Can a NVIDIA RTX Pro 6000 Blackwell (96GB) run Llama 3.3 70B Instruct?

Yes — Llama 3.3 70B Instruct runs at Q8_0 (75.0 GB) at about 17–25 tok/s on a NVIDIA RTX Pro 6000 Blackwell (96GB).

How much memory does Llama 3.3 70B Instruct need?

Llama 3.3 70B Instruct needs about 28.5 GB at 4K context at its smallest quantization. A NVIDIA RTX Pro 6000 Blackwell (96GB) has 96.0 GB.

Yes — Llama 3.3 70B Instruct runs on a NVIDIA RTX Pro 6000 Blackwell (96GB) at Q8_0

Yes — it runs great.

Runs great

Best fit: Llama 3.3 70B Instruct at Q8_0 · 75.0 GB weights · 17–25 tok/s on a NVIDIA RTX Pro 6000 Blackwell (96GB).

Arena Text Overall · style-controlled

1,318Q8_0 untested

llama-3.3-70b-instruct · published configuration reference · Q8_0 not tested

Arena Text Overall (style-controlled), exact published entry llama-3.3-70b-instruct, 2026-10-08: reference rating 1,318. Published confidence bounds 1,314.5–1,321.5. 54,504 votes. Published llama-3.3-70b-instruct configuration reference. Reasoning mode is not disclosed by the Arena dataset. Tested precision, runtime and sampling settings are not disclosed in this dataset. Selected Q8_0 has not been measured by this Arena entry. No quantization quality adjustment is applied.

Snapshot published 2026-10-08 · snapshot imported 2026-10-11 UTC · validated last-good data · manual refresh

Arena leaderboard dataset · Arena / lmarena-ai, Arena Leaderboard Dataset (CC BY 4.0). Selected Text Overall style-controlled rows; field names adapted, ratings unchanged. · dataset CC BY 4.0 · revision e16f90232986

Total memory at 4K context: 77.1 GB; Weights + KV cache + runtime overhead
Estimated generation: 17–25 tok/s
Estimated first token: ~6.9s

Every quantization on this machine

On small screens, each quant lists every metric below its name. On wider screens, scroll sideways for total memory, speed and fit. Keyboard: focus the table, then use the arrow keys. Quant names stay visible.

Llama 3.3 70B Instruct quantizations on NVIDIA RTX Pro 6000 Blackwell (96GB), estimated at 4K context. Weights and total memory are shown separately.
Quant	Weights	Total memory	Speed	Fit
Q2_K	26.4 GB	28.5 GB	42–63 tok/s	Runs great
Q3_K_M	34.3 GB	36.4 GB	34–51 tok/s	Runs great
Q4_K_M	42.5 GB	44.7 GB	28–42 tok/s	Runs great
Q5_K_M	50.0 GB	52.1 GB	24–36 tok/s	Runs great
Q6_K	57.9 GB	60.0 GB	21–32 tok/s	Runs great
Q8_0	75.0 GB	77.1 GB	17–25 tok/s	Runs great
FP16	141.1 GB	143.3 GB	— not resident	Won't fit

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