Model comparison · Updated May 2026
Gemini 2.5 Pro vs Qwen3 Max: Price, Context, Benchmarks (2026)
A direct, dated comparison of Gemini 2.5 Pro (Google) and Qwen3 Max (Alibaba). Every number below is sourced from official provider docs and public benchmarks. If you need to make this decision today, the verdict is at the top.
30-second verdict
- Cheaper: Qwen3 Max (input $1.00 vs $1.25 per 1M tokens).
- Longer context: Gemini 2.5 Pro at 2M vs 1M.
- Stronger on SWE-bench Verified: Gemini 2.5 Pro (~60% vs ~50%).
- Higher LMArena: Gemini 2.5 Pro (1420 vs 1410).
- Open weights: Qwen3 Max can be self-hosted.
Specs side-by-side
| Spec | Gemini 2.5 Pro | Qwen3 Max |
|---|---|---|
| Vendor | Alibaba | |
| Input price (per 1M tokens) | $1.25 | $1.00 |
| Output price | $10.00 | $4.00 |
| Context window | 2M | 1M |
| Release date | 2025-06-17 | 2025-09-05 |
| SWE-bench Verified | ~60% | ~50% |
| HumanEval | ~92% | ~91% |
| LMArena (approx) | 1420 | 1410 |
| Open weights | No | Yes |
| Capabilities | reasoning, code, vision | reasoning, code, vision |
Pricing from official Google and Alibaba docs. Benchmark numbers from SWE-bench Verified, HumanEval, and LMArena public leaderboards as of May 2026.
Gemini 2.5 Pro — strengths and weaknesses
Strengths. Largest context window (2M), strong multimodal, generous AI Studio free tier.
Weaknesses. Recall drops past 500K, weaker on agentic edits than Claude / GPT.
Best for. Whole-repo Q&A, long PDFs, multimodal, free prototyping.
Qwen3 Max — strengths and weaknesses
Strengths. Best Chinese-language quality, multilingual, 1M context, fast in Asia.
Weaknesses. Smaller English ecosystem, fewer integrations.
Best for. Chinese / multilingual products, Asia-region deployments, multilingual RAG.
Which one should you pick?
Pick Gemini 2.5 Pro if: whole-repo q&a, long pdfs, multimodal, free prototyping.
Pick Qwen3 Max if: chinese / multilingual products, asia-region deployments, multilingual rag.
Use both if: you're building an agent or content pipeline. Route the high-stakes / hard-reasoning calls to whichever scores higher on the axis you care about, and the bulk / cheap calls to the other. Most production AI products run a 2-3 model router rather than betting on one.
Try them side-by-side
The Check.AI comparison tool lets you put both models in one table with all the numbers, switch capability filters, and share the resulting URL with your team.