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Can the NVIDIA GeForce RTX 5070 Ti run Gemma 7B IT?

66 ptsGood (B) · 66 of 100 points: Model quality 11.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q6_K it needs about 12.2 GB of 16.0 GB usable, with an estimated speed of 89.4 tok/s.

Best quant
Q6_K
Generation speed
89.4 tok/s
Prompt processing
3,701 tok/s
First token (1K prompt)
0.3 s
Largest safe context
8K

Download Gemma 7B IT

Recommended for the NVIDIA GeForce RTX 5070 Ti: Q6_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 gemma:7b-instruct-q6_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.

huggingface.co/google/gemma-7b-it (opens in a new tab)

ollama run hf.co/google/gemma-7b-it

Original weights · Hugging Face

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

huggingface.co/google/gemma-7b-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 6 days ago against Hugging Face, Ollama and GitHub.

How the B 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.11.6 / 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
Total66.6 / 10066 ptsGood (B) · 66 of 100 points: Model quality 11.6/45, 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 5070 Ti

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 8.6 GB 16.0 GB 212 tok/s Runs well 60 ptsGood (B) · 60 of 100 points: Model quality 8.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.4/15
Q3_K_M 9.3 GB 16.0 GB 166 tok/s Runs well 63 ptsGood (B) · 63 of 100 points: Model quality 9.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.5/15
Q4_K_M 10.4 GB 16.0 GB 129 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 11.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15
Q5_K_M 11.2 GB 16.0 GB 106 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 11.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15
Q6_K 12.2 GB 16.0 GB 89.4 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 11.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15
Q8_0 14.2 GB 16.0 GB 65.6 tok/s Tight fit 65 ptsGood (B) · 65 of 100 points: Model quality 11.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15
F16 22.2 GB 16.0 GB 5.5 tok/s Heavy offload 36 ptsPoor (D) · 36 of 100 points: Model quality 11.7/45, Memory fit 4.0/25, Speed 5.5/15, Memory use 15.0/15 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.