Gemini 2.5 Pro vs Qwen3.8 Max (0902)
Which is better for the money: Gemini 2.5 Pro by Google or Qwen3.8 Max (0902) by Alibaba? Intelligence, total benchmark cost, and end-to-end time from Artificial Analysis & other sources, snapshot 2026-10-25.
Trade-off
Verdict
Depends on your budget
Qwen3.8 Max (0902) scores 29.3 points higher (45.4 vs 16.1) but costs 6.0× as much to run the benchmark ($4935 vs $823; flagship vs premium cost classes). They are not alternatives at one budget: pick Qwen3.8 Max (0902) when you need intelligence above 16.1, and Gemini 2.5 Pro when 16.1 is enough.
| Metric | Gemini 2.5 Pro | Qwen3.8 Max (0902) | Difference |
|---|---|---|---|
| Intelligence (higher is better) | 16.1 | 45.4 | +182.0% Qwen3.8 Max (0902) is 2.8× more intelligent |
| Total AA cost (lower is better) | $822.85 | $4,934.79 | +499.7% Qwen3.8 Max (0902) is 6.0× more expensive |
| End-to-end time (lower is better) | 27.19s | 65.39s | +140.5% Qwen3.8 Max (0902) is 140.5% slower |
| Price per 1M tokens (in / out) | $1.25 / $10.0 | $2.00 / $6.00 | |
| Input modalities | Text, Image, Speech, Video | Text, Image |
Qwen3.8 Max (0902) vs Gemini 2.5 Pro: 182.0% more intelligence, 499.7% more cost to run the AA benchmark, and 140.5% slower end-to-end.
Today's Pareto frontier
Against the frontier
- Gemini 2.5 Pro is off the frontier: at the same or lower cost, GPT-6.1 Sol (Xhigh) scores 51.00 for $662.
- Qwen3.8 Max (0902) is off the frontier: at the same or lower cost, Claude Opus 5.5 (Xhigh, Default Fallback) scores 56.00 for $4057.
Gemini 2.5 ProQwen3.8 Max (0902)Today's Pareto frontierEvery other model
Matchup
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Accept: text/markdown or ?format=md returns this page as Markdown. JSON: /api/v1/compare/gemini-2-5-pro/qwen3-8-max · Markdown: /api/v1/compare/gemini-2-5-pro/qwen3-8-max?format=md · llms.txt · agent skill