BaseRTBase Compute
|
||||||
Related Products
|
||||||
About
BaseRT is a high-performance LLM inference runtime for Apple Silicon that lets developers pull models from Hugging Face, chat with them locally, or serve an OpenAI-compatible API from one CLI. Accelerated by hand-written Metal kernels, it is designed to deliver fast prefill and decode performance on M-series Macs, with published benchmarks showing up to 6.4× faster prefill than llama.cpp, 3.9× faster than MLX, and up to 1.33× faster decode. The basert CLI handles model downloading, conversion, interactive chat, serving, completion, benchmarking, inspection, and bundle signing. Its server supports chat, completions, embeddings, transcription, tool calls, continuous batching, paged KV caching, and prefix caching, while supported models can process text, vision, and audio. BaseRT uses its own .base model format with Q2–Q8 affine quantization, optional AWQ calibration, and signed bundles, and can convert GGUF, Hugging Face, and MLX checkpoints.
|
About
Welcome to Kubestone, the benchmarking operator for Kubernetes. Kubestone is a benchmarking operator that can evaluate the performance of Kubernetes installations. Supports a common set of benchmarks to measure, CPU, disk, network and application performance. Fine-grained control over Kubernetes scheduling primitives, affinity, anti-affinity, tolerations, storage classes, and node selection. New benchmarks can easily be added by implementing a new controller. Benchmarks runs are defined as custom resources and executed in the cluster using Kubernetes resources, pods, jobs, deployments, and services. Follow the quickstart guide to see how Kubestone can be deployed and how benchmarks can be run. Benchmarks can be executed via Kubestone by creating custom resources in your cluster. After the namespace is created you can use it to post a benchmark request to the cluster. The resulting benchmark executions will reside in this namespace.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
AI infrastructure engineers and developers seeking a fast, private local model inference and an OpenAI-compatible backend for applications and coding agents
|
Audience
Professionals seeking a benchmarking solution to evaluate the performance of Kubernetes installations
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationBase Compute
Founded: 2026
Australia
www.basecompute.co/getbasert
|
Company InformationKubestone
kubestone.io/en/latest/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
|
|||||
Categories |
Categories |
|||||
Integrations
Gemma 3
Gemma 4
Hugging Face
Kubernetes
Llama 3.1
Llama 3.2
Mistral AI
OpenAI
Phi-3
Qwen3
|
Integrations
Gemma 3
Gemma 4
Hugging Face
Kubernetes
Llama 3.1
Llama 3.2
Mistral AI
OpenAI
Phi-3
Qwen3
|
|||||
|
|
|