Same model. Same tasks. Same temp=0.
I ran my LLM eval rig twice, a week apart.
qwen3.5-9b on research/finance_hard_01:
Apr 18: 0.90
Apr 24: 0.60
Thirty percentile points of pure judge variance. No model change. No prompt change.
The takeaways ↓
WCK founder Chef José Andrés has arrived in Venezuela to join our teams on the ground. We're serving thousands of meals every day alongside impacted communities and scaling up to reach as many people as possible. ❤️ #ChefsForVenezuela
Today on Anthony Bourdain’s birthday, let’s honor Tony by sharing a meal…with a friend or with a stranger…and making sure they’re okay. @wckitchen we are honoring him in a way by being next to the people of Venezuela after the earthquakes. Sharing food and hope. #BourdainDay
Full writeup — GGUF metadata diff, chat-template diff, both run reports — in the article:
https://t.co/sZQUzSMCQp
Next post: running this as a Kubernetes CronJob. From "eval rig on bare metal" to "platform that runs itself at n=40+ without babysitting."
Same model. Same tasks. Same temp=0.
I ran my LLM eval rig twice, a week apart.
qwen3.5-9b on research/finance_hard_01:
Apr 18: 0.90
Apr 24: 0.60
Thirty percentile points of pure judge variance. No model change. No prompt change.
The takeaways ↓
Two more findings two runs unlocked:
→ qwen3.5-27b: 0.62 composite both runs. qwen3.5-9b: 0.62 both runs. But 27b takes 3× the wall-clock time. Not earning its size.
→ coding_artemis_medium_01: 0.42 every model, both runs. coding_mcp_hard_01: 0.25 every model, both runs.
When every model on a task scores the same across runs, the task is broken — not the models.