Baseten

What Baseten does

Baseten is an AI infrastructure platform that provides the tooling, expertise, and hardware necessary to bring AI products to market quickly. It offers a high-performance inference platform with dedicated inference for high-scale workloads, pre-optimized Model APIs, and the ability to run training on inference-optimized infrastructure. The platform is built on a proprietary Inference Stack that utilizes cutting-edge performance research, custom kernels, and advanced caching, combined with highly performant and reliable infrastructure for global availability and 99.99% uptime. Baseten supports deploying open-source, custom, and fine-tuned AI models, and offers flexible deployment options including Baseten Cloud, self-hosted, and hybrid solutions. It is engineered for demanding Gen AI applications, including rapid image generation, optimized transcription, state-of-the-art text-to-speech, performant LLM runtimes, and ultra-low-latency compound AI.

Products

• Baseten Inference StackProprietary technology utilizing cutting-edge performance research, custom kernels, and advanced caching for high-performance inference.
• Dedicated InferenceInfrastructure purpose-built for high-performance inference at massive scale, supporting open-source, custom, and fine-tuned AI models.
• Pre-optimized Model APIsInstant access to optimized AI models for testing, prototyping, or production, including Kimi K2.6, DeepSeek V4, and GLM-5.2.
• Frontier GatewayAn inference API powered by Baseten to monetize models faster, offering white-labeled API endpoints, API key management, usage limits, and billing/metering.
• Baseten CloudFully-managed, global deployment options with massive horizontal scale and single-tenant clusters for workload isolation.
• Self-hostedDeployment option for low latency, high throughput, and developer experience within a customer's own VPCs.
• Baseten HybridCombines self-hosted deployments with on-demand flex capacity on Baseten Cloud.
• Baseten Embeddings Inference (BEI)Optimized for embeddings with high throughput and low latency.
• Baseten ChainsFramework for orchestrating multi-step AI pipelines, enabling granular hardware and autoscaling for compound AI systems.
• TrussOpen-source framework for packaging models into deployable containers, supporting config-only deployments and custom Python model code.
• Engine-Builder-LLMInference engine for dense text generation models compiled with TensorRT-LLM, supporting lookahead decoding and structured outputs.
• BIS-LLMInference engine for large mixture-of-experts models with KV-aware routing and distributed inference.
• Training Jobs (GA)Framework-agnostic training product for running existing training scripts on managed GPUs, supporting multi-node training and on-demand compute.
• Loops (early access)Training SDK for long sequence length, async RL, and one-click checkpoint deploys, supporting 131K+ sequence length and 1T+ parameter model training.
• Baseten Inference RuntimePlatform for running models with low latency and high throughput, featuring automatic runtime builds, reliable speculation engine, modality-specific optimization, custom kernels, structured output, optional quantization, KV Cache optimization, request prioritization, and topology-aware parallelism.
• Custom ServersAllows deployment of any Docker image with full Baseten Inference Stack capabilities.

Key capabilities

• Fastest model runtimes
• Cross-cloud high availability
• Seamless developer workflows
• Bleeding-edge performance research
• Inference-optimized infrastructure
• DevEx built for rapid iteration
• Forward Deployed Engineers support
• Rapidly scale workloads across any cloud provider
• Global capacity
• Single-tenant and self-hosted deployments
• Custom performance optimizations for Gen AI
• Ultra-low-latency compound AI
• Dedicated inference for custom models
• 99.99% uptime
• Fast cold starts
• SOC 2 Type II and HIPAA compliant
• Unlimited autoscaling
• Priority access to high-demand GPUs
• Dedicated compute
• Higher Model API rate limits
• Custom SLAs
• On-demand flex compute
• Use existing cloud commitments
• Full control over data residency
• Custom global regions
• Advanced security and compliance
• Advanced RBAC with Teams
• Optimal model performance
• Reliable model serving
• Lower costs at scale
• Extensive model tooling
• Designed for sensitive workloads
• Flexible deployment options
• Instant access to leading models
• Streaming and diarization for transcription
• Accurate speaker tags
• OpenAI-compatible endpoints
• Multi-cloud Capacity Management (MCM)
• Observability, logging, and metrics
• CI/CD integration
• Live reload with Truss
• Custom hardware and autoscaling per step for Chains
• Asynchronous RL primitives
• Full ownership of trained weights
• Multi-node training
• On-demand compute for training
• SSH access for debugging training containers
• Automatic runtime builds
• Reliable speculation engine
• Modality-specific optimization
• Custom kernels
• Structured output
• Optional quantization
• KV Cache optimization
• Request prioritization
• Topology-aware parallelism
• API key management
• Auth with no latency overhead
• Usage limits
• Billing & metering
• White-labeled URL

Use cases

• Deploying open-source, custom, and fine-tuned AI models in production
• Testing new workloads and prototyping products
• Evaluating the latest AI models
• Training models and deploying them in one click
• Monetizing AI models
• Rapid image generation
• Optimized transcription and speaker diarization
• State-of-the-art text-to-speech for AI phone calls, voice agents, and translation
• Performant LLM runtimes
• Generating embeddings
• Building ultra-low-latency compound AI systems
• Real-time voice AI use cases like AI note-taking and live conferencing
• Content creation with image generation
• Creating lifelike avatars
• Building custom image generation pipelines
• Shipping LLM-powered applications
• Drafting text, summarizing documents, generating code with text agents
• Combining LLMs with live data retrieval (RAG)
• Automating complex housing and healthcare systems (e.g., patient scheduling, leasing, maintenance)
• Real-time AI code suggestions
• Building large world models
• Programmatic web with high-throughput agentic inference
• Reimagining code editors
• Building presentations with AI
• Transforming businesses with custom medical and financial LLMs
• Real-time text-to-speech for audio experiences
• Pharmaceutical search
• AI coding agents
• Ultra-fast AI agents

AI approach

Baseten provides an AI infrastructure platform for deploying, optimizing, and managing AI models in production. They offer dedicated inference for high-scale workloads, pre-optimized model APIs, and training infrastructure. Their proprietary Inference Stack utilizes performance research, custom kernels, decoding techniques, and advanced caching. They support open-source, custom, and fine-tuned models, and offer solutions for rapid image generation, optimized transcription, state-of-the-art text-to-speech, performant LLM runtimes, and ultra-low-latency compound AI. They also provide an SDK (Loops) for training and an open-source framework (Truss) for packaging models into deployable containers.

Tech named: TensorRT, SGLang, vLLM, TGI, TEI, Medusa, Eagle, TensorRT-LLM, ComfyUI, Whisper Large V3 Turbo, Whisper Large V3, Whisper Large V2, Qwen, DeepSeek, GLM, gpt-oss, Llama, Mistral, Gemma, Phi, Axolotl, TRL, Megatron, OpenAI SDK, Hugging Face, S3, W&B

Industries served

• Software Development
• Healthcare
• Real Estate
• Financial Services
• Marketing
• Media
• Gaming
• Legal
• Education
• Manufacturing
• Retail
• Telecommunications

What it says sets it apart

• Fastest model runtimes and cross-cloud high availability powered by proprietary Inference Stack
• Seamless developer workflows and rapid iteration capabilities
• Hands-on support from Forward Deployed Engineers from prototype to production
• Flexible deployment options: Baseten Cloud, self-hosted, and hybrid
• Engineered for demanding Gen AI apps with custom performance optimizations
• Optimized transcription with lowest latency, highest accuracy, and cost-efficiency
• State-of-the-art text-to-speech with real-time audio streaming and lowest time to first byte
• Highest throughput and lowest latency for embeddings (2x higher throughput, 10% lower latency)
• Ultra-low-latency compound AI with 6x better GPU usage and half the latency
• Single-tenant, region-locked, HIPAA compliant, and SOC 2 Type II certified deployments
• Cost-effective inference with optimal GPU utilization and efficient models
• OpenAI-compatible Model APIs for easy migration from closed models
• Comprehensive observability, logging, and budgeting built-in
• Multi-cloud Capacity Management for 100% uptime and elastic GPU pool
• Proprietary training SDK (Loops) for async RL and one-click checkpoint deploys
• Framework-agnostic training jobs with bare-metal like control on managed infra
• Inference Runtime with configurable performance techniques (TensorRT, SGLang, vLLM, TGI, TEI, custom kernels, structured output, quantization, KV cache optimization, request prioritization, topology-aware parallelism)
• White-labeled API endpoints for model monetization with Frontier Gateway
• Guaranteed reliability with 99.99% uptime and active-active redundancy
• Ability to scale to millions of users without needing an internal ML or infrastructure team