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Parasail vs OpenScale
Parasail serves any Hugging Face model across serverless, dedicated and batch tiers. OpenScale sells one open model at a promotional low price.
By The Subconscious Team · Updated
Parasail vs OpenScale: key differences
Parasail aggregates GPUs across about 40 data centers and serves curated serverless models, elastic and dedicated endpoints with latency SLAs, and batch on any Hugging Face model at half of serverless pricing. OpenScale serves DeepSeek V4.1 Flash at $0.06 in, $0.003 cached and $0.24 out per million tokens under a 50% promotion, at 200+ tokens per second, with a fast tier at about twice the speed. OpenScale's own price table lists Parasail at $0.30 in and $1.20 out on the same model.
Parasail is the more flexible option for teams that need their own models, private repos, batch jobs or dedicated capacity under ZDR and SLA agreements. OpenScale fits teams that only need DeepSeek V4.1 Flash for coding agents and care most about the real-time cached-input price.
What Parasail and OpenScale do
Parasail
Parasail calls itself the inference cloud for AI-native startups. It aggregates GPUs across about 40 data centers in 15 countries, runs some clusters of its own, and since July 2026 has deployed d-Matrix Corsair accelerators alongside NVIDIA Hopper and Blackwell, all sold through one OpenAI-compatible API. It raised a $32M Series A in April 2026, led by Touring Capital and Kindred Ventures. Customers choose serverless per-token endpoints across about 40 curated models, Elastic Endpoints that scale with traffic and bill tokens at 1.25x serverless rates on selected models, dedicated deployments with negotiated latency SLAs, or batch. Its commit-to-spend model lets one commitment draw down across any model or hardware.
Example models: Kimi K3, DeepSeek V4.1 Flash, GLM-5.3, MiniMax M3
Full Parasail profileOpenScale
OpenScale is a Y Combinator-backed inference API built by LatentSpace and run out of Singapore. It sells open models behind one endpoint that speaks Chat Completions, the OpenAI Responses API and Anthropic Messages, so Claude Code, Codex, OpenCode, Cline, GitHub Copilot, Zed and other coding agents can point at it with a base URL and key. Its public catalog today is DeepSeek V4.1 Flash in two versions, standard and fast, both with a 1M token context window and up to 384K output tokens.
Example models: DeepSeek V4.1 Flash
Full OpenScale profileShould you choose Parasail or OpenScale?
Parasail vs OpenScale at a glance
| Attribute | Parasail | OpenScale |
|---|---|---|
| Model access | Any Hugging Face model | Open weights |
| Flagship models | Kimi K3, DeepSeek V4.1 Flash, GLM-5.3, MiniMax M3 | DeepSeek V4.1 Flash |
| Speed | 600ms p99 real-time budget | 200+ tok/s; fast tier ~2x |
| Price | Per-parameter rates; batch 50% off | $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash) |
| Customization | Private Hugging Face repos | N/A |
| Deployment | Serverless, elastic, dedicated, batch | Serverless API |
| Long context | Varies by model | 1M context |
Frequently asked questions
What is the difference between Parasail and OpenScale?
Parasail serves any Hugging Face model across serverless, dedicated and batch tiers. OpenScale sells one open model at a promotional low price.
When should I choose Parasail over OpenScale?
Any Hugging Face model, private repos included; Large batch and eval jobs; Dedicated endpoints with latency SLAs.
When should I choose OpenScale over Parasail?
Cheaper real-time DeepSeek V4.1 Flash calls; Cache-heavy coding agent traffic; No commitments or sales calls.
Is Parasail or OpenScale cheaper?
Parasail: Per-parameter rates; batch 50% off. OpenScale: $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, Parasail or OpenScale?
Parasail: Varies by model. OpenScale: 1M context.
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.