Can I Run IBM Granite 4.1 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM)?

Superseded model. IBM Granite 4.1 has been superseded by IBM Granite 4.2. This page is kept for reference; the newer family is a better starting point. View IBM Granite 4.2 →

Written by Jakub Rusinowski · Last updated April 29, 2026

Yes

Yes — Granite 4.1 30B at Q6_K needs about 27.2 GB of the 32 GB usable on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM) (~4.8 GB spare), at ~47.1 tok/s (estimated), with room for about 16,384 tokens of context.

Confidence: medium · Recommended quantization: Q6_K · Estimated speed: ~47.1 tok/s

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RTX 5090 Desktop (32 GB VRAM, 64 GB RAM) — what it gives a model

Usable memory for models	32 GB
Memory bandwidth	1792 GB/s
Form factor	Desktop
Operating system	Windows or Linux
Memory upgradeable	Yes

IBM Granite 4.1 on RTX 5090 Desktop (32 GB VRAM, 64 GB RAM): memory by quantization

Quant	Memory needed	Fits 32 GB?	Max context	Est. speed	Download
F16	62.6 GB	✗ No	—	—	60 GB
Q8_0	34.5 GB	✗ No	—	—	31.9 GB
Q6_K	27.2 GB	✓ Yes	16K	~47.1 tok/s	24.6 GB
Q5_K_M	23.8 GB	✓ Yes	32K	~53.4 tok/s	21.3 GB
Q4_K_M	20.7 GB	✓ Yes	32K	~61 tok/s	18.1 GB
Q3_K_M	15.4 GB	✓ Yes	64K	~80.5 tok/s	12.8 GB
Q2_K	12.4 GB	✓ Yes	64K	~97.6 tok/s	9.9 GB

Which IBM Granite 4.1 sizes fit

Variant	Needs at Q4_K_M	Fits?	Est. speed
Granite 4.1 30B	20.7 GB	✓ Fits	~61 tok/s
Granite 4.1 8B	6.8 GB	✓ Fits	~159.6 tok/s
Granite 4.1 3B	3.5 GB	✓ Fits	~256 tok/s

What to watch out for

This model does not publish its full attention configuration, so the KV-cache share of these figures is inferred from its parameter count rather than computed exactly.

RTX 5090 desktop limitations

575 W board power — budget for a 1000 W+ PSU and the heat it puts into the room.
Models larger than 32 GB must offload to system RAM, which costs roughly an order of magnitude in speed.

Recommended setup

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

How these numbers are calculated

Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
32 GB of VRAM on the NVIDIA GeForce RTX 5090 at 1792 GB/s.
64 GB of system RAM available for CPU offload when a model exceeds VRAM.
Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
KV cache is inferred from the parameter count because this model does not publish its full attention configuration.

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