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SGLang v0.5.22 reports 2.3x DeepSeek-V4.1 throughput per H200 GPU

SGLang v0.5.22 reports 2.3x the DeepSeek-V4.1 throughput per H200 GPU, letting the same DeepSeek-V4.1 load fit on fewer than half the H200s it previously required, cutting GPU spend for self-hosters. The release also adds support for running DeepSeek-V4.1 on AMD MI350X and MI355X GPUs, giving teams a second vendor to serve the model on.

read1 min views1 publishedOct 19, 2026

At the reported peak, the same DeepSeek-V4.1 load fits on fewer than half the H200s it needed before, a direct cut in GPU spend for self-hosters. The model now also runs on AMD MI350X and MI355X, giving teams a second vendor to serve it on. Try: At the reported peak, the same DeepSeek-V4.1 load fits on fewer than half the H200s it needed before, a direct cut in GPU spend for self-hosters. The model now also runs on AMD MI350X and MI355X, giving teams a second vendor to serve it on. Read: Agents built on DeepSeek models can now search the live web and read pages as Markdown with the same API key, dropping a separate search vendor account and bill. Billing counts successful requests only, so failed lookups cost nothing. Read: The authors report 2.7-3.7x lower cost while tool calls stay in plain text, so existing tool interfaces keep working. Latent thoughts can be rendered for inspection, and code and checkpoints are public, so the self-reported numbers can be checked. Read: It beats Fish Audio's own S2.1 Pro by five points on hard words, numbers and codes, so voice products misread fewer names and IDs. Weights are free for commercial use below US$500,000 in annual revenue; reselling it as a service needs a separate license. Watch: A Keycard panel with JPMorgan Chase's security architect and OAuth co-creator Dick Hardt used the case to argue that OAuth scopes are too coarse for agents. They proposed giving each agent a mission and a budget instead of a rate limit. Listen: If models plan ahead without stating it, the next-token predictor picture engineers use to write prompts and read agent output is incomplete. Ameisen pairs this with findings that models form general concept representations.

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