Can the RTX 5070 run Llama 3.1 8B?

Yes. Llama 3.1 8B fits the RTX 5070's 12 GB at Q4_K_M (about 7.3 GB needed), running at an estimated 70 tok/s. There's room for up to Q8_0 if you want higher quality.

VRAM
12 GB
Needs at Q4
7.3 GB
Headroom
4.7 GB
Speed (Q4_K_M)
~70 tok/s

Every quantization

Llama 3.1 8B (8B) on 12 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M5.5 GB7.3 GBFits~70 tok/s
Q5_K_M7 GB8.8 GBFits~55 tok/s
Q8_010 GB11.8 GBTight~39 tok/s
FP1616 GB17.8 GBToo big -

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 5070's 672 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

ollama run llama3.1:8b
llama-server -hf bartowski/Meta-Llama-3.1-8B-Instruct-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Llama 3.1 8B details →

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Same model, other hardware - and other models on this card

Llama 3.1 8B on other hardware

Also runs on the RTX 5070

Frequently asked

Quick answers

Can the NVIDIA RTX 5070 run Llama 3.1 8B?

Yes. Llama 3.1 8B fits the RTX 5070's 12 GB at Q4_K_M (about 7.3 GB needed), running at an estimated 70 tok/s. There's room for up to Q8_0 if you want higher quality.

How much VRAM does Llama 3.1 8B need?

About 5.5 GB of weights at Q4_K_M, 10 GB at Q8_0 and 16 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Llama 3.1 8B on the RTX 5070?

Roughly 70 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 5070's 672 GB/s memory bandwidth.