Compare Qwen/Qwen2.5-VL-32B-Instruct 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.
Qwen/Qwen2.5-VL-32B-Instruct
Step 3.7 FlashQwen2.5-VL-32B-Instruct is an advanced multimodal model from the Tongyi Qianwen team that can recognize objects, analyze text and graphics in images, operate tools, locate objects in images, and generate structured outputs. Through reinforcement learning, it has improved mathematics and problem-solving capabilities, with a more concise and natural response style.
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.
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Qwen/Qwen2.5-VL-32B-Instruct: $0.24/M output tokens; Step 3.7 Flash: $1.32/M. Use the cost calculator above to estimate your own workload.
Qwen/Qwen2.5-VL-32B-Instruct accepts text, image and video input and supports tool calling, function calling and structured outputs; Step 3.7 Flash accepts text, image and video input.
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