Hyperbolic
Serverless inference API and GPU cloud for open-source LLMs - access Llama, DeepSeek, and Mistral with OpenAI-compatible endpoints from $0.04 per million tokens.
Hyperbolic is a San Francisco-based AI infrastructure company that offers two products: a serverless inference API for running popular open-source LLMs and an HPC GPU cloud for training workloads. The inference API provides access to Llama 3.3, DeepSeek V3, Mistral, Qwen, and dozens of other models via an OpenAI-compatible interface, letting teams swap the API endpoint in existing code without rewrites. Pricing starts at $0.04 per million tokens for smaller models - significantly below managed cloud provider rates. Hyperbolic raised a $12M Series A from a16z in 2024 and is particularly popular with startups and research teams running open-source model workloads at cost-sensitive scales. New accounts receive $1 in free API credits to evaluate the platform before committing.
Key Features
- Serverless LLM inference - access Llama 3.3, DeepSeek V3, Mistral, Qwen, and more without managing servers
- OpenAI-compatible API - drop-in replacement for OpenAI SDK calls with no code changes beyond the base URL
- Pay-per-token pricing from $0.04/1M tokens - no minimum spend or reserved capacity commitment
- HPC GPU cloud - rent H100, A100, and RTX clusters for training and fine-tuning workloads
- Low-latency routing - global inference infrastructure with sub-second TTFT for production apps
- Dedicated deployments - reserve capacity for a specific model with guaranteed throughput SLAs
Use Cases
- Startups building LLM-powered products who need open-source model access without self-hosting complexity
- Research teams running evaluations and experiments across multiple open-source models at budget-friendly rates
- Developers migrating off OpenAI who want drop-in API compatibility with open-source model options
- ML engineers renting H100 cluster time for fine-tuning and training runs without long-term cloud commitments
Pros
- $0.04/1M tokens for smaller models - measurably cheaper than AWS Bedrock or Azure equivalents for open-source workloads
- OpenAI-compatible API means zero integration lift - change one line of code to test models from a different provider
- Backed by a16z and growing fast - investment signals platform reliability and ongoing model catalog expansion
Cons
- Catalog covers popular open-source models but lacks proprietary models - not a replacement for OpenAI or Anthropic APIs
- SLA guarantees on serverless endpoints are weaker than dedicated-tier plans, causing variable latency under load spikes
- Newer provider with less community documentation and fewer tutorials than Together AI or Fireworks
Hyperbolic Alternatives
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Together AI
Fast open-source LLM inference platform with 200+ models, fine-tuning, and the largest selection of serverless AI APIs outside OpenAI.
Fireworks AI
High-speed LLM inference API by ex-Meta AI researchers, serving Llama 3, Mixtral, and 50+ open-source models at 4x standard throughput with fine-tuning support.
Groq
Ultra-fast LLM inference API using custom LPU hardware - 400–800 tokens/second on Llama 3.3, Gemma, and Mixtral models.
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