun/step-3.7-flash perform on benchmarks?
stepfun/step-3.7-flash scores 98.5% on τ²-Bench, 80.9% on GPQA Diamond, 40.0% on SciCode. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can stepfun/step-3.7-flash do?
stepfun/step-3.7-flash supports tool calling, extended reasoning, prompt caching. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use stepfun/step-3.7-flash with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "novita/stepfun/step-3.7-flash". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run stepfun/step-3.7-flash through Requesty?
Yes. stepfun/step-3.7-flash runs through Requesty's OpenAI-compatible API, served from Novita AI. You do not host the model yourself: point base_url at Requesty, set the model to "novita/stepfun/step-3.7-flash", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access stepfun/step-3.7-flash through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

All Novita AI models