Local AI Advisor

Can MacBook Pro M4 Pro 24 GB run LFM2.5 24B-A2B?

24 GB unified · 273 GB/s memory bandwidth · LFM2.5 24B-A2B has 24B parameters (2B active per token).

Short answer

Yes, comfortable for chat; borderline for coding questions.

Best quantization for chat: Q4_K_M (14 GB of weights) on LM Studio. Generation: 100–140 tok/s, leaving about 1.8 GB free for your other apps.

How it rates for each workload

Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.

WorkloadVerdictQuantGenerationFirst replyContext
Chatwith Open WebUIComfortableQ4_K_M100–140 tok/sunder 1 s8KDetails
Coding questionswith ContinueBorderlineQ4_K_M95–130 tok/s≈4 s16KDetails
Coding in a repositorywith AiderBorderlineQ4_K_M80–110 tok/s≈10 s32KDetails
Agentic codingwith OpenCodeBorderlineQ4_K_M75–100 tok/s≈15 s32KDetails
Long documents (64K)with Open WebUIBorderlineQ4_K_M55–75 tok/s≈40 s64KDetails

Speeds are estimates calibrated against measured benchmarks on similar hardware. “First reply” is the time to read the workload’s opening prompt. How we calculate

Different tool, context size or workload?

These pages use typical settings. The full check models your exact setup.