Baseten Blog

Engineering meets ML infrastructure. Dive into curated insights, expert tutorials, and innovative techniques that make deploying ML models less daunting and more accessible. Explore the topics that resonate with today's tech landscape, and empower your developer journey with expert knowledge.

33% faster LLM inference with FP8 quantization

Quantizing Mistral 7B to FP8 resulted in near-zero perplexity gains and yielded material performance improvements across latency, throughput, and cost.

High performance ML inference with NVIDIA TensorRT

Use TensorRT to achieve 40% lower latency for SDXL and sub-200ms time to first token for Mixtral 8x7B on A100 and H100 GPUs.

40% faster Stable Diffusion XL inference with NVIDIA TensorRT

Using NVIDIA TensorRT to optimize each component of the SDXL pipeline, we improved SDXL inference latency by 40% and throughput by 70% on NVIDIA H100 GPUs.

Streaming real-time text to speech with XTTS V2

In this tutorial, we'll build a streaming endpoint for the XTTS V2 text to speech model with real-time narration and 200 ms time to first chunk.

How to serve your ComfyUI model behind an API endpoint

This guide details deploying ComfyUI image generation pipelines via API for app integration, using Truss for packaging & production deployment.

GPT vs Mistral: Migrate to open source LLMs seamlessly

Use ChatCompletions API to test open-source LLMs like Mistral 7B in your AI app with just three minor code modifications.

NVIDIA A10 vs A10G for ML model inference

The A10, an Ampere-series GPU, excels in tasks like running 7B parameter LLMs. AWS's A10G variant, similar in GPU memory & bandwidth, is mostly interchangeable.

NVIDIA A10 vs A100 GPUs for LLM and Stable Diffusion inference

This article compares two popular GPUs—the NVIDIA A10 and A100—for model inference and discusses the option of using multi-GPU instances for larger models.

Understanding NVIDIA’s Datacenter GPU line

This guide helps you navigate NVIDIA’s datacenter GPU lineup and map it to your model serving needs.

Playground v2 vs Stable Diffusion XL 1.0 for text-to-image generation

Playground v2, a new text-to-image model, matches SDXL's speed & quality with a unique AAA game-style aesthetic. Ideal choice varies by use case & art taste.

Stable Video Diffusion now available

Stability AI announced the release of Stable Video Diffusion, marking a huge leap forward for open source novel video synthesis

Open source alternatives for machine learning models

Building on top of open source models gives you access to a wide range of capabilities that you would otherwise lack from a black box endpoint provider.

How latent consistency models work

Latent Consistency Models (LCMs) improve on generative AI methods to produce high-quality images in just 2-4 steps, taking less than a second for inference.

Control plane vs workload plane in model serving infrastructure

A separation of concerns between a control plane and workload planes enables multi-cloud, multi-region model serving and self-hosted inference.

Comparing tokens per second across LLMs

To accurately compare tokens per second between different large language models, we need to adjust for tokenizer efficiency.

What I learned from my AI startup’s internal hackathon

See hackathon projects from Baseten for ML infrastructure, inference, user experience, and streaming

If You Build It, Devs will Come: How to Host an AI Meetup

Want to host an AI community meetup, but aren’t sure where to start? Julien shares his top 10 tips for successfully hosting an AI meetup.

StartupML AMA: Daniel Whitenack

Meet Daniel, Data Scientist and founding data science team member at SIL

Baseten Chains Explained: Building Multi-Component AI Workflows at Scale

A Delightful Developer Experience for Building and Deploying Compound ML Inference Workflows

New in May 2024

AI events, multicluster model serving architecture, tokenizer efficiency, and forward-deployed engineering

New in April 2024

Use four new best in class LLMs, stream synthesized speech with XTTS, and deploy models with CI/CD

Baseten announces HIPAA compliance

Baseten is a HIPAA-compliant MLOps platform for fine-tuning, deploying, and monitoring ML models on secure model infrastructure.

How we achieved SOC 2 and HIPAA compliance as an early-stage company

Baseten is a SOC 2 Type II certified and HIPAA compliant platform for fine-tuning, deploying, and serving ML models, LLMs, and AI models.

Baseten achieves SOC 2 Type II certification

Baseten, an MLOps platform for model deployment & fine-tuning, now boasts SOC 2 type 2 certification, ensuring data security, privacy, and confidentiality.