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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/Meta Llama 3.1 8B Instruct/on NVIDIA H800 80GB

Can it run?

Can NVIDIA H800 80GB run Meta Llama 3.1 8B Instruct?

CUsable

Runs well

Using Q4_K_M in Ollama

Capabilities:

Fit status

Runs well

Decode

498.0 tok/s

TTFT

389 ms

Safe context

83K

Memory

15.3 GB / 80.0 GB

Memory breakdown

Weights4.9 GB
KV Cache1.3 GB
Runtime1.2 GB
Headroom8.0 GB

Performance by workload

WorkloadGradeFitDecodeTTFTContext
Agentic CodingCRuns well498.0 tok/s566 ms154K
ChatCRuns well498.0 tok/s350 ms43K
CodingCRuns well498.0 tok/s389 ms83K
RAGCRuns well498.0 tok/s707 ms154K
ReasoningCRuns well498.0 tok/s459 ms83K

Quantization options

How Meta Llama 3.1 8B Instruct (8B params) fits at each quantization level on NVIDIA H800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
3.1 GB
LowD30
Q3_K_S
3
3.9 GB
LowD31
NVFP4
4
4.5 GB
MediumD31
Q4_K_M
4
4.9 GB
MediumD31
Q5_K_M
5
5.8 GB
HighD31
Q6_K
6
6.6 GB
HighD31
Q8_0
8
8.6 GB
Very HighD32
F16Best for your GPU
16
16.4 GB
MaximumD34

Get started

Upgrade options

Hardware that runs Meta Llama 3.1 8B Instruct well

AppleMac Studio M2 Ultra 128GBBudget pick
C95.1 tok/s decode

~$3,999 MSRP

AppleMac Studio M1 Ultra 128GBBest value
C90.2 tok/s decode

~$3,999 MSRP

See all results for NVIDIA H800 80GBSee all hardware for Meta Llama 3.1 8B Instruct