Bringing Generative AI

Within Reach

Custom AI Agents in 3 Clicks
Running On DF11

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DF11: The World's Most Optimized Format for LLMs

Reduced Memory Footprint by 30%

The first mathematically proven method to reduce memory requirements for LLMs without any accuracy loss. Run bigger models on smaller hardware with perfect fidelity.

30%

Memory Savings

100%

Standard Format

70%

DF11 Format

Memory Comparison

Standard Format

100%

DF11 Format

70%

30% Memory Savings

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Overview
Comparison
How It Works
Mathematically Lossless

DF11 preserves 100% of the model's accuracy by maintaining precision where it matters most in the weight distribution.

30% Memory Savings

Reduces model memory footprint by approximately 30%, allowing for larger models or more efficient deployment on the same hardware.

Universal Compatibility

Works with any LLM on standard hardware with minimal implementation effort. No retraining required.

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The Future of Model Efficiency

We believe DF11 marks the beginning of a new era in model memory efficiency—where developers no longer have to choose between size and quality. This isn't a compromise. It's a breakthrough, and we're excited to help the AI community and see the adoption of DF11, feel free to try it to try it out by yourself

Get Started with DF11

FineTune OpenSource LLMs

For your agent tasks in hours with no PhDs

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Simplified Process: No complex setup required

Our platform simplifies the fine-tuning process so you can focus on results rather than complex setup procedures.

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Rapid Deployment

From data to production in hours, enabling you to quickly deploy customized models that meet your specific needs.

IMPLEMENTATION SCENARIOS

Perfect For Every Use Case

Solo Developers

(Democratized AI)

Run larger models on limited hardware, trading a bit oflatency for a big memory win

Run 70B parameter models on consumer GPUs

Enterprise Deployment

(Cost Efficiency)

Cut memory use and bandwidth while preserving full fidelity and throughput.

30% reduction in GPU memory requirements

Edge Devices

(Democratized AI)

Enable advanced AI capabilities on resource-constrained devices.

Run 70B parameter models on consumer GPUs

Cloud Infrastructure

(Optimized ROI)

Reduce costs and increase model capacity in cloud environments.

30% reduction in GPU instance costs.

Latest Insights

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Pied Piper is Here with DFloat11

Introducing DFloat11—A Mathematically Lossless Way to Run LLMs on GPUs and CPUs

Who are we?

We're a frontier AI agent research lab firmly focused on advancing agent technology beyond current limitations. We believe that the current approaches most companies are taking with prompt engineering and RAG are ultimately a dead end for creating truly effective AI agents.

Our team brings together top researchers in model reinforcement learning, fine-tuning, synthetic data generation, performance optimization, and distributed systems. We're uniquely positioned at the intersection of cutting-edge research and practical enterprise applications.

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