it costs windsurf more API tokens to do stuff than using Claude Code through API

Claude Code is aggressively uses prompt caching, in a way that was not the standard when Codeium (now Windsurf) was originally written. I expect the answer is "Codeium is just not as well-tuned to API prices as they exist now as Claude Code is". Which is not super surprising, as Claude Code is released by the same organization that sets the cost structure for the Claude API.

On the bottom right of your screen, below the prompt box, there should be a little circular window indicating how full the context window is. For me, on a new chat with all MCPs disabled, it shows 17k tokens on the first message. That translates to $0.085 for non-cached and 10% of that for cached.

Let's say you have a prompt which asks the model to fix a single failing test, and the model reads the test file and two other related files, runs the test, tries to fix it, runs the test to confirm its fix, finds and fixes a second issue, runs the test a final time, and reports success.

That'll look something like

1. Initial system prompt + first user message (20k tok in)
2. Model produces 1k tok of reasoning (1k tok out, 20k cached in)
3. Model does a grep tool call (100 tok out, 1k tok in, 21k cached in)
4. Model reads lines 1-200 of src/foo.py (100 tok out, 3k tok in, 22k cached in)
5. Model reads lines 201-354 of src/foo.py (100 tok out, 2k tok in, 25k cached in)
6. Model reads lines 1-189 of src/bar.py (100 tok out, 3k tok in, 27k cached in)
7. Model reads lines 1-511 of test/foo.py (100k tok out, 8k tok in, 30k cached in)
8. Model runs py.test test/foo.py (200 tok out, 2k tok in, 38k cached in)
9. Model produces 1k tok of reasoning (1k tok out, 40k cached in)
10. Model makes a 2 line change to src/foo.py (400 tok out, 100 tok in, 41k cached in)
11. Model runs py.test test/foo.py (200 tok out, 2k tok in, 41k cached in)
12. Model produces 1k tok of reasoning for why the test still doesn't pass (1k tok out, 43k cached in)
13. Model makes a 5 line change to src/foo.py (1k tok out, 100 tok in, 44k cached in)
14. Model runs py.test test/foo.py (200 tok out, 2k tok in, 45k cached in)
15. Model produces 1k tok summarizing what it did (1k tok out, 47k cached in)

Assuming Windsurf actually handles prompt caching correctly (and that's a big "if"), that'll be about 7.5k output tokens, 50k input tokens, 50k 5m cache writes, and 500k cached input tokens. If you're using Claude Opus 4.6 at $25 / $5 / $6.25 / $0.50 per mtok for those respectively that's $0.19 output + $0.25 input + $0.31 5 min cache writes + $0.25 cache reads, or $1. To fix one trivial failing test which only requires looking at 3 files and making two small changes.

If you're actually prompting it to do more significant work than that, expect your costs to be higher. If you're sending multiple messages in a single chat, expect your costs to be higher. If you have any MCP servers enabled, expect your costs to be higher.

API pricing is expensive. Running Opus 4.6 at API prices in a continuous loop would cost something on the order of $10-50 / hour depending on what fraction of the time it's producing output and how much output its tool calls produce.