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oMLX vs BaseRT: Which is Better in 2026?

Choosing between oMLX and BaseRT comes down to understanding what each tool does best. This comparison breaks down the key differences so you can make an informed decision based on your specific needs, not marketing claims.

Bottom line: BaseRT wins this matchup. Our overall AI Assistants pick is ChatGPT. Our free AI Assistants pick is Fathom. Pick oMLX if you need a fully free option.

··Methodology
Editor reviewed0 verified reviews comparedPricing checked Aug 2026

Short on time? Here's the quick answer

We've tested both tools. Here's who should pick what:

oMLX

Fast local LLM inference on Apple Silicon with persistent SSD cache

Best for you if:

  • Paged SSD KV caching eliminates recomputation by persisting cache blocks to disk, enabling sub-5-second TTFT on long contexts for coding agents.
  • Continuous batching delivers up to 4x generation speedup at high concurrency, outperforming in-memory-only solutions.

BaseRT

Fast open-source LLM inference for Apple Silicon, on-device

Best for you if:

  • Optimized runtime for Apple Silicon delivering significant speedups compared to alternatives.
  • Enables local model serving for coding agents, ensuring data privacy by keeping everything on the user's machine.
At a Glance
oMLXoMLX
BaseRTBaseRT
Starts at
FreeFree tier available
FreeFree tier available
Best For
Developer ToolsDeveloper Tools
Rating
--
Free plan
Yes Yes

Choose oMLX or BaseRT?

oMLX

Choose oMLX if

Fast local LLM inference on Apple Silicon with persistent SSD cache

  • Dramatically reduces TTFT on long contexts for coding agents by persisting KV cache to SSD
  • Significant throughput improvements with continuous batching at high concurrency
  • Seamless integration with popular coding tools via OpenAI/Anthropic compatible APIs
BaseRT

Choose BaseRT if

Fast open-source LLM inference for Apple Silicon, on-device

  • Fast inference speeds, especially on prefill and decode phases.
  • Keeps data fully local, enhancing privacy and security for sensitive work.
  • Free and open-source, with active community support.
FeatureoMLXBaseRT
Pricing ModelFreeFree
User RatingNo ratings yetNo ratings yet
Categories
Developer ToolsAI Assistants
Developer ToolsAI Assistants

In-Depth Analysis

oMLXoMLX

Fast local LLM inference on Apple Silicon with persistent SSD cache

Starts at Free

Strengths

  • +Dramatically reduces TTFT on long contexts for coding agents by persisting KV cache to SSD
  • +Significant throughput improvements with continuous batching at high concurrency
  • +Seamless integration with popular coding tools via OpenAI/Anthropic compatible APIs

Weaknesses

  • -Requires macOS 15+ and Apple Silicon, limiting compatibility to recent Mac hardware
  • -Large models demand substantial RAM (64GB+ recommended), making it less accessible on lower-end Macs

Key features

Paged SSD KV caching with two-tier RAM/SSD architecture and LRU eviction policyContinuous batching via mlx-lm's BatchGenerator for concurrent request handlingNative macOS menu bar app with web dashboard for model management and real-time metricsMulti-model serving supporting LLM, VLM, embedding, and reranker models simultaneouslyOpenAI and Anthropic drop-in API endpoints with one-click config generator for tools like Claude Code and CursorTool calling support for JSON, Qwen, Gemma, GLM, and MiniMax formats with MCP integration

BaseRTBaseRT

Fast open-source LLM inference for Apple Silicon, on-device

Starts at Free
Great value

BaseRT is completely free at $0/month, making it an exceptionally generous offering for Apple Silicon users.

Watch out

May lack features of paid runtimes (e.g., quantization options)

Strengths

  • +Fast inference speeds, especially on prefill and decode phases.
  • +Keeps data fully local, enhancing privacy and security for sensitive work.
  • +Free and open-source, with active community support.

Weaknesses

  • -Only compatible with Apple Silicon (M-series) hardware.
  • -Model support may not cover all open-source models available in other runtimes.

Key features

Supports a wide range of models: Qwen, Llama, Gemma, Mistral, Phi, Nomic BERT, and more.Serves models via a simple `basert serve` command for integration with coding agents.Installs with a single curl command for quick setup.Delivers significantly faster prefill tokens per second compared to MLX and llama.cpp.Community-driven development with documentation, GitHub repository, and Discord chat.

Pricing: oMLX vs BaseRT

PlanoMLXBaseRT
Tier 1N/A
Free
BaseRT

Pricing verified from each vendor's public pricing page. Compare in detail on oMLX pricing and BaseRT pricing.

Who Should Use What?

On a budget?

Both are free. Compare plans on their websites.

Go with: oMLX

Want the highest-rated option?

Neither has ratings yet.

Too early to call on ratings — compare on features and pricing.

Value user reviews?

Neither has ratings yet.

Too early to call — neither has ratings yet.

3 Questions to Help You Decide

1

What's your budget?

Both are free. Pricing won't help you decide here.

2

What's your use case?

Both are developer tools tools. Compare their specific features to decide.

3

How important are ratings?

Neither has ratings yet.

Key Takeaways

BaseRT

  • Completely free
  • Our pick for this comparison

oMLX

  • Choose if you want fast local LLM inference on Apple Silicon with persistent SSD cache

The Bottom Line

BaseRT wins this matchup. Our overall AI Assistants pick is ChatGPT. Our free AI Assistants pick is Fathom.

Frequently Asked Questions

Is oMLX or BaseRT better?

BaseRT is rated in our evaluation. Both are free.

What are oMLX and BaseRT used for?

oMLX: Fast local LLM inference on Apple Silicon with persistent SSD cache. BaseRT: Fast open-source LLM inference for Apple Silicon, on-device.

What does oMLX cost vs BaseRT?

oMLX is completely free. BaseRT is completely free. Visit their websites for detailed pricing.

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