Can Desktop PC · Radeon RX 7900 XT · 32 GB RAM run LFM2.5 24B-A2B?

20 GB VRAM + 32 GB RAM · 800 GB/s memory bandwidth · LFM2.5 24B-A2B has 24B parameters (2B active per token).

Short answer

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

Best quantization for chat: Q4_K_M (14 GB of weights) on Lemonade. Generation: 240–410 tok/s, leaving about 4.4 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	Excellent	Q4_K_M	240–410 tok/s	under 1 s	8K	Details
Coding questionswith Continue	Excellent	Q4_K_M	230–390 tok/s	≈1 s	16K	Details
Coding in a repositorywith Aider	Acceptable	Q4_K_M	200–330 tok/s	≈3 s	32K	Details
Agentic codingwith OpenCode	Acceptable	Q4_K_M	190–310 tok/s	≈4 s	32K	Details
Long documents (64K)with Open WebUI	Excellent	Q4_K_M	140–230 tok/s	≈15 s	64K	Details

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

Other models for Desktop PC · Radeon RX 7900 XT · 32 GB RAM

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Different tool, context size or workload?

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

Check my exact setup