Compare Grok 4.5 from Grok and Qwen3.5 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
Qwen3.5 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 Qwen 3.5 native vision-language Plus model is built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In multiple task evaluations, the 3.5 series has demonstrated outstanding performance comparable to current leading frontier models, with leapfrog improvements over the 3 series in both pure-text and multimodal capabilities. This model version is functionally equivalent to the snapshot model qwen3.5-plus-2026-02-15.
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.
LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.
Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
Qwen3.5 27B: $0.6768/M output tokens; Grok 4.5: $6/M. Use the cost calculator above to estimate your own workload.
Grok 4.5: 1523; Qwen3.5 27B: 1450 (LMArena coding leaderboard).
Qwen3.5 27B: 1.7s 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 Qwen3.5 27B accepts 991,000 input tokens. Maximum output per request is 500,000 tokens on Grok 4.5 and 64,000 tokens on Qwen3.5 27B.
Grok 4.5 at 31.5 tok/s and Qwen3.5 27B at 25.1 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; Qwen3.5 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.
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