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Parasail

www.parasail.io

Inference cloud for open models with an OpenAI-compatible API, offering per-token serverless endpoints, elastic endpoints, dedicated GPU deployments and discounted batch jobs.

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About Parasail

Startups building on open-weight models such as Kimi, GLM, DeepSeek and Qwen need reliable, low-cost inference without running and scaling their own GPU servers.

Who it’s for

  • Developers switching from closed model APIs to open models through an OpenAI-compatible endpoint
  • AI startups running large evaluation, embedding or batch workloads that need a low per-token rate

When to consider it

Consider Parasail when you want to call recent open models through one OpenAI-compatible API, then move high-volume work to batch pricing or to elastic endpoints with dedicated GPU performance billed per token instead of per GPU hour.

Tradeoffs & limitations

  • Serverless prices are per 1M tokens and vary by model, for example DeepSeek V4 Flash at $0.14 input and $0.28 output, GLM-5.3 at $1.40 and $4.40, and Kimi K3 at $3.00 and $15.00; serverless has no minimums but only community support.
  • Elastic endpoints cost 25% above a model's serverless token rates, cover selected models only and are set up through sales; dedicated GPU deployments (B300, B200, H200, H100, RTX PRO 6000, RTX 5090) have no public hourly prices and require a quote.

SOTA overview · Documentation-based assessment · Sources & review method

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Sources & review method

Documentation-based assessment · Nov 2, 2026 · Prepared with AI assistance; not a hands-on benchmark.

Checked by SOTA · AI-assisted documentation review. Selection advice is our assessment; verify current requirements for your deployment.

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Import history & original evidence

Parasail official website

Scope: Product overview · Imported Nov 2, 2026

Inference cloud for open models with an OpenAI-compatible API, offering per-token serverless endpoints, elastic endpoints, dedicated GPU deployments and discounted batch jobs.

Based on official pages and announcements checked on 2026-11-02. No hands-on test, performance benchmark or popularity ranking is claimed.