FrontierHarness Eval
FrontierHarness Eval enables developers to benchmark different AI harness configurations on identical software engineering tasks using the same model and runtime. It measures quality, cost, latency, and cache metrics to optimize harness design for software agent runtimes like Runta.
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Around the Web
It's nice to see time reflected here. Deepseek is fuckin fast! Seems like the bigger the task, the faster it gets, which is kind of unfortunate because nobody is going to be doing 17 benchmark passes on a $50-100 task. I'm assuming the brief pause before it avalanches out 16kb of text at upwards of 250tk/s (multiples beyond anything resembling a comfortable reading speed) is some sort of workload evaluator directing sessions to individual/multiple cards, occasionally waiting for what it thinks is best to become available. I couldn't believe it at first, it shit out a damn fine multithreaded physics simulation fabric (integrated into a massive codebase, tests passing) in under an hour. Anything I could find online says they average like 80 but my logs average ~3x that.
monster_truck · Imported from Show HN
Do you have instructions on how to run a custom harness against this? There are none on the linked page. I want to run Dirac (https://github.com/dirac-run/dirac).
GodelNumbering · Imported from Show HN
Testing it against Kimi is potentially skewing the numbers massively. Kimi has a number of quirks that requires behaviours that e.g. Claude or GPT doesn't. Harnesses that are built around needing to work with "weird" models will need to deal with that, such as Kimi's tendency to get stuck in tool-call loops. Harnesses built to deal with e.g. Anthropic's models primarily, do not need to deal with that. Claiming on the blog that this gives Kimi Code no home field advantage seems like a dicey assumption. I haven't dug into the newest Kimi Code much, but the older Kimi CLI included several tools that were clearly specifically aimed at working around that behaviour - when I copied their checkpoints and "dmail" mechanism into my own harness, the performance with Kimi improved dramatically, but it made zero difference against Anthropic models. That doesn't make the data worthless - it's clear you shouldn't use Clade Code to work against Kimi. But it does significantly limit the utility of it.
vidarh · Imported from Show HN
The Exo harness is the most interesting one in the benchmark, as it has the potential to complete tasks with fewer turns and cost.
Edward40 · Imported from Show HN
I've been confused a lot why there isn't a benchmark to measure a harness's performance rather than the model's one. Now there it is.
EFLKumo · Imported from Show HN