Baseten
Production model serving that hit $600M ARR in 2026.
Overview
A managed inference platform for deploying, autoscaling and serving ML/LLM models via Truss, its open-source packaging framework. Built for ML engineering teams shipping custom or open-weight models.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 13 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- Per-token billing
- No infra to manage
- Autoscaling
- Truss packaging
- Autoscaling endpoints
- Caching and monitoring
- GPU-hour billing
- Reliability SLAs
- Best-in-class GPU utilization
- Dedicated support
- Custom terms
What you can produce with Baseten
- Autoscaling HTTPS inference endpoints with GPU orchestration
- Truss open-source model-packaging framework (~1.2k stars)
- Supports transformers, diffusers, PyTorch, vLLM, TensorRT-LLM
- Built-in caching, monitoring and observability
- Usage-based billing on tokens or GPU-hours
- Enterprise SLA contracts
- Model APIs for open-source models plus custom deployments
ASEAN Perspective
Baseten in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
This is infrastructure for teams that have models and engineers to run them, not a point-and-click app. Truss, Baseten's open-source framework, turns a Hugging Face or custom model into an autoscaling HTTPS endpoint and handles GPU orchestration, caching and monitoring — the friction it removes is real, and the observability tooling gets specific praise. The business is on a tear: $600M annualized revenue by March 2026, up roughly 1,900% year-over-year, backed by a $1.5B raise at a $13B valuation. That momentum buys reliability engineering and enterprise SLAs, which is exactly what production inference customers pay for. The cost caveat is blunt: H100 capacity lists around $6.50/GPU-hour, among the highest in the category, so heavy workloads add up fast. Right for engineering teams serving custom or open-weight models where uptime has a budget; overkill for anyone who just wants a token endpoint.
What people say
Baseten's 2026 story is as much a funding story as a product one. It raised $1.5B at a $13B post-money valuation in June 2026, following a $300M Series E at $5B in January (IVP and CapitalG leading, with Nvidia putting in $150M). Total funding sits around $2.085B. Revenue tracked the hype: $600M annualized by March 2026, up about 1,900% year-over-year from $200M in December 2025.
The product reviewers actually touch is Truss, the open-source packaging framework — around 1.2k GitHub stars — that containerizes models across transformers, diffusers, PyTorch, vLLM and TensorRT-LLM into autoscaling endpoints. The consistent praise: it cuts the friction of turning a Hugging Face model into a production API, the GPU orchestration and caching are handled for you, and observability is solid. Enterprise teams single out SLA contracts as the reason to be here when reliability has a budget.
The recurring caveat is who it's for. Multiple write-ups frame Baseten as built for MLOps and ML-engineering teams deploying their own models, not for developers who just want a hosted token endpoint — one review is explicitly titled around finding "a simpler alternative." If you don't have custom models and the engineers to package them, the platform's depth is wasted.
Cost is the other flag. A Baseten H100 lists around $6.50/GPU-hour, described as among the highest in the category — Modal, DeepInfra and GMI Cloud undercut it in head-to-head pricing comparisons. Baseten's answer is utilization and reliability: best-in-class GPU efficiency plus the operational tooling that keeps production endpoints healthy. Whether that premium pays off depends on scale and how much downtime would actually cost you. For funded teams shipping custom or open-weight models to production, the pedigree, tooling and SLAs line up; for cost-first or hobbyist inference, cheaper token clouds are the obvious call.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Baseten's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Baseten unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
For the latest details, please refer to Baseten directly →
Spotted something out of date? Suggest an update →
Alternatives to Baseten
More in LLMs & Chat
