Compare Grok 4.5 from Grok and Qwen3.6 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
Qwen3.6 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.
The Qwen3.6 series 27B native vision-language Dense model. Compared with the 3.5-27B, the model notably improves Agentic coding capability and further enhances STEM and reasoning abilities; on the visual modality side, spatial intelligence, object localization and detection capabilities are significantly strengthened, and video understanding, document OCR, and visual agent capabilities have steadily improved.
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.
Qwen3.6 27B: $2.53/M output tokens; Grok 4.5: $6.00/M. Use the cost calculator above to estimate your own workload.
Qwen3.6 27B: 1.0s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
Grok 4.5 accepts 500,000 and Qwen3.6 27B accepts 254,000 input tokens. Maximum output per request is 500,000 tokens on Grok 4.5 and 64,000 tokens on Qwen3.6 27B.
Qwen3.6 27B at 41.0 tok/s and Grok 4.5 at 25.6 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
Grok 4.5 accepts text and image input and supports thinking, tool calling, function calling, structured outputs and long context; Qwen3.6 27B accepts text, image and video input and supports tool calling, function calling, structured outputs, web search, long context and thinking.
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.
Related model match-ups readers also look at.
AIHubMix