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About

LMCache is an open source Knowledge Delivery Network (KDN) designed as a caching layer for large language model serving that accelerates inference by reusing KV (key-value) caches across repeated or overlapping computations. It enables fast prompt caching, allowing LLMs to “prefill” recurring text only once and then reuse those stored KV caches, even in non-prefix positions, across multiple serving instances. This approach reduces time to first token, saves GPU cycles, and increases throughput in scenarios such as multi-round question answering or retrieval augmented generation. LMCache supports KV cache offloading (moving cache from GPU to CPU or disk), cache sharing across instances, and disaggregated prefill, which separates the prefill and decoding phases for resource efficiency. It is compatible with inference engines like vLLM and TGI and supports compressed storage, blending techniques to merge caches, and multiple backend storage options.

About

oMLX is a macOS-native MLX server designed to make local AI faster and more practical on Apple Silicon. Built for the way coding agents actually work, it uses paged SSD KV caching to persist cache blocks to disk, allowing previously seen prefixes to be restored across requests and server restarts instead of being recomputed from scratch. This can reduce time to first token on long contexts from 30–90 seconds to under five seconds after the first turn. Continuous batching handles concurrent requests through mlx-lm’s BatchGenerator, improving generation throughput without forcing requests to wait behind a single job. oMLX can serve LLMs, vision-language models, embedding models, and rerankers simultaneously, using LRU eviction when memory runs low. It supports any MLX-format model from Hugging Face, including Qwen, LLaMA, Mistral, Gemma, DeepSeek, MiniMax, and GLM, and can reuse models already stored in the standard Hugging Face cache, LM Studio folders, or custom directories.

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 engineers and infrastructure teams looking for a tool to lower latency, reduce compute cost, and scale throughput

Audience

Developers and AI power users needing to run fast local LLM inference and agentic coding workflows on Apple Silicon

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

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

LMCache
United States
lmcache.ai/

Company Information

oMLX
United States
omlx.ai/

Alternatives

Alternatives

Photon

Photon

Moondream
BaseRT

BaseRT

Base Compute
Run BiOS

Run BiOS

UltraSafe AI Inc.
BaseRT

BaseRT

Base Compute
Macyou

Macyou

Macyou LLC
DeepSeek-V2

DeepSeek-V2

DeepSeek

Categories

Categories

Integrations

Anthropic
Claude Code
Cursor
DeepSeek
GLM-4.1V
Gemma
Gemma
GitHub
Hugging Face
JSON
LM Studio
Llama
MiniMax
Mistral AI
Model Context Protocol (MCP)
OpenAI
OpenClaw
Python
Qwen

Integrations

Anthropic
Claude Code
Cursor
DeepSeek
GLM-4.1V
Gemma
Gemma
GitHub
Hugging Face
JSON
LM Studio
Llama
MiniMax
Mistral AI
Model Context Protocol (MCP)
OpenAI
OpenClaw
Python
Qwen
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