The Inference Cloud for AI-native startups

Built for reliability, performance, and flexibility to scale.

mem0MiniMaxReflowVeniceZElicitSkyfall AINeuralwatt
Model library

Every model, one endpoint

Browse 40+ open and frontier models on Parasail's inference cloud. Filter by category, compare specs, and call any model with one OpenAI-compatible API.

Agentic optimization

Get performance tuned to your needs

Strike your own balance of speed, quality, and cost and an optimization agent tunes your deployment to hit it. Lossless by default, with no hidden quantization. Any lossy speedup is yours to opt into.

Built for production

Commit to spend, not GPUs

Elastic endpoints support selected models, with more added individually. Contact sales to set up an endpoint or discuss custom models and configurations.

Capacity that follows demand

Elastic endpoints give eligible models dedicated GPU performance, billed per token — no GPU-hour commitment or idle-GPU bill. One pricing tier: 25% above the model’s Serverless input and output token rates.

Fixed capacity means guessing

Forecast high and you're paying for GPUs sitting idle. Forecast low and you're throttling requests right when demand peaks. Either way, you're locked into a number that rarely matches reality.

Built for production

One API for any model

One endpoint, any model — frontier open models and your own fine-tunes, day zero.

Engineering notes &
inference deep dives

How we run open models fast, cheap, and at scale — plus product updates and the economics of serving inference in production. Written by the team behind the infrastructure.

Read all articles
Built for production

Your questions, answered.

We're paying a closed-model vendor directly. Can we switch?

Yes — one of the most common reasons teams come to us. Parasail runs open-source models on dedicated infrastructure without single-vendor dependency. Capacity and rate limits depend on your endpoint. Most teams run Parasail alongside their existing setup first, then migrate workloads over.

Are the models as capable as Claude or GPT for my use case?

For most production use cases, yes — and for some, better. The best open models (Llama, DeepSeek, Qwen, Kimi) have closed the gap, and for domain-specific tasks a well-tuned open model often outperforms a general closed one. For sales-assisted deployments, our team can help evaluate models against your workload.

Can I use specialized or fine-tuned models?

Yes — contact our team for specialized or fine-tuned models, custom architectures, and sidecar containers. Elastic endpoints support selected models, with additional models rolling out individually. Contact sales to set up an endpoint and discuss availability for your workload.

If something breaks, can I talk to a person who'll fix it?

Yes — you can contact our team for help. If you need dedicated support or specific service guarantees, talk to us about your deployment requirements.

How fast can we get up and running?

Contact sales to set up an Elastic endpoint. We support selected models, with more added individually; our team will confirm model availability and setup details for your workload. Contact us to discuss custom models and configurations, too.

Why not just self-host?

Self-hosting looks cheaper until you account for MLOps headcount (two to three engineers), idle GPU burn, scaling complexity, and constant maintenance as models evolve. Elastic endpoints provide dedicated GPU performance for eligible models without managing infrastructure or making a GPU-hour commitment. Contact sales to set up an endpoint or discuss custom models and configurations.

Start building today

Instantly run any open model — popular or specialized.