Best-in-Class LLM Batch Inference
Run LLM batch inference jobs cheaper than competitors. See why Anyscale is the choice for LLM batch inference.
Optimized Performance
Throughput-Optimized Workloads
We know how important throughput is for your large scale, offline batch inference jobs—and we’ve optimized Anyscale accordingly.
Advanced vLLM Optimizations
The Anyscale inference team consists of many of the leading committers to the vLLM project. Our experts can help tune engine performance to reduce costs.
Long-Context Use Cases
Our custom optimizations for prefix caching enable significant performance improvements on long-context use cases compared to vLLM.
Reduce Costs By Using GPUs and CPUs
Anyscale makes it easy to leverage heterogeneous compute. Use CPUs and GPUs in the same pipeline to increase utilization, fully saturate GPUs, and decrease costs.
Optimized LLM Batch Inference at Any Scale
Automated Throughput Tuner
Support for Different GPUs/Accelerators
Support for Large Model Parallelism
Spot Instance Support
Aceclerated Long Context Inference
Custom Optimized Kernels
Multi-Modal Support
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|---|---|---|---|---|
Automated Throughput Tuner | N/A | - | - | |
Support for Different GPUs/Accelerators | N/A | - | | |
Support for Large Model Parallelism | | - | | |
Spot Instance Support | N/A | | | |
Aceclerated Long Context Inference | - | - | - | |
Custom Optimized Kernels | N/A | - | - | |
Multi-Modal Support | - | | | |
“We have no ceiling on scale, and an incredible opportunity to bring AI features and value to our 170 million users.”
Greg Roodt
ML Lead, Canva
Out-of-the-Box Templates & App Accelerators
Jumpstart your development process with custom-made templates, only available on Anyscale.
Batch Inference with LLMs
Run LLM offline inference on large scale input data with Ray Data
End-to-End LLM Workflows
Execute end-to-end LLM workflows to develop and productionize LLMs at scale
FAQs
At Anyscale, we know how important it is to stay competitive within the AI space. That’s why we’re constantly updating and iterating on our product to make sure it’s the fastest, cheapest, and most performant option for AI/ML workloads. When it comes to offline batch inference, we’ve invested in a number of advanced capabilities to enhance your inference process, including:
- Cascade inference
- FP8 support
- Batch size tuning
- Pipeline parallelism
- Continuous batching
- And more!
Offline Batch Inference at Scale
See why Anyscale is the best option for offline batch inference.