Access Litespark

A new performance baseline for LLM pre-training

Litespark is a high-performance LLM framework that speeds up training and inference while improving GPU efficiency.

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  • Amazon Web Services
  • Nvidia
  • Arm
Benchmarks That Matter

Benchmark-proven acceleration for LLM training and inference

H100:Benchmark GPU
PyTorch
PyTorch with Litespark
0K
0K
Throughput (Tokens/sec/GPU)

Litespark reaches convergence faster on the same hardware, reducing training time, energy consumption, and iteration cycles — without requiring changes to existing models or workflows.

  • 67kTokens/sec/GPU
  • 83-86% lessEnergy use
  • 6x fasterLLM training
  • Zero-codePyTorch drop-in
  • Months to daysIteration cycles
  • 2x-6xMulti-node speedup
GPU hours per training run
10%Fewer training steps
Baseline Training
0%
With Litespark
0%
Reduced GPU hours through faster convergence

Lower cost per trained model.

Cuts training time and GPU hours, lowering infra and energy costs.

  • Less GPU time
  • Lower infra cost
Energy per training run
Baseline
337MWh256 GPUs
Litespark
133MWh0%256 GPUs
Reduced MWh and CO₂ emissions across GPU clusters

Lower energy per trained model.

Cuts MWh consumption and CO₂ emissions across 256–512 GPU clusters.

  • Lower MWh
  • Lower CO₂
Fits your existing ML pipeline
DataModel
TrainingLitesparkServing
ML Accelerator
EfficientSeamlessScalable

Performance without disruption.

Integrates seamlessly with NVIDIA and PyTorch — zero code changes.

  • PyTorch-ready
  • Native NVIDIA support
Zero-code Deployment

Run Zero-Code LLM
pre-training seamlessly on AWS

  • Bring your own data or use open source data on HuggingFace.
  • Model weights and checkpoints are stored safely in your secured environment.
  • Track metrics and performance with Weights & Biases.
Access Litespark
Your DatasetModel

Litespark doesn't just train faster — it trains smarter, using fewer resources without sacrificing model quality. The result is measurable across every dimension of your infrastructure spend.

Your team ships better models sooner — and at a fraction of the energy and cost.

  • Energy efficiency

    Up to 83%Lower energy consumption

  • Lower emissions

    Up to 83%Lower CO₂ emissions

  • GPU efficiency

    Up to 6XHigher throughput per GPU

Litespark Benefits

Built for practical LLM training

Accelerate LLM training while maximizing GPU efficiency and reducing infrastructure overhead.

Move from experiments to production-ready models sooner, with confidence.

Reduce power consumption and operational overhead for AI workloads.

Consistent performance from single-node runs to large GPU clusters.

Frequently Asked Questions

By shortening training time and improving GPU utilization, Litespark significantly lowers total GPU hours — resulting in major cost savings for large-scale training.

Accelerate LLM pre-training with Litespark.

Unlock higher throughput, lower energy use, and seamless integration with your existing stack.

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