Gemini 2.5 Pro vs Qwen3-Max
Gemini 2.5 Pro (2025) and Qwen3-Max (2026) are compact production models from Google DeepMind and Alibaba. Gemini 2.5 Pro ships a 1M-token context window, while Qwen3-Max ships a 128K-token context window. On SWE-bench Verified, Qwen3-Max leads by 15.6 pts. On pricing, Qwen3-Max costs $0.78/1M input tokens versus $1.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3-Max is ~60% cheaper at $0.78/1M; pay for Gemini 2.5 Pro only for coding workflow support.
Specs
| Released | 2025-06-17 | 2026-01-15 |
| Context window | 1M | 128K |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-01 | 2025-12 |
Pricing and availability
| Gemini 2.5 Pro | Qwen3-Max | |
|---|---|---|
| Input price | $1.25/1M tokens | $0.78/1M tokens |
| Output price | $10/1M tokens | $3.9/1M tokens |
| Providers |
Capabilities
| Gemini 2.5 Pro | Qwen3-Max | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Qwen3-Max |
|---|---|---|
| SWE-bench Verified | 63.2 | 78.8 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has Gemini 2.5 Pro at 63.2 and Qwen3-Max at 78.8, with Qwen3-Max ahead by 15.6 points. The largest visible gap is 15.6 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on code execution: Gemini 2.5 Pro. Both models share vision, multimodal input, function calling, and tool use, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Gemini 2.5 Pro lists $1.25/1M input and $10/1M output tokens, while Qwen3-Max lists $0.78/1M input and $3.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-Max lower by about $2.16 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Qwen3-Max when vision-heavy evaluation and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemini 2.5 Pro or Qwen3-Max?
Gemini 2.5 Pro supports 1M tokens, while Qwen3-Max supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemini 2.5 Pro or Qwen3-Max?
Qwen3-Max is cheaper on tracked token pricing. Gemini 2.5 Pro costs $1.25/1M input and $10/1M output tokens. Qwen3-Max costs $0.78/1M input and $3.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Qwen3-Max open source?
Gemini 2.5 Pro is listed under Proprietary. Qwen3-Max is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemini 2.5 Pro or Qwen3-Max?
Both Gemini 2.5 Pro and Qwen3-Max expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Gemini 2.5 Pro or Qwen3-Max?
Both Gemini 2.5 Pro and Qwen3-Max expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Gemini 2.5 Pro and Qwen3-Max?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Qwen3-Max is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.