Subconscious
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Subconscious vs Parasail

Parasail optimizes cheap batch on aggregated GPUs. Subconscious optimizes the trace itself, keeping live agents fast past 200K tokens on dedicated infrastructure.

By The Subconscious Team · Updated

Subconscious vs Parasail: key differences

Parasail optimizes the fleet, and Subconscious optimizes the trace. Parasail owns no data centers. It aggregates GPUs from many providers, runs any Hugging Face model including private repos, and prices by parameter count and precision, so a 4B to 8B model costs $0.03 in and $0.06 out at FP4. Batch runs at half of serverless, with cached tokens another 50% off. Subconscious works inside the model's context. Its runtime prunes the KV cache and preserves suffix state, which cuts cost 50% to 80% versus standard inference, and it bills only those processed tokens.

Offline evals, embeddings and large data jobs belong on Parasail, which also suits startups moving from closed APIs to dedicated open-model endpoints under a ZDR and SLA agreement. The trade-off is that its performance depends on the underlying hardware providers. Subconscious is the better fit for interactive and long-running agents, where it delivers 2x faster task completion and a 5M+ effective context window, and for teams that want a fixed deployment on dedicated or on-prem hardware. A team could batch its evals on Parasail and run the agent those evals measure on Subconscious.

What Subconscious and Parasail do

Subconscious

Subconscious is an MIT CSAIL spinout in Kendall Square that builds inference for long-horizon agents, the workloads where a single trace runs past 200K tokens and often into the millions. Its runtime drops in as a replacement for vLLM or SGLang. Instead of rereading an ever-growing context on every step, it prunes the KV cache and preserves suffix state, and Subconscious co-designs the runtime with post-trained model variants it calls Marathon. Against open models on standard inference, Subconscious delivers 2x faster task completion, delivers a 5M+ effective context window, cuts cost 50% and up to 80%, and scores neutral to 10% better on agentic benchmarks.

Example models: GLM 5.3, DeepSeek V4.1 Flash

Full Subconscious profile

Parasail

Parasail calls itself the inference cloud for AI-native startups. Instead of owning data centers, it aggregates GPUs from many hardware providers and sells them through one OpenAI-compatible API. Customers choose serverless per-token endpoints, Elastic Endpoints that scale with traffic and bill only for tokens used, 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: GTE-Qwen2, Qwen3-VL-8B-Instruct

Full Parasail profile

Should you choose Subconscious or Parasail?

Subconscious

Choose Subconscious for

  • Live agents running past 200K tokens
  • Dedicated or on-prem serving instead of aggregated third-party GPUs
  • Processed-token billing on long traces

Parasail

Choose Parasail for

  • Offline evals and embeddings at half of serverless price
  • Batch jobs on private Hugging Face repos
  • Flexible commit-to-spend across models and hardware

Subconscious vs Parasail at a glance

AttributeSubconsciousParasail
Model accessOpen weightsAny Hugging Face model
Flagship modelsGLM 5.3, DeepSeek V4.1 FlashGTE-Qwen2, Qwen3-VL-8B-Instruct
Speed2x faster task completion600ms p99 real-time budget
Price50–80% lower cost; billed on processed tokensPer-parameter rates; batch 50% off
CustomizationMarathon post-trained variantsPrivate Hugging Face repos
DeploymentManaged API, dedicated, on-premServerless, elastic, dedicated, batch
Long context5M+ effective contextVaries by model

Frequently asked questions

What is the difference between Subconscious and Parasail?

Parasail optimizes cheap batch on aggregated GPUs. Subconscious optimizes the trace itself, keeping live agents fast past 200K tokens on dedicated infrastructure.

When should I choose Subconscious over Parasail?

Live agents running past 200K tokens; Dedicated or on-prem serving instead of aggregated third-party GPUs; Processed-token billing on long traces.

When should I choose Parasail over Subconscious?

Offline evals and embeddings at half of serverless price; Batch jobs on private Hugging Face repos; Flexible commit-to-spend across models and hardware.

Is Subconscious or Parasail cheaper?

Subconscious: 50–80% lower cost; billed on processed tokens. Parasail: Per-parameter rates; batch 50% off. The cheaper choice depends on the model and workload.

Which has more context, Subconscious or Parasail?

Subconscious: 5M+ effective context. Parasail: Varies by model.

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Run your longest agent traces on Subconscious

Point the OpenAI or Anthropic SDK, or the coding agent you already use, at Subconscious. Keep Parasail for the work it does best and send the long runs to us.

Get an API keyRead the docs