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Builds / RTX Pro 6000 Blackwell Workstation (96 GB) + RTX 3090 Ti (EV

EPYC 7532 workstation (RTX Pro 6000 + RTX 3090 Ti, 300 W caps): Qwen3.8-Flash-Next, llama.cpp vs Strata engine

Source: research.strata2signal.com ↗📏 How measured: reported by the original source; RigBase re-checked the numbers at that source
GPU(s)
RTX Pro 6000 Blackwell Workstation (96 GB) + RTX 3090 Ti (EVGA FTW3 Ultra, 24 GB); each test used one card
Amazon · eBay (used) · Newegg
VRAM / unified memory (GB)
120
CPU
AMD EPYC 7532 (32 cores, Zen 2)
Amazon · eBay (used) · Newegg
Motherboard
not stated
RAM
128 GB DDR4-3200, 8 channels
Amazon · eBay (used) · Newegg
PSU
not stated
Other
Both cards power-capped to 300 W for the bench; one request at a time, 4,038-token prompt, 256 tokens out, greedy
Reported total cost
not stated
Power
Board power (not wall), 4K prompt: RTX Pro 6000 297.8 W (llama.cpp) / 290.6 W (Strata); RTX 3090 Ti 168.5 W (llama.cpp) / 281.1 W (Strata)

Measured speed (generation tokens/sec)

ModelQuantEnginetok/sDetails
Qwen3.8 Flash-NextIQ3_S, all experts on the RTX Pro 6000, no draft headllama.cpp (3cf03257), RTX Pro 6000102.889⚡ spec-decode (speculative)
Qwen3.8 Flash-NextIQ3_S + model draft head, all experts on the RTX Pro 6000Strata engine 0.1.39, RTX Pro 6000205.263⚡ spec-decode (speculative)
Qwen3.8 Flash-NextIQ3_S, 32K prompt, all on the RTX Pro 6000llama.cpp (3cf03257), RTX Pro 600076.337
Qwen3.8 Flash-NextIQ3_S, experts of 34/48 layers in system RAM, no draft headllama.cpp (b11514), RTX 3090 Ti22.657⚡ spec-decode (speculative)
Qwen3.8 Flash-NextIQ3_S + draft head, 8,144 of 24,576 experts on cardStrata engine 0.1.39, RTX 3090 Ti98.291⚡ spec-decode (speculative)

strata→signal research, published 12 Oct 2026; runs 6-9 Oct 2026. Median of three runs. llama.cpp ran near defaults (512-token micro-batch, 8 threads); on the 3090 Ti its speed was limited by those 8 CPU threads, not the card. Strata is a third-party engine built on llama.cpp (github.com/Niko1221/Strata). The source also benches an RTX 5090 laptop GPU (24.4 tok/s llama.cpp, 85.6 Strata).

Source: https://research.strata2signal.com/flash-next-on-three-cards/

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

Rent before you buy: try this model on a cloud GPU for a few dollars first: Runpod (referral link; sign up with Google to get the new-user bonus)