 | Hi! I wanted to share my new blog on the costs of running AI Evals. We dig into how benchmarking frontier systems now routinely costs tens of thousands of dollars per run, why agent evals are especially unpredictable, and what that concentration of validation authority means for the broader research community. [link] [comments] |
Blog: AI evals are becoming the new compute bottleneck
Reddit r/LocalLLaMA / 5/1/2026
💬 OpinionDeveloper Stack & InfrastructureIdeas & Deep AnalysisModels & Research
Key Points
- Running AI evaluations (“evals”) is increasingly becoming a major cost and bottleneck, with frontier benchmarking often costing tens of thousands of dollars per run.
- Evaluating agent-based systems is especially unpredictable, making it harder to estimate compute and total cost before running tests.
- The concentration of validation/benchmarking authority influences the research community by shaping what gets measured, prioritized, and funded.
- The blog discusses the broader implications of these rising eval costs for how researchers plan experiments and allocate resources.
Related Articles
Can AI Predict Pollution Before It Happens? The Smart Solution to an Old Problem
Dev.to
THE FIFTH TRANSMISSION: THE GRADIENT IS THE GOVERNMENT
Reddit r/artificial
Looking for feedback on OpenVidya: an open-source AI classroom layer for NCERT/CBSE [R]
Reddit r/MachineLearning
RAG Series (1): Why LLMs Need External Memory
Dev.to
One Open Source Project a Day (No. 54): Warp - The AI-Native Rust Terminal
Dev.to
