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// 74d agoTUTORIAL
DeepSeek-R1 VRAM math: 32B hits 24GB limit
A LocalLLaMA community post breaks down actual VRAM requirements for running DeepSeek-R1 distilled models locally, accounting for KV cache — a factor most estimates ignore. The 32B model at Q4_K_M consumes ~20.5GB on a single 24GB card, leaving almost no headroom beyond 16k context.
// ANALYSIS
Practical VRAM accounting for local LLMs is genuinely underserved, but this post is a low-signal Reddit thread with score 0 and no accessible tool link.
- –Most published VRAM estimates omit KV cache scaling, which grows linearly with context — a critical blind spot for anyone pushing context windows
- –32B Q4_K_M at ~20.5GB on a single 4090 leaves almost no headroom; the 70B at ~42.8GB on dual 48GB cards is similarly constrained
- –The author built a calculator tool but withheld the link to avoid self-promotion rules, making this post largely informational without a deliverable
- –Dual-GPU setups for the 70B face bandwidth bottlenecks that limit tokens-per-second regardless of VRAM headroom
// TAGS
deepseek-r1llminferenceedge-aiopen-source
DISCOVERED
74d ago
2026-03-14
PUBLISHED
74d ago
2026-03-14
RELEVANCE
5/ 10
AUTHOR
abarth23