Parasail
Brokered GPU inference: pay per token, skip the long-term contract
Overview
Parasail brokers a global GPU pool into serverless, dedicated and batch inference for open models like DeepSeek, Llama and Qwen, or your own weights, billing per token even on dedicated hardware — aimed at developers who want scale without GPU contracts.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 12 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- No contracts
- Autoscaling
- Wide open-model catalog
- Guaranteed private capacity
- Custom/fine-tuned model support
- Flat 50% discount vs serverless
- Additional 50% off cached tokens
What you can produce with Parasail
- Serverless pay-per-token inference on open models (DeepSeek, Llama, Qwen, etc.)
- Dedicated single-tenant endpoints billed per token, not per reserved hour
- Batch processing at 50% off serverless rates
- 50% discount on cached tokens
- Support for custom/fine-tuned model weights
- H100, H200, A100 and RTX 4090 GPU access
- No long-term contracts
ASEAN Perspective
Parasail in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Parasail's edge is billing dedicated GPU capacity by the token rather than the hour, which it can apparently do because fleet utilization runs around 95% — high enough that per-token math works out even on hardware nominally reserved for one customer. Combined with serverless and batch tiers (the latter at a flat 50% discount, with another 50% off cached tokens), it covers most of the shapes a production inference workload takes.
The company is young and moving fast: a $32M Series A in April 2026 on top of a $10M seed, claims of 500 billion tokens a day flowing through the platform, and a GPU fleet the company says outsizes Oracle's entire cloud. None of that is independently audited, so the real test is whether that claimed supply and 95% utilization hold up under your specific traffic pattern rather than the marketing number. Built for developers and infra teams, not consumers.
What people say
Parasail launched with $10M in seed funding and closed a $32M Series A in April 2026 — co-led by Touring Capital and Kindred Ventures with Samsung NEXT, Flume Ventures and Banyan Ventures participating — bringing total funding to $42M. CEO Mike Henry has said the platform is already moving around 500 billion tokens a day, which the company frames as evidence that pay-per-token inference, rather than provisioned capacity, is where developer demand is heading.
The product has three shapes. Serverless endpoints handle real-time inference on open models (DeepSeek, Llama, Qwen and others) or a customer's own weights, billed per token. Dedicated instances are private, single-tenant deployments — Parasail's pitch here is that its fleet runs at roughly 95% utilization, which is high enough that it can still bill dedicated hardware per token rather than per reserved hour, passing the efficiency back as savings. Batch processing gets a flat 50% discount off the serverless rate, and cached tokens are a further 50% off on top of that, which matters for workloads with repeated context.
TechCrunch reported that Parasail's on-demand GPU fleet — spanning H100, H200, A100 and RTX 4090 — was larger than Oracle's entire cloud footprint, a claim the company has repeated in its own materials. That kind of figure is hard to verify independently and should be read as a supply claim rather than an audited fact, but it's consistent with the deployment speed the company advertises: going from a single GPU to a cluster within minutes, without a DevOps team in the loop.
Independent user reviews are thin, which tracks for a developer-infrastructure product barely two years old. The clearest customer voice available is company-sourced: one client described the team as "responsive, technically excellent" and credited them with getting "high-throughput screening into production with minimal engineering overhead." No organic Reddit or Trustpilot discussion turned up in research, so anyone evaluating Parasail for production traffic is largely working from the company's own claims plus press coverage of the funding rounds.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Parasail's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Parasail unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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