Ultra-lightweight model with million-token context, optimized for speed and low latency, costing only $0.10 per million input tokens. It is suitable for edge computing and real-time interaction. The automatic caching mechanism offers a 75% cost reduction on cache hits.
GPT 4.1 Nano vs Step 3.7 Flash
Compare GPT 4.1 Nano from OpenAI and Step 3.7 Flash from StepFun on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
step-3.7-flash is stepfun's flagship inference model, designed for high-complexity tasks that require deep reasoning and fast execution. It excels at decomposing multi-step problems, performing tool calls, and maintaining consistency across massive datasets. It is the preferred choice for complex workloads such as long-context agents, advanced software engineering, and end-to-end research automation.
Pricing & Specifications
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Activity Past 30 Days
Daily traffic served through AIHubMix — how demand for each model is trending.
Tokens / day
Requests / day
Performance Past 3 Days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (tok/s)
TTFT (s)
Uptime (%)
Cost calculator
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: GPT 4.1 Nano, Step 3.7 Flash?
GPT 4.1 Nano: $0.4/M output tokens; Step 3.7 Flash: $1.32/M. Use the cost calculator above to estimate your own workload.
Which responds faster?
GPT 4.1 Nano: 0.8s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
How large is each context window?
GPT 4.1 Nano accepts 1,047,576 and Step 3.7 Flash accepts 256,000 input tokens.
Which one generates tokens faster?
GPT 4.1 Nano at 72.7 tok/s and Step 3.7 Flash at 32.6 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
What inputs and capabilities does each model support?
GPT 4.1 Nano accepts text, image and PDF input and supports tool calling, function calling, structured outputs and long context; Step 3.7 Flash accepts text, image and video input.
Can I call GPT 4.1 Nano and Step 3.7 Flash with the same API key?
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
Popular comparisons
Related model match-ups readers also look at.