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vmlx vs semble
vmlx logo
vmlx
★ 557
vs
semble logo
semble
★ 4.6k

vmlx vs semble

vmlx: vMLX is a local AI inference engine for Apple Silicon Macs that runs LLMs, VLMs, and image generation models. It provides OpenAI and Anthropic compatible APIs with advanced features like continuous batching, prefix caching, KV cache quantization, speculative decoding, and tool calling. No cloud or API keys required, ensuring data privacy.; semble: Semble is a high-performance code search library designed for AI agents, providing instant access to precise code snippets. It offers significantly faster indexing and querying compared to transformer models, achieving 99% of their retrieval quality while running entirely on CPU without external dependencies.

01

TL;DR

vmlx logoChoose vmlx if…

Run local AI assistants with chatbot and agentic coding capabilities

semble logoChoose semble if…

Enhancing AI agents (e.g., Claude Code, Cursor, Codex) with fast and accurate code search capabilities

02

Side-by-Side Comparison

Field
vmlx logovmlx
semble logosemble
Category
Vision / Multimodal
RAG / Knowledge Base
Stars
★ 557
★ 4.6k
License
Apache-2.0
MIT
Updated
1w ago
2d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
anthropic-api, kvcache-compression, kvcache-optimization
agents, code-search, embeddings
03

Features

vmlx logovmlx
01Continuous Batching for efficient concurrent request handling
02Prefix Cache with memory-aware and paged KV cache
03KV Cache Quantization to q4/q8 for memory savings
04Speculative Decoding for 20-90% speedup
05Tool Calling with auto-detected parsers for major model families
semble logosemble
01Fast performance on CPU (indexes in ~250ms, queries in ~1.5ms)
02High accuracy (NDCG@10 of 0.854), comparable to transformer models
03Supports indexing local paths and remote Git repositories
04Functions as an MCP server for various AI agents
05Zero setup, no API keys, GPU, or external services required
04

Use Cases

vmlx logovmlx
↳Run local AI assistants with chatbot and agentic coding capabilities
↳Generate and edit images locally using Flux models
↳Deploy a fully local API server compatible with OpenAI and Anthropic SDKs
semble logosemble
↳Enhancing AI agents (e.g., Claude Code, Cursor, Codex) with fast and accurate code search capabilities
↳Searching local or remote codebases for specific code snippets based on natural language or code queries
↳Finding semantically similar code sections related to a given file path and line number
05

Best For

vmlx logovmlx
LLM InfraDev Tooling
semble logosemble
Code AssistantRAG / Knowledge Base
FAQ

FAQ

What is the difference between vmlx and semble?
Both vmlx and semble are in the Vision / Multimodal category. vmlx has 557 stars, while semble has 4.6k stars.
Which is better, vmlx or semble?
The best choice depends on your use case. Choose vmlx if Run local AI assistants with chatbot and agentic coding capabilities, and semble if Enhancing AI agents (e.g., Claude Code, Cursor, Codex) with fast and accurate code search capabilities.
Is vmlx free or open source?
Yes, vmlx is open source on GitHub (Apache-2.0).
Is semble free or open source?
Yes, semble is open source on GitHub (MIT).
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Related

Alternatives to vmlx →Alternatives to semble →vmlx details →semble details →
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