Can the NVIDIA GeForce RTX 5080 run Gemma 4 E2B?

82 pts

Yes, it runs well

Runs well. At F16 it needs about 11.7 GB of 16.0 GB usable, with an estimated speed of 54.0 tok/s.

Best quant: F16
Generation speed: 54.0 tok/s
Prompt processing: 7,917 tok/s
First token (1K prompt): 0.3 s
Largest safe context: 128K

Download Gemma 4 E2B

Recommended for the NVIDIA GeForce RTX 5080: F16. 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 gemma4:e2b-it-bf16

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 F16 file (opens in a new tab)

huggingface.co/unsloth/gemma-4-E2B-it-GGUF (opens in a new tab)

ollama run hf.co/unsloth/gemma-4-E2B-it-GGUF:BF16

Original weights · Hugging Face

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

huggingface.co/google/gemma-4-E2B-it (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/google-deepmind/gemma (opens in a new tab)

git clone https://github.com/google-deepmind/gemma

Google DeepMind’s official Gemma library.

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.	27.9 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	25.0 / 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	82.9 / 100	82 ptsGreat (A) · 82 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, 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 5080

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	3.5 GB	16.0 GB	378 tok/s	Runs well	64 ptsGood (B) · 64 of 100 points: Model quality 19.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.1/15	GGUF (UD-Q2_K_XL) (opens in a new tab)
`Q3_K_M`	4.0 GB	16.0 GB	298 tok/s	Runs well	69 ptsGood (B) · 69 of 100 points: Model quality 23.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.7/15	GGUF (opens in a new tab)
`Q4_K_M`	4.6 GB	16.0 GB	230 tok/s	Runs well	73 ptsGreat (A) · 73 of 100 points: Model quality 26.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.6/15	GGUF (opens in a new tab)
`Q5_K_M`	5.1 GB	16.0 GB	190 tok/s	Runs well	74 ptsGreat (A) · 74 of 100 points: Model quality 27.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.4/15	GGUF (opens in a new tab)
`Q6_K`	5.7 GB	16.0 GB	160 tok/s	Runs well	75 ptsGreat (A) · 75 of 100 points: Model quality 27.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.2/15	GGUF (opens in a new tab)
`Q8_0`	6.9 GB	16.0 GB	117 tok/s	Runs well	77 ptsGreat (A) · 77 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.9/15	GGUF (opens in a new tab)
`F16`	11.7 GB	16.0 GB	54.0 tok/s	Runs well	82 ptsGreat (A) · 82 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (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

82 ptsGreat (A) · 82 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4080 SUPER F16 · 41.4 tok/s
82 ptsGreat (A) · 82 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5070 Ti F16 · 50.4 tok/s
82 ptsGreat (A) · 82 of 100 points: Model quality 27.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4060 Q6_K · 45.2 tok/s
80 ptsGreat (A) · 80 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.9/15 Intel Arc B580 Q8_0 · 42.5 tok/s
80 ptsGreat (A) · 80 of 100 points: Model quality 27.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.9/15 NVIDIA GeForce RTX 3060 12GB Q8_0 · 43.9 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.