Output tokens cost $6.00 per million on Grok 4.5 and $1.12 per million on Qwen3 235B A22B. Input tokens cost $2.00 per million on Grok 4.5 and $0.28 per million on Qwen3 235B A22B. Cached input tokens are billed at $0.50 per million on Grok 4.5 and $0.28 per million on Qwen3 235B A22B. Context lengths are 500,000 tokens on Grok 4.5 and 131,100 tokens on Qwen3 235B A22B. Time to first token (TTFT) measured on AIHubMix is 1.9s on Grok 4.5 and 0.6s on Qwen3 235B A22B. Measured output throughput is 26.7 tok/s on Grok 4.5 and 81.2 tok/s on Qwen3 235B A22B. On the LMArena coding leaderboard Grok 4.5 scores 1523 and Qwen3 235B A22B scores 1433.
Grok 4.5
Qwen3 235B A22BGrok 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.
Qwen3-235B-A22B is a massive 235B parameter Mixture-of-Experts (MoE) model that operates with the efficiency of a 22B model. Its standout feature is the ability to seamlessly switch between a "thinking" mode for complex reasoning and a "non-thinking" mode for fast conversation, offering both world-class power and practical speed.
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 235B A22B: $1.12/M output tokens; Grok 4.5: $6.00/M. Use the cost calculator above to estimate your own workload.
Grok 4.5: 1523; Qwen3 235B A22B: 1433 (LMArena coding leaderboard).
Qwen3 235B A22B: 0.6s 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 235B A22B accepts 131,100 input tokens. Maximum output per request is 500,000 tokens on Grok 4.5 and 128,000 tokens on Qwen3 235B A22B.
Qwen3 235B A22B at 81.2 tok/s and Grok 4.5 at 26.7 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 235B A22B accepts text 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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