Question the measurement
My LLM judge was flipping a coin a third of the time
What happened when I tested the judge I had trusted for months.
The notebook
Writing
Small thoughts, things I learned the hard way, and ideas that needed more room.
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Follow a fix
Every FP8 GEMM traps on DGX Spark (SM121)
An exact failure, the hardware behind it, and the two-line fix.
Look at the craft
A page transition that breathes
The engineering behind a quieter page transition on this site.
Browse the notebook
5 pieces about Evaluation & measurement
Essay
The kernel kills your inference server first, and by default
An 87 GiB model got OOM-killed with nothing in its own log. The process that triggered it was a 27 MB dashboard service. The reason my inference server was the kernel first choice was not its size — it was a systemd user-manager default that scores every terminal-launched process to die before any system service. Then restarting it killed my editor.
Essay
Tokens per second told me the wrong model was faster
A 125B model decoding at 26.6 tok/s looks unremarkable beside a 31B at 29.3 — until you notice the 31B is running a drafter, so its number is a forward-pass rate multiplied by an acceptance length. Per forward pass the big model was 3x faster. Here is how to decompose the number, and what the bandwidth arithmetic says is still on the table.
Essay
My guardrail checked the config, not the corpus
I have swapped the local model under my newspaper 85 times in four months. That looked like a natural experiment, so I built an instrument to read it — including a gate that refuses comparisons contaminated by time. The gate passed. It was reading my switch log instead of my writing, and the two models it cleared had never once alternated.
Essay
My LLM judge was flipping a coin a third of the time
I used a language model to pick the better of two drafts, and trusted it for months. Then I gave it two drafts from an identical configuration and asked it to choose. Here is what measuring a judge’s noise floor costs, and why every A/B result before it was unreadable.
Essay
The model ran out of room to think, and every diagnostic guessed wrong
Three times this year a reasoning model spent its whole token budget thinking and handed back empty content under HTTP 200. Three times, the code reading the result invented a different explanation — a parser bug, then an unconstrained grammar. Neither was true, and one of them fired inside a safety check.