There are many other advantages of SGLang, and the team is constantly pushing the boundaries of inference performance - making it an excellent choice for production workloads. Happy building and tag us in applications you build!

In our example, of an Advertisement Analyzer we use SGLang to runs multiple prompts in parallel, like: “Does this ad align with the company’s description?” “Is the message clear and consistent?” “Does it target the right audience?” All prompts run concurrently, then join at the

What makes SGLang different from vLLM and TensorRT-LLM? - You can define model logic using gen(), fork(), join(), select() - no more prompt chaining - RadixAttention = smarter KV cache reuse (up to 6× faster) - No more messy JSON — FSMs guarantee clean structured output -

We just dropped a new tutorial on deploying a Vision-Language model using #SGLang - an inference framework thats used by xAI and Deepseek. We created an Advertisement analyzer taking advantage of parallel inference requests - functionality that is unique to SGLang. Checkout the

To get started: 1️⃣ Open your project’s Integrations tab 2️⃣ Click Connect GitHub and authorize 3️⃣ Select repos + deployment branch 4️⃣ (Optional) Enable auto-deploy This feature is in beta — we’d love your feedback 🫶

What it unlocks: • Continuous deployment — auto-deploy on every push • Full version control for apps/models • Branch-based deployments • Monorepo support for subdirectories

🚀 New Feature: GitHub Integration Your workflow just got simpler! Cerebrium now supports GitHub Integration — connect your repo and deploy straight from source. No YAMLs. No secrets juggling. Just push your code, and it ships ⚡️ 🎥 Demo ↓

AI teams don’t just need GPUs — they need infrastructure that moves as fast as they do. Cerebrium is redefining what serverless GPU compute means for real-time AI. ⚡️

auto-scales to 1000s of calls, pay-per-second billing, global regions real-time voice AI, finally feels real-time 🎙️

ran STT → LLM → TTS all in one Cerebrium cluster <10 ms inter-container latency, zero network hops, sub-500 ms round-trip

every team at #VapiCon hit the same wall — latency + scale. here’s how we showed real-time voice agents can actually be real-time ⚡️

and that's a wrap! #vapicon ✅ turns out everyone faces similar challenges when building voice agents - scalability & low latency - both of which Cerebrium can solve! reach out to us for up to $60 free credits before October 16th 👀 thank you san francisco and @Vapi_AI 🤍

tomorrow at #VapiCon - our founder @MichaelLouis_za will discuss how to build and scale fast, reliable agents! SF is so back! 🔥 @Vapi_AI

The release of gpt-oss is a powerful unlock for companies who want to run low-latency use cases, at global scale at a cost effective price. The first time OpenAI has released open weights in a long time! https://t.co/HJ0oz2vAyX #ai #inference #gpu #gpt

We’ve teamed up with the team at @VideoSDK to help developers build ultra-low latency AI voice agents — with real-time conversations under 300ms. From global routing and autoscaling to fast responses, this stack is perfect for any real-time voice experience at scale.

Our customers have constantly asked us for ways to run their applications at the lowest latency as well as have data residency/compliance in certain locations. Thats why we partnered with @rimelabs Run their TTS models next to your Cerebrium deployment!

Useful for teams building: • Voice agents for support • Internal tools with hands-free access • Real-time automation over audio • AI assistants that combine reasoning + action Plus its extendable to our MCP servers

The agent listens to user input → parses intent via LLM → uses MCP to do things like: • Create invoices • Manage subscriptions • Process refunds Then responds with natural-sounding speech — all in real time.

What you’ll learn: • How MCP gives LLMs structured access to PayPal tools • How to build a voice interface that can actually perform actions • Real-time audio streaming + LLM orchestration • End-to-end stack using @pipecat_ai , Cerebrium, and Daily

Ever wished your voice assistant could actually do something useful—like send invoices or manage subscriptions? We just published a tutorial on integrating @PayPal's Model Context Protocol (MCP) into a real-time voice agent. https://t.co/7ct3BYK9cF #mcp #voiceai #genai #llm