Key takeaways
Pick DeepSeek-V4-Pro when the POC is hard reasoning or coding and call cost matters. Pick DeepSeek-V4-Flash when you need the same 1M-token window and 384K max output at higher request volume. Pick DeepSeek-R1 when you need a visible chain of thought for math and logic. DeepSeek-V3 remains the earlier high-value line; its parameter count and context length are not disclosed on this catalog.
Published specs you can quote
DeepSeek-V4-Pro: 1.6T total parameters, about 49B active per inference, 1M-token context, 384K maximum output. Page: /en/models/deepseek-v4-pro. DeepSeek-V4-Flash: 284B total, about 13B active, same 1M context and 384K max output. Page: /en/models/deepseek-v4-flash. Knowledge cutoff for both is not publicly disclosed. Do not fill that blank from memory.
DeepSeek-R1 is the reasoning model with a visible thinking trace for math, code, and complex logic. Its parameter count and context window are not on this page: /en/models/deepseek-r1. A longer note is /en/articles/deepseek-r1-reasoning-guide-2026.
A one-hour bake-off
Run the same 10 coding prompts on V4-Pro and V4-Flash. Score answer quality, tool success if you use tools, P95 latency, and output tokens. Add R1 only if you need the trace. Then compare the winner with one non-DeepSeek model using /en/articles/best-chinese-llm-2026. Overseas API steps: /en/articles/deepseek-api-overseas-quickstart-2026.
FAQ
What is DeepSeek-V4-Pro?
The V4 high-performance edition on this index: 1.6T total / about 49B active, 1M context, 384K max output, aimed at complex reasoning at very low call cost.
How is V4-Flash different?
It is the speed and cost tier: 284B total / about 13B active, with the same 1M context and 384K max output.
Should I still use DeepSeek-R1?
Use R1 when the product must show a chain of thought. Use V4-Pro when you want flagship reasoning without that requirement.
Are these official DeepSeek specs?
They are the public figures stored on Swift Horse. Re-check the DeepSeek console before a contract.