Live data from Hacker News

Show HN: Terminal-Bench-RL: Training long-horizon terminal agents with RL

github.com

11–14 of 14 posts

Re: Show HN: Terminal-Bench-RL: Training long-horizon terminal agents with RL

#11

Some of the comments so far seem to be misunderstanding this submission. As I understand it: 1. Custom scaffolding (system prompt and tools) using Qwen3-32B achieved 13.75% on Terminal-Bench. No training was involved. 2. The author has built an RL system, but it has not been used for anything due to cost limitations. So there's actually no result related to training here. It well known that the scaffolding used can h…

It looks like the submission has two aspects that are being conflated.

1. Tooling for training a terminal agent.

2. An agent that was _not_ trained with this tooling but prompt engineered. I could not find the author's discussion on this point.

Re: Show HN: Terminal-Bench-RL: Training long-horizon terminal agents with RL

#14
post #13

Why do you need 50k? Can't you tune using LoRA?

Exactly my first thought when I realised the cost! Currently LoRA is not supported by rLLM (The team told me they aim to support in next release), but it is certainly possible to port to verl directly or another RL framework for sure. I just did not have the time to port again (already done 2x as other RL frameworks had issues)
Post reply on HN