Gemma 4 26B-A4B on NVIDIA GeForce RTX 5080 Laptop GPU

Can the NVIDIA GeForce RTX 5080 Laptop GPU run Gemma 4 26B-A4B?

88 pts

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 14.4 GB of 16.0 GB usable, with an estimated speed of 187 tok/s.

Best quant: Q3_K_M
Generation speed: 187 tok/s
Prompt processing: 7,768 tok/s
First token (1K prompt): 0.3 s
Largest safe context: 38K

Download Gemma 4 26B-A4B

Recommended for the NVIDIA GeForce RTX 5080 Laptop GPU: Q3_K_M. 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 gemma4:26b

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 Q3_K_M file (opens in a new tab)

huggingface.co/unsloth/gemma-4-26B-A4B-it-GGUF (opens in a new tab)

ollama run hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:Q3_K_M

Original weights · Hugging Face

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

huggingface.co/google/gemma-4-26B-A4B-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 6 days ago against Hugging Face, Ollama and GitHub.

How the S 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.	35.0 / 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	89.0 / 100	88 ptsExcellent (S) · 88 of 100 points: Model quality 35.0/45, 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 5080 Laptop GPU

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	12.1 GB	16.0 GB	238 tok/s	Runs well	84 ptsGreat (A) · 84 of 100 points: Model quality 29.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (UD-Q2_K_XL) (opens in a new tab)
`Q3_K_M`	14.4 GB	16.0 GB	187 tok/s	Tight fit	88 ptsExcellent (S) · 88 of 100 points: Model quality 35.0/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q4_K_M`	17.5 GB	16.0 GB	65.1 tok/s	Runs with offload	79 ptsGreat (A) · 79 of 100 points: Model quality 39.5/45, Memory fit 10.0/25, Speed 15.0/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q5_K_M`	20.1 GB	16.0 GB	31.4 tok/s	Runs with offload	78 ptsGreat (A) · 78 of 100 points: Model quality 40.4/45, Memory fit 10.0/25, Speed 13.3/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q6_K`	23.0 GB	16.0 GB	19.7 tok/s	Heavy offload	70 ptsGood (B) · 70 of 100 points: Model quality 41.2/45, Memory fit 4.0/25, Speed 10.5/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q8_0`	29.2 GB	16.0 GB	10.5 tok/s	Heavy offload	68 ptsGood (B) · 68 of 100 points: Model quality 41.6/45, Memory fit 4.0/25, Speed 7.7/15, Memory use 15.0/15	GGUF (opens in a new tab)
`F16`	53.4 GB	16.0 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (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

96 ptsExcellent (S) · 96 of 100 points: Model quality 41.6/45, Memory fit 25.0/25, Speed 14.7/15, Memory use 15.0/15 Apple M4 Max (64 GB) Q8_0 · 38.7 tok/s
96 ptsExcellent (S) · 96 of 100 points: Model quality 41.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q6_K · 201 tok/s
95 ptsExcellent (S) · 95 of 100 points: Model quality 41.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.8/15 NVIDIA RTX PRO 6000 Blackwell F16 · 67.9 tok/s
95 ptsExcellent (S) · 95 of 100 points: Model quality 41.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q6_K · 92.6 tok/s
95 ptsExcellent (S) · 95 of 100 points: Model quality 41.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q6_K · 105 tok/s
95 ptsExcellent (S) · 95 of 100 points: Model quality 41.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q6_K · 113 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.