DeepSeek-V3 vs DeepSeek V4.1 Flash
A direct, empirical evaluation of DeepSeek-V3 (DeepSeek-AI) against DeepSeek V4.1 Flash (DeepSeek-AI).
DeepSeek-V3
Developed by DeepSeek-AI · 671B parameters
Cost-effective high-throughput general reasoning and bilingual generation.
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.
| Metric | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| SWE-bench Verified | 49.2% | 67.2% |
| MMLU-Pro | 75.9% | 78.4% |
| MATH-500 | 90.2% | 92.6% |
| Context Window | 128,000 tokens | 1,000,000 tokens |
| Input Pricing (per 1M) | $0.14 | $0.06 |
| Output Pricing (per 1M) | $0.28 | $0.22 |
Architectural & Practical Deployment Analysis
Evaluating DeepSeek-V3 (DeepSeek-AI) alongside DeepSeek V4.1 Flash (DeepSeek-AI) highlights key technical trade-offs across neural parameter scale and compute efficiency. DeepSeek-V3 executes across 671B total parameters with 37B active per token, whereas DeepSeek V4.1 Flash operates on 552B parameters with 8B input / 16B output active per token.
On SWE-bench Verified software engineering tasks, DeepSeek-V3 achieves 49.2% autonomous resolution rate, compared to 67.2% for DeepSeek V4.1 Flash. On complex reasoning benchmarks, DeepSeek-V3 posts 75.9% on MMLU-Pro and 90.2% on MATH-500, against 78.4% and 92.6% respectively for DeepSeek V4.1 Flash.
From an operational economics perspective, processing 10,000,000 mixed tokens (7M input / 3M output) costs approximately $1.82 on DeepSeek-V3 versus $1.04 on DeepSeek V4.1 Flash.
Recommendation: Deploy DeepSeek-V3 when your infrastructure prioritizes cost-effective high-throughput general reasoning and bilingual generation.. Deploy DeepSeek V4.1 Flash when workload requirements favor high-throughput software engineering, autonomous coding loops, terminal agents, 1m long-context retrieval, and low-cost production inference..