What is TurboQuant and does it run on MacBook?

TurboQuant compresses LLM KV cache for long contexts; yes, via MLX sidecar on Apple Silicon—perfect for MacBooks with limited RAM.

How to install TurboQuant local stack with Ollama?

Run `bash install.sh` from the repo—it sets up Ollama, MLX sidecar, routing proxy, and auto-starts everything.

Can TurboQuant handle 70B models on 24GB MacBook?

Yes for long-context inference after weight quantization; KV cache compression prevents OOM on big prompts.

🚀 New Releases

TurboQuant on MacBook: One-Command Local LLM Stack

Forget cramming 70B models onto your MacBook. TurboQuant targets the real killer: exploding KV caches during inference. Here's the dead-simple stack to make it work.

theAIcatchup Apr 09, 2026 4 min read

Diagram of TurboQuant local stack: Ollama, MLX sidecar, and routing proxy on MacBook

⚡ Key Takeaways

TurboQuant compresses KV cache, not model weights—key for long-context local LLMs. 𝕏
One-command installer sets up Ollama + MLX sidecar + routing proxy on Apple Silicon. 𝕏
Smart proxy routes short prompts to Ollama, long ones to TurboQuant—zero client changes. 𝕏

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#KV cache #TurboQuant #apple silicon #local LLMs #mlx #ollama

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Originally reported by dev.to

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