DeepSeek V4.1 Flash vs Qwen 2.5 Max
A direct, empirical evaluation of DeepSeek V4.1 Flash (DeepSeek-AI) against Qwen 2.5 Max (Alibaba Cloud).
DeepSeek V4.1 Flash
Developed by DeepSeek-AI · 552B parameters
High-throughput software engineering, autonomous coding loops, terminal agents, 1M long-context retrieval, and low-cost production inference.
Qwen 2.5 Max
Developed by Alibaba Cloud · Proprietary (~700B) parameters
Cross-lingual document extraction and structured structured output generation.
| Metric | DeepSeek V4.1 Flash | Qwen 2.5 Max |
|---|---|---|
| SWE-bench Verified | 67.2% | 51.4% |
| MMLU-Pro | 78.4% | 77.2% |
| MATH-500 | 92.6% | 89.4% |
| Context Window | 1,000,000 tokens | 128,000 tokens |
| Input Pricing (per 1M) | $0.06 | $1.60 |
| Output Pricing (per 1M) | $0.22 | $6.40 |
Architectural & Practical Deployment Analysis
Evaluating DeepSeek V4.1 Flash (DeepSeek-AI) alongside Qwen 2.5 Max (Alibaba Cloud) highlights key technical trade-offs across neural parameter scale and compute efficiency. DeepSeek V4.1 Flash executes across 552B total parameters with 8B input / 16B output active per token, whereas Qwen 2.5 Max operates on Proprietary (~700B) parameters with Dense/MoE Hybrid active per token.
On SWE-bench Verified software engineering tasks, DeepSeek V4.1 Flash achieves 67.2% autonomous resolution rate, compared to 51.4% for Qwen 2.5 Max. On complex reasoning benchmarks, DeepSeek V4.1 Flash posts 78.4% on MMLU-Pro and 92.6% on MATH-500, against 77.2% and 89.4% respectively for Qwen 2.5 Max.
From an operational economics perspective, processing 10,000,000 mixed tokens (7M input / 3M output) costs approximately $1.04 on DeepSeek V4.1 Flash versus $30.40 on Qwen 2.5 Max.
Recommendation: Deploy DeepSeek V4.1 Flash when your infrastructure prioritizes high-throughput software engineering, autonomous coding loops, terminal agents, 1m long-context retrieval, and low-cost production inference.. Deploy Qwen 2.5 Max when workload requirements favor cross-lingual document extraction and structured structured output generation..