Local AI Advisor

Can MacBook Pro M5 Max 128 GB run LFM2.5 24B-A2B?

128 GB unified · 614 GB/s memory bandwidth · LFM2.5 24B-A2B has 24B parameters (2B active per token).

Short answer

Yes, excellent for chat and comfortable or better for every workload we test.

Best quantization for chat: Q4_K_M (14 GB of weights) on LM Studio. Generation: 180–300 tok/s, leaving about 103 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 WebUIExcellentQ4_K_M180–300 tok/sunder 1 s8KDetails
Coding questionswith ContinueExcellentQ8_0100–170 tok/sunder 1 s16KDetails
Coding in a repositorywith AiderComfortableQ8_090–150 tok/s≈2 s32KDetails
Agentic codingwith OpenCodeComfortableQ8_090–150 tok/s≈2 s32KDetails
Long documents (64K)with Open WebUIExcellentQ8_070–120 tok/s≈6 s64KDetails

Speeds are bandwidth-based estimates; no direct benchmark exists for this pair. “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.