KV Cache on 16 GB GPUs: Making Long Context Actually Fit
A model can advertise a 128K context window and still fail at 40K tokens on a 16 GB GPU. The architecture ceiling never promised that weights, KV ca…
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From adapter to deployment: merging LoRA weights and serving with vLLM or a Space
A fine-tuned adapter sitting in a folder is not a product. FineTune Studio offers three inference paths — local, a vLLM server, or a Hugging Face Sp…
Self-hosting a lite agent backend on one TPU: Gemma 4 E2B + vLLM on a v5e-1
Self-hosting a lite agent backend on one TPU chip A single Google Cloud TPU v5e chip — 16 GB of HBM, about $0.58/hour on spot — will serve google/ge…
[Перевод] Как оптимизировать LLM-инференс в 2026 году
Если вы в 2026 году запускаете LLM в продакшене, то почти наверняка больше всего денег тратите на инференс. Одна неоптимизированная модель размером…