Run and fine-tune models. Deploy custom models. All with one line of code.
Memory that reasons
Stage
Not given
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Founded
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Based in
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US
Pricing model
Paid
Freemium
Pricing
Most models billed by time based on hardware used (CPU $0.000100/sec, T4 GPU $0.000225/sec, L40S GPU $0.000975/sec). Some models billed by input/output tokens or generated items. Private custom models billed for all uptime; fast-booting fine-tunes billed only for active processing.
Free plan at $0 USD; Pro plan at $5 USD per month.
Key features
Run thousands of community-contributed open-source models
Fine-tune models with custom data to create specialized versions
Deploy custom models using Cog, an open-source packaging tool
Automatic scaling based on demand
Pay only for compute time used
Image generation from text
Entity-graph spreading activation for cross-vocabulary retrieval
Works with any LLM model
No LLM or GPU in retrieval path
Point-in-time and windowed recall
Timestamped memories
Fixed recall cost as memory grows
What makes it different
One-line code interface for running models without ML expertise
Automatic infrastructure scaling without manual management
Open-source community with thousands of production-ready models
Fine-tuning capability to customize models for specific tasks
Reaches answers across unrelated documents that share no keywords, where vector search scores zero
Deterministic retrieval with no model in the path, so results never vary between queries
Constant per-query cost regardless of memory size, even at 32,000 words
No infrastructure to run—no vector database, cluster, or GPU needed
Works with any model, so small local models gain the most from better retrieval