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Gemini 2.5 Pro vs Qwen3.5-235B-A22B

Gemini 2.5 Pro (2025) and Qwen3.5-235B-A22B (2026) are general-purpose language models from Google DeepMind and Alibaba. Gemini 2.5 Pro ships a 1M-token context window, while Qwen3.5-235B-A22B ships a 512k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Qwen3.5-235B-A22B is safer overall; choose Gemini 2.5 Pro when coding workflow support matters.

Specs

Released2025-06-172026-02-24
Context window1M512k
Parameters235B
Architecturedecoder onlyMoE
LicenseProprietaryApache 2.0
Knowledge cutoff2025-01-

Pricing and availability

Gemini 2.5 ProQwen3.5-235B-A22B
Input price$1.25/1M tokens-
Output price$10/1M tokens-
Providers-

Capabilities

Gemini 2.5 ProQwen3.5-235B-A22B
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Gemini 2.5 Pro, multimodal input: Gemini 2.5 Pro, function calling: Gemini 2.5 Pro, tool use: Gemini 2.5 Pro, structured outputs: Gemini 2.5 Pro, and code execution: Gemini 2.5 Pro. Both models share the core language-model surface, 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.

Pricing coverage is uneven: Gemini 2.5 Pro has $1.25/1M input tokens and Qwen3.5-235B-A22B has no token price sourced yet. Provider availability is 3 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Gemini 2.5 Pro when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Qwen3.5-235B-A22B when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which has a larger context window, Gemini 2.5 Pro or Qwen3.5-235B-A22B?

Gemini 2.5 Pro supports 1M tokens, while Qwen3.5-235B-A22B supports 512k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Gemini 2.5 Pro or Qwen3.5-235B-A22B open source?

Gemini 2.5 Pro is listed under Proprietary. Qwen3.5-235B-A22B 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 Qwen3.5-235B-A22B?

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 Qwen3.5-235B-A22B?

Gemini 2.5 Pro has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, Gemini 2.5 Pro or Qwen3.5-235B-A22B?

Gemini 2.5 Pro has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Gemini 2.5 Pro and Qwen3.5-235B-A22B?

Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Qwen3.5-235B-A22B is available on the tracked providers still being sourced. 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.