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Builds / 4x RTX 3090 24 GB

4x RTX 3090 + EPYC 9575F + 768 GB DDR5: DeepSeek V4.1 Flash UD-Q4_K_XL, 20.6 tok/s prose, 39.3 code

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Source: reddit.com ↗📏 How measured: reported by the original source; RigBase re-checked the numbers at that source
GPU(s)
4x RTX 3090 24 GB
Amazon · eBay (used) · Newegg
VRAM / unified memory (GB)
96
CPU
AMD EPYC 9575F (64 cores)
Amazon · eBay (used) · Newegg
Motherboard
not stated
RAM
768 GB DDR5
Amazon · eBay (used) · Newegg
PSU
not stated
Other
llama.cpp built from PR #30817; Unsloth DeepSeek-V4.1-Flash-1017 UD-Q4_K_XL; experts partly in system RAM (--load-mode none --lazy-mode off), one thread per physical core, -ub 2048; 65,536 context, flash attention; DSpark Q8_0 drafter, up to 3 draft tokens; one request at a time, thinking off
Reported total cost
not stated
Power
not stated

Measured speed (generation tokens/sec)

ModelQuantEnginetok/sPrompt processing (tok/s)Details
DeepSeek V4.1 FlashUD-Q4_K_XL (GGUF)llama.cpp PR #30817, GPU + CPU offload20.6326 @ 8K-token prompt
est. TTFT @8k ≈ 25.1 s (calculated from measured prefill)		⚡ spec-decode (DSpark Q8_0 (~30% acceptance on prose))context: 8K prompt📏 Single run, prose; 25.4 after a 32K prompt (363 pp); 12.6 before RAM-load and -ub tuning
DeepSeek V4.1 FlashUD-Q4_K_XL (GGUF)llama.cpp PR #30817, GPU + CPU offload39.3not stated⚡ spec-decode (DSpark Q8_0 (~80% acceptance on code))context: code task, 65K ctx📏 Single run, code generation; 17.5 before tuning/drafter

Prompt processing = prefill speed (how fast the prompt is read) as reported by the source, with the prompt length it was measured at; blank = the source does not report it. est. TTFT @8k is calculated from the measured prefill speed (8,192 ÷ prefill tok/s), shown only when prefill was measured on a prompt of 512+ tokens. It is not a measurement and ignores load time and caching. measured TTFT is the source's own time-to-first-token. Why prefill matters for coding assistants.

r/LocalLLaMA post (20 Oct 2026). Shows that 96 GB of VRAM can run a 552B MoE when a big-RAM EPYC holds the rest of the experts. Reddit blocks automated reading, so the figures were cross-checked across the llamaperf report (https://llamaperf.com/model/deepseek-v4-1-flash) and two independent summaries on 2026-10-30. Gotchas from the post: --fit cannot size the drafter (manual --fit-target needed) and -ub 4096 pushes ~6 GB more to RAM, dropping decode to 10-12 tok/s.

Source: https://www.reddit.com/r/LocalLLaMA/comments/1xas9h8/deepseekv41flash_udq4_k_xl_on_4x_3090_epyc_12_25/

Blank fields = not stated in the source. We never estimate build data; GPU street prices above are separately sourced and dated.

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Quick answers: Can 4x RTX 3090 run DeepSeek V4.1 Flash?