5 Comments
User's avatar
Yu Sakamoto's avatar

Your RTK/Headroom/Caveman comparison is exactly the right benchmark target. DeepSWE found Tura reduced coding-agent rounds by 89% and total token cost by 80%, while I/O-only compression barely changed end-to-end cost. Would you review the method? https://turaai.net/docs#benchmark-current-test-set-record

Christopher Moyé, Atty @ Law's avatar

I was just looking for a tutorial and found this explanation. Great post and thank you for taking the time to share this.

Perfect timing.

DK Labs's avatar

Thanks for the benchmark. Replaying your own sessions is the only honest way to judge these tools.

One question it raised for us: a lot of the waste is in what Claude Code carries, not in what tools return. We built Flightpath (free, open source, local) to show that per step, live: in one seven-minute session on a small sample project, the prompts came to about 41 tokens while Claude Code was carrying 59,375, and one file read later added 20,573 in a single step. If it's useful for a follow-up, it might help explain where the savings land: https://github.com/dk-labs-dev/flightpath

Ben Collins's avatar

most in-depth analysis I have found comparing these tools. Have you evaluated non opensource tools such as wozcode?

Yongkyun's avatar

Thanks! I haven’t tried non opensource tools, but I’ll check wozcode out.