Side-by-side technical and economic comparison between Google's Gemini 2.5 Flash and Alibaba / Qwen's Qwen3 235B-A22B.
| Metric | Gemini 2.5 Flash | Qwen3 235B-A22B | Advantage |
|---|---|---|---|
| Provider Organization | Alibaba / Qwen | — | |
| Standard Input / 1M | $0.30 | $0.90 | Gemini 2.5 Flash (67% lower) |
| Cached Input / 1M | $0.03 | $0.18 | Gemini 2.5 Flash lower |
| Output / 1M | $2.50 | $1.60 | Qwen3 235B-A22B lower |
| Context Window | 1.05M | 128k | Gemini 2.5 Flash (1.05M) |
| Max Generation Tokens | 8.2k | 32k | Qwen3 235B-A22B |
| Tokenizer Family | Google Gemma SentencePiece (~256k vocabulary) | Qwen SentencePiece BPE (152k vocabulary) | — |
Opt for Gemini 2.5 Flash when your engineering requirements prioritize Google's ecosystem, specific tokenizer efficiencies (Calibrated Gemma Tokenizer (±3%)), or when your expected prompt-to-completion ratios favor its $0.3/M input rate.
Opt for Qwen3 235B-A22B when looking for Alibaba / Qwen's tooling integration, specific context window depth (128k tokens), or when output generation volume favors its $1.6/M rate.