Compare Grok 4.5 from Grok and Qwen3.8 27B from Qwen on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
Grok 4.5
Qwen3.8 27BGrok 4.5 was trained on datasets spanning knowledge in coding, science, engineering, and math. With both intelligent and efficient reasoning, Grok 4.5 excels at real engineering tasks and exceeds comparable leading models at these tasks.
qwen3.8-27b is Qwen's open-weight dense vision-language model, designed for coding, professional workflows, research, multimodal interaction, and long-running agent tasks. It supports text and image inputs with an extensive 1,000,000-token context length and flexible thinking capabilities.
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.
Daily traffic served through AIHubMix — how demand for each model is trending.
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
Qwen3.8 27B: $2.5/M output tokens; Grok 4.5: $6/M. Use the cost calculator above to estimate your own workload.
Grok 4.5 accepts 500,000 and Qwen3.8 27B accepts 1,000,000 input tokens. Maximum output per request is 500,000 tokens on Grok 4.5 and 131,072 tokens on Qwen3.8 27B.
Grok 4.5 accepts text and image input and supports thinking, tool calling, function calling, structured outputs and long context; Qwen3.8 27B accepts text, image and video input.
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