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Can the NVIDIA GeForce RTX 5060 Ti 16GB run Gemma 2B IT?

54 ptsUsable (C) · 54 of 100 points: Model quality 5.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.5/15

Yes, it runs well

Runs well. At F16 it needs about 6.6 GB of 16.0 GB usable, with an estimated speed of 51.4 tok/s.

Best quant
F16
Generation speed
51.4 tok/s
Prompt processing
6,798 tok/s
First token (1K prompt)
0.3 s
Largest safe context
8K

Download Gemma 2B IT

Recommended for the NVIDIA GeForce RTX 5060 Ti 16GB: 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 gemma:2b-instruct-fp16

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.

huggingface.co/google/gemma-2b-it (opens in a new tab)

ollama run hf.co/google/gemma-2b-it

Original weights · Hugging Face

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

huggingface.co/google/gemma-2b-it (opens in a new tab)

Free Hugging Face account needed: request access on the model page, and Google approves it (usually within minutes to a few hours).

Links checked 1 week ago against Hugging Face, Ollama and GitHub.

How the C 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.5.4 / 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.9.5 / 15
Total54.9 / 10054 ptsUsable (C) · 54 of 100 points: Model quality 5.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.5/15

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

Every quantization on the NVIDIA GeForce RTX 5060 Ti 16GB

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 2.6 GB 16.0 GB 360 tok/s Runs well 47 ptsUsable (C) · 47 of 100 points: Model quality 3.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 3.7/15
Q3_K_M 2.8 GB 16.0 GB 283 tok/s Runs well 48 ptsUsable (C) · 48 of 100 points: Model quality 4.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.0/15
Q4_K_M 3.1 GB 16.0 GB 219 tok/s Runs well 49 ptsUsable (C) · 49 of 100 points: Model quality 5.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.4/15
Q5_K_M 3.3 GB 16.0 GB 181 tok/s Runs well 50 ptsUsable (C) · 50 of 100 points: Model quality 5.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.8/15
Q6_K 3.6 GB 16.0 GB 152 tok/s Runs well 50 ptsUsable (C) · 50 of 100 points: Model quality 5.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.2/15
Q8_0 4.2 GB 16.0 GB 112 tok/s Runs well 51 ptsUsable (C) · 51 of 100 points: Model quality 5.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.1/15
F16 6.6 GB 16.0 GB 51.4 tok/s Runs well 54 ptsUsable (C) · 54 of 100 points: Model quality 5.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.5/15 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

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.