Hugging Face
Hugging Face is an NYC-based AI platform company (founded 2016) whose Hub hosts 2M+ open-source models, 500K+ datasets, and 1.5M Spaces demo apps as of mid-2026; its open-source `transformers` Python library (Apache 2.0) reached v5.14.0 on July 15, 2026. Last disclosed valuation: $4.5B after a $235M Series D (Aug 2023) backed by Google, Amazon, Nvidia, IBM, and Salesforce; 2024 ARR estimated at $130.1M. Two paid inference products: Inference Endpoints (dedicated GPU hosting billed per-minute — A100 80GB $2.50/hr, H200 $5/hr on AWS, H100 $10/hr on GCP) and Inference Providers (serverless routing to 200+ third-party models, no HF markup, $2/mo free credits for PRO users). Hub tiers: Free, PRO $9/mo, Team $20/user/mo, Enterprise $50/user/mo. Current version/status: Platform continuously deployed (no version); `transformers` library v5.14.0 (Jul 15, 2026). License: Hub/platform: proprietary SaaS (free + paid tiers); `transformers` library: Apache 2.0; hosted models/datasets carry their own individual licenses. Pricing: Hub: Free / PRO $9/mo / Team $20/user/mo / Enterprise $50/user/mo; Inference Endpoints billed per-minute (A100 80GB $2.50/hr, H200 $5/hr on AWS, H100 $10/hr on GCP); Inference Providers is pass-through pricing with no HF markup plus $2/mo free credits for PRO users ($0.10 for free accounts). Maintained by Hugging Face, Inc. — independent company backed by Google, Ama
Pick Hugging Face to discover, version, and self-host open-source models via git-native workflows — nothing else matches its 2M-model catalog or the `transformers` library ecosystem. Skip Inference Endpoints for bursty serverless workloads: it bills the full hourly rate continuously once min replicas hit 1 (no scale-to-zero on GPUs), and its own GCP H100 rate ($10/hr) is nearly triple Modal's effective per-second cost (~$3.95/hr) or Together AI's dedicated H100 ($6.49/hr). For high-volume serverless LLM inference, Together AI or Modal beat it on price and cold-start latency — Inference Providers is a zero-markup router, not a compute optimizer. Known weakness: Inference Endpoints bill the full hourly GPU rate continuously whenever minimum replicas are set to 1 or more, even at zero traffic — a single always-on T4 ($0.50/hr) runs roughly $4,380/year before serving a single request, a cost trap widely flagged by users comparing it to true scale-to-zero competitors.
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