Baseten: Serverless AI Inference Infrastructure for Production
Baseten provides serverless infrastructure to deploy and serve open-source, custom, and fine‑tuned AI models and agents in production with low latency, high throughput, autoscaling, and 99.99% uptime. Its stack spans model packaging to deployment, observability, and scale, available in cloud, self‑hosted (VPC), and hybrid modes.
Website: [Baseten](https://www.baseten.co)Tagline: “Inference is everything”HQ: San Francisco, CALinkedIn: [Baseten on LinkedIn](https://www.linkedin.com/company/baseten)What Baseten Does
Build and operate serverless AI inference with the [Baseten Inference Stack](https://www.baseten.co/resources/guide/the-baseten-inference-stack) optimized for compound AI systems and agents.Package models using [Truss](https://docs.baseten.co/development/model/overview) and orchestrate multi‑step pipelines with the [Chains framework](https://www.baseten.co/blog/baseten-chains-for-production-compound-ai-systems).Deliver active‑active reliability and [multi‑cloud capacity management](https://www.baseten.co/products/multi-cloud-capacity-management) targeting 99.99% uptime.Key Capabilities
Performance-first inference: H100 support, low latency, and high throughput with published benchmarks and speedups .Production readiness: autoscaling, observability, tracing, and versioning across the full deployment lifecycle .Agentic and compound AI: reduced hop latency, per‑step hardware control, and built‑in telemetry via [Chains](https://www.baseten.co/blog/baseten-chains-for-production-compound-ai-systems) plus reliability guidance for [agent patterns](https://www.baseten.co/blog/how-to-build-reliable-ai-agents).Flexible runtime and interfaces: [vLLM](https://docs.baseten.co/examples/vllm), [TensorRT‑LLM](https://docs.baseten.co/examples/tensorrt-llm), [gRPC](https://docs.baseten.co/development/model/grpc), and OpenAI‑compatible patterns.Ecosystem orchestration: [LangChain and LlamaIndex support](https://docs.baseten.co/development/concepts) with additional [integrations](https://docs.baseten.co/inference/integrations).Deployment Options
Baseten Cloud: fully managed, production‑grade inference .Self‑Hosted (VPC): run the platform in your own VPC for data control, compliance, and custom networking .Hybrid: keep steady workloads in your cloud with burst spillover into Baseten’s fleet for elasticity .Performance and Reliability
99.99% uptime via active‑active, multi‑cloud capacity management .Demonstrated gains on modern GPUs, including H100 throughput and latency improvements with transparent hourly pricing .Case study: [Zed Industries](https://www.baseten.co/resources/customers/zed-industries-serves-2x-faster-code-completions-with-baseten) achieved 45% lower latency, 3.6x higher throughput, and 100% uptime for code completion.Agent and Compound AI Workflows
Chains framework for multi‑step orchestration with per‑step hardware selection, fewer network hops, and integrated observability .Best practices for building reliable agents, tool use, data access, and orchestration patterns .Integrations and Partnerships
Orchestration and SDKs: [LangChain](https://docs.baseten.co/development/concepts), LlamaIndex; [LiteLLM and others](https://docs.baseten.co/inference/integrations).Model runtimes and protocols: [vLLM](https://docs.baseten.co/examples/vllm), [TensorRT‑LLM](https://docs.baseten.co/examples/tensorrt-llm), [gRPC](https://docs.baseten.co/development/model/grpc), OpenAI‑compatible endpoints.Data and infra examples: MongoDB Atlas for compound AI .Cloud partners and capacity: [Google Cloud collaboration](https://cloud.google.com/blog/products/ai-machine-learning/how-baseten-achieves-better-cost-performance-for-ai-inference), [Vultr alliance](https://blogs.vultr.com/baseten-cloud-alliance).Use Cases
Real‑time LLM inference for chat, tools, and code completion.Low‑latency ASR and TTS for voice products, including high‑performance [Whisper](https://www.baseten.co/blog/the-fastest-most-accurate-and-cost-efficient-whisper-transcription) and [Praktika](https://www.baseten.co/resources/customers/praktika) at production scale.Retrieval, reranking, and search/recommendation pipelines.Batch and streaming inference for personalization, classification, and embeddings.Multi‑step agent workflows with Chains for compound AI.Who It’s For
Product and platform teams shipping AI features in production.ML engineers who want fast, reliable inference without building infra.Enterprises requiring VPC deployments, compliance, and SLAs.Startups seeking usage‑based pricing with a quick path from prototype to production.Pricing and Free Trial
Usage‑based per‑minute pricing with free credits; no platform fee for non‑Enterprise workspaces .Customers and Case Studies
Notable users include OpenEvidence, Writer, Patreon, Latent, Praktika, and toby .Highlight: [Zed Industries](https://www.baseten.co/resources/customers/zed-industries-serves-2x-faster-code-completions-with-baseten) improved speed, throughput, and uptime on code completion workloads.Patreon’s production deployment is profiled here: [Patreon case](https://www.baseten.co/resources/customers/patreon).Market Signals and Sentiment
Pros:Strong performance focus and production‑grade inference at scale .Ease of deploying LLMs and ASR/TTS (e.g., Whisper); quick path to serving fine‑tunes .Self‑hosted and hybrid options appeal to security‑sensitive teams .Cons:Cost scrutiny vs. DIY GPU hosting for steady, predictable workloads .Complex custom workflows (e.g., ComfyUI, bespoke pipelines) may require additional setup and expertise .Limited third‑party review volume on G2/Capterra today .Company and Funding
Headquartered in San Francisco with an employee range of 51–200 .Recent funding to scale performant, reliable, and cost‑efficient inference:[Series C: $75M](https://www.baseten.co/blog/announcing-baseten-75m-series-c)[Series D: $150M](https://www.baseten.co/blog/announcing-baseten-150m-series-d)Why Baseten
Purpose‑built for production AI inference with a focus on speed, reliability, and cost efficiency.Flexible deployment (Cloud, VPC, Hybrid) and broad ecosystem integration.Proven results with real‑world customers and transparent performance reporting.Explore More
Product overview: [Baseten Inference Stack](https://www.baseten.co/resources/guide/the-baseten-inference-stack)Compound AI and agents: [Chains framework](https://www.baseten.co/blog/baseten-chains-for-production-compound-ai-systems)Deployment options: [Cloud](https://www.baseten.co/deployments/baseten-cloud) • [Self‑Hosted](https://www.baseten.co/deployments/baseten-self-hosted) • [Hybrid](https://www.baseten.co/deployments/baseten-hybrid)Pricing and credits: [Pricing](https://www.baseten.co/pricing) • [Free credits](https://www.baseten.co/resources/changelog/usage-based-pricing-with-free-credits)Customer stories: [All customers](https://www.baseten.co/resources/customers) • [Zed case study](https://www.baseten.co/resources/customers/zed-industries-serves-2x-faster-code-completions-with-baseten)
