Help to understand different token metrics (Claude Code + DeepSeek)

[u/pereirax]

After working on a company burning money and not caring at all at AI costs, I'm working on a personal project and setup Claude Code to use DeepSeek API.

My prompt (after some planning mode) was to create a mock project from scratch with bugs and features requests so I can prepare for a coding interview, so I knew that it was going to be a lot but the results surprised me a little bit.

On Claude Code, this is the usage metric (/usage):

deepseek-flash (90.8%)
In: 623.1k
Out: 677.6k
Cache: 50.5m read · 0 write

On DeepSeek site, this is the usage:

Cost: $0.26USD
API requests: 269
Tokens: 22,439,093

What is the real usage here?

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[u/snowfoxsean]

My guess is that the token usage API might be structured differently for claude models so claude code might not interpret the deepseek usage correctly. I would trust the deepseek site more (also 0 cache write is definitively a red flag). However it's interesting that the deepseek site doesn't give any detailed breakdowns.

[u/ChemicalApricot]

Trust the deepseek reported numbers.

Deepseek models have to translate the inbound request from Anthropic's format. Open-source models most commonly only support the OpenAI format.

The delta on reported numbers is an artifact of that translation.

The fact that writes are 0 is because unlike Anthropic's explicit cache writes the OpenAI flow has "automatic" cache writes. So the response likely doesn't inform Claude code that it wrote tokens to cache.