Granite 4.2 30B on NVIDIA GeForce RTX 4080 SUPER

Can the NVIDIA GeForce RTX 4080 SUPER run Granite 4.2 30B?

77 pts

Yes, with little memory to spare

Tight fit. At Q2_K it needs about 15.3 GB of 16.0 GB usable, with an estimated speed of 50.7 tok/s.

Best quant: Q2_K
Generation speed: 50.7 tok/s
Prompt processing: 1,284 tok/s
First token (1K prompt): 0.8 s
Largest safe context: 10K

Download Granite 4.2 30B

Recommended for the NVIDIA GeForce RTX 4080 SUPER: Q2_K. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run granite4.2:30b-q2_K

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q2_K file (opens in a new tab)

huggingface.co/ibm-granite/granite-4.2-30b-GGUF (opens in a new tab)

ollama run hf.co/ibm-granite/granite-4.2-30b-GGUF:Q2_K

Original weights · Hugging Face

Full-precision files from IBM, for fine-tuning, vLLM, Transformers.

huggingface.co/ibm-granite/granite-4.2-30b (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from IBM. The weights themselves download from Hugging Face.

github.com/ibm-granite/granite-4.2-language-models (opens in a new tab)

git clone https://github.com/ibm-granite/granite-4.2-language-models

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	23.9 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Total	77.9 / 100	77 ptsGreat (A) · 77 of 100 points: Model quality 23.9/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the NVIDIA GeForce RTX 4080 SUPER

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	15.3 GB	16.0 GB	50.7 tok/s	Tight fit	77 ptsGreat (A) · 77 of 100 points: Model quality 23.9/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q3_K_M`	17.9 GB	16.0 GB	17.2 tok/s	Runs with offload	63 ptsGood (B) · 63 of 100 points: Model quality 28.7/45, Memory fit 10.0/25, Speed 9.8/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q4_K_M`	21.4 GB	16.0 GB	7.6 tok/s	Heavy offload	58 ptsGood (B) · 58 of 100 points: Model quality 32.5/45, Memory fit 4.0/25, Speed 6.6/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q5_K_M`	24.3 GB	16.0 GB	5.1 tok/s	Heavy offload	57 ptsUsable (C) · 57 of 100 points: Model quality 33.2/45, Memory fit 4.0/25, Speed 5.3/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q6_K`	27.6 GB	16.0 GB	3.7 tok/s	Heavy offload	57 ptsUsable (C) · 57 of 100 points: Model quality 33.9/45, Memory fit 4.0/25, Speed 4.5/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q8_0`	34.6 GB	16.0 GB	2.2 tok/s	Heavy offload	56 ptsUsable (C) · 56 of 100 points: Model quality 34.2/45, Memory fit 4.0/25, Speed 3.5/15, Memory use 15.0/15	GGUF (opens in a new tab)
`F16`	62.1 GB	16.0 GB	—	Won't run	10 ptsWon't run (F) · 10 of 100 points: Model quality 10.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · part 1 of 2 (opens in a new tab) Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

88 ptsExcellent (S) · 88 of 100 points: Model quality 33.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q5_K_M · 62.1 tok/s
86 ptsExcellent (S) · 86 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q4_K_M · 42.3 tok/s
86 ptsExcellent (S) · 86 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 14.9/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q4_K_M · 39.2 tok/s
85 ptsExcellent (S) · 85 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 14.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q4_K_M · 34.7 tok/s
83 ptsGreat (A) · 83 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 14.7/15, Memory use 9.3/15 NVIDIA RTX PRO 6000 Blackwell Q8_0 · 38.2 tok/s
80 ptsGreat (A) · 80 of 100 points: Model quality 33.9/45, Memory fit 25.0/25, Speed 6.2/15, Memory use 15.0/15 Apple M4 Pro (48 GB) Q6_K · 6.8 tok/s

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.