Hugging Face
Serverless Inference API — 150K+ open models including Llama, Qwen, and FLUX
Hugging Face is the central hub for open-source AI models, hosting 150K+ models across text, image, audio, and video. Its Serverless Inference API provides pay-per-request access to popular open-weight models including Llama 3.3 70B, Qwen 2.5 72B, and FLUX.1-dev — without managing infrastructure. Ideal for developers who want open-weights models without self-hosting.
The world's largest open-model hub — Serverless Inference API gives instant pay-per-request access to Llama, Qwen, FLUX, and 150K+ other open-weight models without any infrastructure setup.
- Largest open-model hub — 150K+ models across all modalities
- Serverless Inference API requires no infrastructure management
- Access to Llama, Qwen, Mistral, FLUX, and hundreds of other open-weight models
- Free tier available for low-volume experimentation
- Deep ecosystem: datasets, Spaces, model cards, and community fine-tunes
- Serverless API has cold-start latency for less popular models
- No proprietary frontier models — all hosted models are open-weight
- Rate limits on free tier; dedicated endpoints required for production SLAs
- Pricing varies by model and can be less predictable than fixed-rate APIs
Hugging Face Models
| Model | Modality | Tier | Price | Cached /1M | TTFT | Throughput | Context | Intel. | Caps | |
|---|---|---|---|---|---|---|---|---|---|---|
FLUX.1-dev FLUX | Image | advanced | $0.03 per image EST Aug 2026 | — | 5.0s | 0 t/s | — | 0 | ||
Llama-3.3-70B-Instruct Llama 3.3 | Chat | advanced | $0.59/ $0.79 in / out per 1M EST Aug 2026 | — | 900ms | 55 t/s | 128K | 72 | ||
Qwen2.5-72B-Instruct Qwen 2.5 | Chat | advanced | $0.59/ $0.79 in / out per 1M EST Aug 2026 | — | 850ms | 60 t/s | 131K | 74 |
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Full comparison tableHugging Face LLM pricing overview
Hugging Face is an inference API provider that hosts open-weight and third-party large language models. Hugging Face is the central hub for open-source AI models, hosting 150K+ models across text, image, audio, and video. Its Serverless Inference API provides pay-per-request access to popular open-weight models including Llama 3.3 70B, Qwen 2.5 72B, and FLUX.1-dev — without managing infrastructure. Ideal for developers who want open-weights models without self-hosting. Common use cases include Open-model inference, Prototyping, Image generation, Research. Headquartered in New York, NY, founded 2016. All models are accessible via a REST API compatible with standard OpenAI-style request formats, enabling drop-in integration with most LLM frameworks and orchestration tools.
Hugging Face vs other LLM providers
Hugging Face competes with OpenAI, Anthropic, Google, Groq, Together AI, Mistral, Cohere, and other inference API providers across dimensions of price, throughput, latency, context window, and model intelligence. The world's largest open-model hub — Serverless Inference API gives instant pay-per-request access to Llama, Qwen, FLUX, and 150K+ other open-weight models without any infrastructure setup. Use the LLM provider comparison tool to see Hugging Face token pricing, latency, and throughput side-by-side with any other provider. The full LLM pricing table shows all providers ranked by input token cost, output token cost, and throughput in a single sortable view.
Why choose Hugging Face?
Hugging Face stands out because: The world's largest open-model hub — Serverless Inference API gives instant pay-per-request access to Llama, Qwen, FLUX, and 150K+ other open-weight models without any infrastructure setup.. The API currently offers 3 models, spanning 3 advanced tiers. For teams running high-volume inference workloads, prompt caching and batch API endpoints can reduce effective input token costs by 50–90% — check the context window cost guide for a full breakdown of caching economics.
Understanding Hugging Face token pricing
Hugging Face charges separately for input (prompt) and output (completion) tokens, priced per 1M tokens in USD. Output tokens are typically 3–5× more expensive than input tokens due to the compute cost of autoregressive generation. The cheapest {meta.name} input rate is currently $0.59/1M tokens. Prices shown are sourced from Hugging Face's public pricing page and updated every 15 minutes. Need help estimating your spend? Read the LLM API cost calculator guide — it covers tokens, context windows, prompt caching, and batch discounts with worked examples for RAG, chat history, and document processing workloads.
Hugging Face context window and model capabilities
Context window size directly affects both capability and cost — every token in the context window is charged as an input token. Hugging Face's largest context window is 131K tokens. For RAG and document processing workloads, longer context windows enable richer retrieval but increase per-call costs proportionally. Prompt caching — where supported — stores the KV state of repeated prefixes and charges 75–90% less for cache hits, making it the most impactful cost optimization for applications with consistent system prompts or retrieved documents. See the LLM context window cost guide for a full analysis of how context length affects your API bill.
Self-hosted vs managed inference: when Hugging Face makes sense
Managed inference APIs like Hugging Face eliminate infrastructure overhead — no GPU provisioning, driver management, or model serving stack to maintain. The trade-off is cost at scale: a single H100 at ~$2.50/hr can serve ~500K tokens/min of Llama 3.3 70B, which at Hugging Face API rates would cost significantly more per token. The break-even point depends on your request volume, latency requirements, and engineering capacity. For teams processing fewer than ~10M tokens/day, managed APIs are almost always cheaper when total cost of ownership is considered. Above that threshold, self-hosted inference on rented GPU compute typically wins on unit economics. Read the cheapest GPU cloud guide for a full break-even analysis. Historical Hugging Face token price data is available in the LLM price history charts.
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