FP4 Reinforcement Learning and Inference with Zero Performance Loss
nrehiew_ · x · 2026-07-13
A tweet shares an interesting side effect of using FP4 precision for reinforcement learning (RL): it enables FP4 inference serving. The author notes that when using GLM5.1 as a judge model, the FP4 service appears to show absolutely no performance degradation.
More from Infra
- LLM Serving Metrics Thread: Why TPOT and Uptime Make or Break User Experience — abhijithneil · 2026-09-11
- PlanetScale launches sharded Postgres: 768 servers acting as one, 1PB scale — dhruv2038 · 2026-09-11
- Can a 7900 XTX 24GB run Qwen locally? Reddit seeks ROCm tok/s benchmarks — thenomadexplorerlife · 2026-09-11
- RTK Terminal Compression Cuts Tokens but Leaves Your AI Coding Bill Unchanged — Bartaseth · 2026-09-11
- SF Compute founder: buying compute is 'an absolutely awful experience' right now — IgorCarron · 2026-09-11
- SmolVM open-sources persistent computer infrastructure for agents that outlive chat sessions — aniketmaurya · 2026-09-11