Gemini 3.5 Flash 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 Gemini 3.5 Flash and Qwen 2.5 72B.
Gemini 3.5 Flash
Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...
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 | Gemini 3.5 Flash | Qwen 2.5 72B |
|---|---|---|
| Provider | Alibaba | |
| Context Window | 1,048,576 tokens | 131,072 tokens |
| Agent Suitability | 88/100 | 88/100 |
| Time to First Token (TTFT) | 200 ms | 280 ms |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-05-19 | 2025-09-19 |
API Pricing Comparison
Input Price per Million Tokens
Gemini 3.5 Flash
$1.50
Qwen 2.5 72B
$0.40
Output Price per Million Tokens
Gemini 3.5 Flash
$9.00
Qwen 2.5 72B
$0.80
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Gemini 3.5 Flash Quirks & Gotchas
- ▸Excellent multimodal performance — native video understanding
- ▸Tool calling via Google's native function_declarations in Vertex AI
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