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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Llama 4 Maverick 17B 128E/on NVIDIA A800 80GB

Can it run?

Can NVIDIA A800 80GB run Llama 4 Maverick 17B 128E?

FWon't run

Too heavy

Using Q4_K_M in vLLM

Capabilities:

Fit status

Too heavy

Decode

18.5 tok/s

TTFT

10454 ms

Safe context

5K

Memory

257.1 GB / 80.0 GB

Memory breakdown

Weights244.0 GB
KV Cache2.7 GB
Runtime2.4 GB
Headroom8.0 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingFToo heavy18.5 tok/s15205 ms10K
ChatFToo heavy18.5 tok/s5702 ms4K
CodingFToo heavy18.5 tok/s10454 ms5K
RAGFToo heavy18.5 tok/s19007 ms10K
ReasoningFToo heavy18.5 tok/s12354 ms5K

Quantization options

How Llama 4 Maverick 17B 128E (400B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
156.0 GB
LowF0
Q3_K_S
3
196.0 GB
LowF0
NVFP4
4
224.0 GB
MediumF0
Q4_K_M
4
244.0 GB
MediumF0
Q5_K_M
5
288.0 GB
HighF0
Q6_K
6
328.0 GB
HighF0
Q8_0
8
428.0 GB
Very HighF0
F16
16
820.0 GB
MaximumF0

Upgrade options

Hardware that runs Llama 4 Maverick 17B 128E well

AMDAMD Instinct MI350X 288GBBest value
C71.7 tok/s decode

~$8,000 MSRP

AMDAMD Instinct MI325X 256GBBiggest leap
C50.6 tok/s decode

 

See all results for NVIDIA A800 80GBSee all hardware for Llama 4 Maverick 17B 128E