Nano Banana (Gemini 2.5 Flash Image) vs Qwen 2.5 72B
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Nano Banana (Gemini 2.5 Flash Image) and Qwen 2.5 72B.
Nano Banana (Gemini 2.5 Flash Image)
Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation,...
Qwen 2.5 72B
Qwen 2.5 72B is Alibaba Cloud's flagship open-weight large language model from the Qwen 2.5 generation, delivering GPT-4-class performance across general reasoning, coding, mathematics, and multilingual tasks with strong Chinese-language superiority. It supports a 131,072-token context window and is available under a permissive Apache 2.0 license for both research and commercial use, making it one of the most popular open-weight alternatives to Llama for bilingual applications.
Technical Specifications
| Specification | Nano Banana (Gemini 2.5 Flash Image) | Qwen 2.5 72B |
|---|---|---|
| Provider | Alibaba | |
| Context Window | 32,768 tokens | 131,072 tokens |
| Agent Suitability | N/A | 88/100 |
| Time to First Token (TTFT) | N/A | 280 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-10-07 | 2025-09-19 |
API Pricing Comparison
Input Price per Million Tokens
Nano Banana (Gemini 2.5 Flash Image)
$0.30
Qwen 2.5 72B
$0.40
Output Price per Million Tokens
Nano Banana (Gemini 2.5 Flash Image)
$2.50
Qwen 2.5 72B
$0.80
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Nano Banana (Gemini 2.5 Flash Image) Quirks & Gotchas
No developer gotchas reported.
Qwen 2.5 72B Quirks & Gotchas
- ▸Strong bilingual (ZH/EN) performance — best open model for Chinese-language tasks
- ▸Self-hostable via vLLM or Ollama with 4-bit quantization