SGLang
product on 6 shows · 10 statements across 5 episodes · said 77 times in 17 episodes since 2024
Latent Space 67 
the MAD Podcast 4 
the a16z Podcast 2 
20VC 2 
the Y Combinator Startup Podcast 1 
No Priors 1
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Latent Space 67the MAD Podcast 4the a16z Podcast 220VC 2No Priors 1the Y Combinator Startup Podcast 1
2026 20 mentions in 7 episodes 3 per episode
- Next 100x in AI: Inference, Networking, & Self-Optimizing Models — Philip Kiely & Ali Taha, Baseten
- Dylan Patel: NVIDIA's New Moat & Why China is "Semiconductor Pilled”
- Agent Inference at the "Speed of Light" — How NVIDIA moves like a $4.3 Trillion Startup
- The Future of AI Infra: from Kubernetes to Agent Sandboxes — Akshat Bubna, Modal CTO
- Nebius Co-Founder on AI Infrastructure Bubbles | How Price Elastic is Demand for Compute · 20VC with Harry Stebbings
- Goodfire AI’s Bet: Interpretability as the Next Frontier of Model Design — Myra Deng & Mark Bissell
- Multi-GPU Kernels, Intelligence per Watt, Heterogeneous Inference, and More | YC Paper Club · Y Combinator
- every mention in 2026, scene by scene →
2025 55 mentions in 8 episodes 7 per episode
- DeepSeek V3, SGLang, and the state of Open Model Inference in 2025 (Quantization, MoEs, Pricing)
- The Shape of Compute (Chris Lattner of Modular)
- [State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute
- Dylan Patel on GPT-5’s Router Moment, GPUs vs TPUs, Monetization
- No Priors Ep. 127 | With SemiAnalysis Founder and CEO Dylan Patel
- ⚡️Mercury: Ultra-Fast Diffusion LLMs — Estefano Ermon, CEO Inception Labs
- Information Theory for Language Models: Jack Morris
- Beyond Leaderboards: LMArena’s Mission to Make AI Reliable
- every mention in 2025, scene by scene →
2024 2 mentions in 2 episodes 1 per episode
every mention on every show, scene by scene, with the transcript →
10 statements about SGLang, every show
Open-source inference engines often receive model weights before official launches
“Getting to the point of I can make a token out of this model is not that hard because generally the open source inference engines, your VLMs, SGLangs of the world oftentimes even receive weights ahead of time maintainers do, or the people making the model merg…”
Ermon: Inception Labs built proprietary engine for production inference traffic
“So just like you would normally serve an LLM using a VLLM or SGLang or a Tensor or TLLM, we have built our own inference engine. And so we are supporting production traffic already with our own inference engine. We support continuous batch and quantization.”
Morris: vLLM and SGLang are here to stay and will grow more complex
“I also think, ah, VLLM and SGLang seem, like, really good and important and here to stay. Like, they'll probably just get larger and more complex to accommodate future systems”
Zhang: SGLang outperforms vLLM and has better usability than TensorRT-LLM
“I think for the common use case, maybe not, not the DeepSeq VIII, for the common use case, I think SGLAN's performance is better than FLM, and its usability is better than TensorFlow TLM.”
Zhang: vLLM does not support DeepSeek MLA while SGLang does
“Something like DeepSeq V-II, they proposed attention parent named MLA, multi-latent attention, and I think SGLAN is the only framework to support that. Maybe LightLM and TRTM also support, but VLM doesn't support.”
Zhang: DeepSeek team officially recommends SGLang as its inference engine
“That's why SGLAN is the recommended LLM engine by the DeepSeq team.”
Zhang: SGLang achieves higher cache hit rates using block size of one
“Redix cache, I think it's the technology of the prefix caching, and it is a special case for something like block size is one, you know, for VLM or for other frameworks, they use something block size, 32, and SGLAN use the block size one. I think if you use th…”
Zhang: SGLang creators Lianmin Zheng and Ying Sheng work at xAI
“Lian Ming and Yin are the XAI's member of the technical staff.”
Zhang: Cursor Team Contacted SGLang Over DeepSeek-V3 Support
“And when we released the DeepSeq feed story support some employee from the Cursor team Also very interested in our implementation and ask, reach out and ask some questions from us.”
Angelopoulos: Chatbot Arena is decoupling from LMSYS as co-creators shift focus
“Sort of Chatbot Arena has, of course, like, kind of become its own thing, and Lianmin and Ying, who are, you know, created LMSYS, have kind of, like, moved on to working on SGLang, and now They're doing other projects that are sort of originating from LMSS. An…”