I thought the benchmark was supposed to be about terminal use and specifically chaining together lots of bash tool calls. Which test cases does this matter for?
A few examples from memory:
1. This task [1] asks the agent to train a CNN under 1 CPU, 2GB RAM, 10GB storage. If you allow high resources, weaker models often succeed (the most clock time actually goes in waiting for the network to train).
2. This task [2] asks agents to implement a complete MIPS interpreter in JavaScript in 1 cpu and 2GB RAM. A common failure mode is OOM, at least in the earlier buggy versions that models run to get feedback. When OOM hits, the task is killed, no do-overs.
3. A lot of tasks involve building projects with a single core supplied. If you use -j12 type options, it will actually be _slower_ to build and the task will more likely miss the timeout. Having more threads squeezes the end to end time. This is a big one actually since the most common failure mode (from what I have seen) is the task timeout hitting before the agent finishes
[1] https://github.com/harbor-framework/terminal-bench-2-1/blob/...
[2] https://github.com/harbor-framework/terminal-bench-2-1/tree/...
https://www.anthropic.com/engineering/infrastructure-noise
Is anthropic benchmark maxxing and cheating on terminal bench too? They don't follow the strict resource "limits" either
Sure for old tasks you could argue that now its not required to boost because infra errors are alleviated with better default limits. My point more so is that its a strange thing to index on because if you wanted to cheat on the benchmark, it does not particularly seem like something that shifts results? Once the API is out maybe I'll eat my words, but I don't really believe that if you manually tried to reproduce the results with lower limits you'd see significantly different results