Lesson 07 · DeepSeek Mastery
Pro+
~10 min read
Updated June 2026
Migrating to V4: the painless path off the legacy models.
If you built on an older DeepSeek model alias, the legacy names are being retired. The migration is small but has a couple of traps. Here is the checklist.
01What actually changes
Mostly just the model name in your request. Swap the retired alias for a current V4 identifier (Flash or Pro). The endpoint shape, message format, and your SDK stay the same — that is the benefit of the compatible API.
02The traps to check
Hard-coded model strings scattered across your code — search and replace them all. Behavior drift: V4 may format or reason slightly differently, so re-run your evals or spot-checks. Reasoning vs non-reasoning: make sure you are calling the variant you intend.
Legacy aliases are being retired on a deadline — calls to them will start failing after the cutoff. Migrate before then, and pin to explicit V4 names rather than floating aliases so you control when behavior changes.
Migration checklistFind every model string → swap to a current V4 name → re-run your tests/spot-checks → confirm reasoning vs non-reasoning → set a spend limit → ship. Ten minutes for most projects.
Frequently asked
DeepSeek — your questions, answered
How do I migrate to DeepSeek V4?
Replace retired legacy model aliases with current V4 names (Flash or Pro) everywhere in your code, then re-run your tests. The endpoint and message format stay the same.
Will my old DeepSeek model name keep working?
Legacy aliases are being retired on a deadline and will stop working after the cutoff. Move to explicit V4 names before then.
Does V4 behave differently from older models?
It can format and reason slightly differently, so re-run your evaluations or spot-checks after switching rather than assuming identical output.
Do I need to change my code beyond the model name?
Usually not — the compatible API keeps the same shape. Just update model strings and verify reasoning vs non-reasoning variants.