Parasail

Parasail is an inference cloud offering 40+ open and frontier models through one OpenAI-compatible API, with per-token pricing, elastic dedicated-GPU endpoints and an optimization agent for tuning speed, quality and cost.

Parasail is an inference cloud aimed at AI-native startups that want to run open and frontier models in production without operating their own GPU fleet. Its model library lists more than 40 open and frontier models, among them GLM-5.3, Kimi K3, DeepSeek V4 Flash and MiniMax M3, and every model is reachable through a single OpenAI-compatible API. Teams can also bring their own fine-tunes or specialized architectures by talking to the sales team. The service is built around per-token billing. Serverless access charges by input and output tokens, while Elastic endpoints give eligible models dedicated GPU performance that still bills per token, so there is no GPU-hour commitment and no idle-GPU charge. The Elastic tier is priced at 25% above the model's Serverless token rates. Elastic endpoints cover selected models, with more added one at a time, and setup runs through a conversation with sales rather than a self-serve form. In practice, a developer signs in to the platform, picks a model from the library, and points an existing OpenAI-style client at Parasail's endpoint. An optimization agent can then tune a deployment toward a chosen balance of speed, quality and cost. Tuning is lossless by default, with no hidden quantization, and any lossy speedup has to be opted into. That default matters for teams comparing output quality against a closed vendor. Parasail positions itself against two alternatives: paying a closed-model API directly, and self-hosting open models. Its argument against self-hosting centers on MLOps staffing, idle hardware and ongoing maintenance as models change. Against closed APIs, it pitches a gradual migration in which routine workloads move to open models while the existing setup keeps running alongside. The blog adds practical material on throughput tuning with vLLM, migration decisions and cutting coding-agent costs with OpenCode. It suits engineering teams comfortable with API integration and cost analysis, less so those wanting a no-code product.