Compare Qwen3 235B A22B Thinking 2507 from Qwen 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.
Qwen3 235B A22B Thinking 2507
Step 3.7 FlashThe open-source thinking model based on Qwen3 has significantly improved in logical ability, general capability, knowledge enhancement, and creative ability compared to the previous version (Tongyi Qianwen 3-235B-A22B). It is suitable for high-difficulty and strong reasoning scenarios.
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.
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
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Step 3.7 Flash: $1.32/M output tokens; Qwen3 235B A22B Thinking 2507: $2.8/M. Use the cost calculator above to estimate your own workload.
Qwen3 235B A22B Thinking 2507: 0.3s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
Qwen3 235B A22B Thinking 2507 accepts 262,144 and Step 3.7 Flash accepts 256,000 input tokens.
Qwen3 235B A22B Thinking 2507 at 87.4 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.
Qwen3 235B A22B Thinking 2507 accepts text and image input and supports thinking, tool calling, function calling and structured outputs; Step 3.7 Flash accepts text, image and video input.
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