Gemini 2.5 Pro vs Qwen3.5-397B-A17B
Gemini 2.5 Pro (2025) and Qwen3.5-397B-A17B (2026) are general-purpose language models from Google DeepMind and Alibaba. Gemini 2.5 Pro ships a 1M-token context window, while Qwen3.5-397B-A17B ships a 262K-token context window. On MMLU PRO, Qwen3.5-397B-A17B leads by 1.6 pts. On pricing, Qwen3.5-397B-A17B costs $0.39/1M input tokens versus $1.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3.5-397B-A17B is ~221% cheaper at $0.39/1M; pay for Gemini 2.5 Pro only for coding workflow support.
Specs
| Released | 2025-06-17 | 2026-02-16 |
| Context window | 1M | 262K |
| Parameters | — | 397B |
| Architecture | decoder only | MoE |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | 2025-01 | - |
Pricing and availability
| Gemini 2.5 Pro | Qwen3.5-397B-A17B | |
|---|---|---|
| Input price | $1.25/1M tokens | $0.39/1M tokens |
| Output price | $10/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Gemini 2.5 Pro | Qwen3.5-397B-A17B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Qwen3.5-397B-A17B |
|---|---|---|
| MMLU PRO | 86.2 | 87.8 |
| Google-Proof Q&A | 86.4 | 89.3 |
Deep dive
On shared benchmark coverage, MMLU PRO has Gemini 2.5 Pro at 86.2 and Qwen3.5-397B-A17B at 87.8, with Qwen3.5-397B-A17B ahead by 1.6 points; Google-Proof Q&A has Gemini 2.5 Pro at 86.4 and Qwen3.5-397B-A17B at 89.3, with Qwen3.5-397B-A17B ahead by 2.9 points. The largest visible gap is 2.9 points on Google-Proof Q&A, 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 vision: Gemini 2.5 Pro, function calling: Gemini 2.5 Pro, tool use: Gemini 2.5 Pro, and code execution: Gemini 2.5 Pro. Both models share multimodal input and structured outputs, 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 Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-397B-A17B lower by about $2.9 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 Qwen3.5-397B-A17B when provider fit 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 Qwen3.5-397B-A17B?
Gemini 2.5 Pro supports 1M tokens, while Qwen3.5-397B-A17B supports 262K 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 Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B is cheaper on tracked token pricing. Gemini 2.5 Pro costs $1.25/1M input and $10/1M output tokens. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Qwen3.5-397B-A17B open source?
Gemini 2.5 Pro is listed under Proprietary. Qwen3.5-397B-A17B is listed under Apache 2.0. 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 Qwen3.5-397B-A17B?
Gemini 2.5 Pro has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Gemini 2.5 Pro or Qwen3.5-397B-A17B?
Both Gemini 2.5 Pro and Qwen3.5-397B-A17B 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 Qwen3.5-397B-A17B?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Qwen3.5-397B-A17B is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.