Can the RTX A1000 run Granite 4.2 8B?

Yes. Granite 4.2 8B fits the RTX A1000's 8 GB at Q4_K_M (about 6.8 GB needed), running at an estimated 22 tok/s. There's room for up to Q5_K_M if you want higher quality.

VRAM
8 GB
Needs at Q4
6.8 GB
Headroom
1.2 GB
Speed (Q4_K_M)
~22 tok/s

Every quantization

Granite 4.2 8B (8.8B) on 8 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M5 GB6.8 GBFits~22 tok/s
Q5_K_M6 GB7.8 GBTight~18 tok/s
Q8_09 GB10.8 GBToo big -
FP1618 GB19.8 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 A1000's 192 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

llama-server -hf ibm-granite/granite-4.2-8b-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Granite 4.2 8B details →

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

Granite 4.2 8B on other hardware

Also runs on the RTX A1000

Frequently asked

Quick answers

Can the RTX A1000 run Granite 4.2 8B?

Yes. Granite 4.2 8B fits the RTX A1000's 8 GB at Q4_K_M (about 6.8 GB needed), running at an estimated 22 tok/s. There's room for up to Q5_K_M if you want higher quality.

How much VRAM does Granite 4.2 8B need?

About 5 GB of weights at Q4_K_M, 9 GB at Q8_0 and 18 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Granite 4.2 8B on the RTX A1000?

Roughly 22 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX A1000's 192 GB/s memory bandwidth.