Can MacBook Air M3 24 GB run LFM2.5 24B-A2B?

24 GB unified · 100 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: 40–50 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.

Workload	Verdict	Quant	Generation	First reply	Context
Chatwith Open WebUI	Comfortable	Q4_K_M	40–50 tok/s	≈2 s	8K	Details
Coding questionswith Continue	Borderline	Q4_K_M	35–50 tok/s	≈8 s	16K	Details
Coding in a repositorywith Aider	Borderline	Q4_K_M	30–45 tok/s	≈25 s	32K	Details
Agentic codingwith OpenCode	Borderline	Q4_K_M	30–40 tok/s	≈35 s	32K	Details
Long documents (64K)with Open WebUI	Borderline	Q4_K_M	20–30 tok/s	≈2 min	64K	Details

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

Other models for MacBook Air M3 24 GB

The best-rated models for chat on this machine.

Everything MacBook Air M3 24 GB can run

Cheapest machines for LFM2.5 24B-A2B

Hardware rated comfortable or better for chat, lowest price first.

Same chip, other memory: 8 GB, 16 GB

Different tool, context size or workload?

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

Check my exact setup