Compare Grok 4.5 from Grok and Qwen3 VL 235B A22B Instruct 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 VL 235B A22B InstructGrok 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 series open-source models include hybrid models, thinking models, and non-thinking models, with both reasoning capabilities and general abilities reaching industry SOTA levels at the same scale.
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 VL 235B A22B Instruct: $1.096/M output tokens; Grok 4.5: $6/M. Use the cost calculator above to estimate your own workload.
Qwen3 VL 235B A22B Instruct: 1.1s 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 VL 235B A22B Instruct accepts 131,072 input tokens. Maximum output per request is 500,000 tokens on Grok 4.5 and 32,768 tokens on Qwen3 VL 235B A22B Instruct.
Qwen3 VL 235B A22B Instruct at 57.0 tok/s and Grok 4.5 at 17.6 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 VL 235B A22B Instruct accepts text, image and video input and supports tool calling, function calling and structured outputs.
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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