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Can the NVIDIA GeForce RTX 5080 run Granite Code 3B Instruct (128K)?

64 ptsGood (B) · 64 of 100 points: Model quality 9.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At F16 it needs about 11.0 GB of 16.0 GB usable, with an estimated speed of 79.4 tok/s.

Best quant
F16
Generation speed
79.4 tok/s
Prompt processing
11,648 tok/s
First token (1K prompt)
0.3 s
Largest safe context
22K

Download Granite Code 3B Instruct (128K)

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 granite-code:3b-instruct-128k-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/mradermacher/granite-3b-code-instruct-128k-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/granite-3b-code-instruct-128k-i1-GGUF

Original weights · Hugging Face

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

huggingface.co/ibm-granite/granite-3b-code-instruct-128k (opens in a new tab)

No sign-in needed.

Links checked 1 week 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.9.0 / 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
Total64.0 / 10064 ptsGood (B) · 64 of 100 points: Model quality 9.0/45, 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 5.5 GB 16.0 GB 556 tok/s Runs well 54 ptsUsable (C) · 54 of 100 points: Model quality 6.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.9/15 GGUF (opens in a new tab)
Q3_K_M 5.8 GB 16.0 GB 438 tok/s Runs well 55 ptsUsable (C) · 55 of 100 points: Model quality 7.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.4/15 GGUF (opens in a new tab)
Q4_K_M 6.2 GB 16.0 GB 339 tok/s Runs well 57 ptsUsable (C) · 57 of 100 points: Model quality 8.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.0/15 GGUF (opens in a new tab)
Q5_K_M 6.6 GB 16.0 GB 280 tok/s Runs well 58 ptsGood (B) · 58 of 100 points: Model quality 8.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.5/15 GGUF (opens in a new tab)
Q6_K 6.9 GB 16.0 GB 235 tok/s Runs well 58 ptsGood (B) · 58 of 100 points: Model quality 8.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.0/15 GGUF (opens in a new tab)
Q8_0 7.8 GB 16.0 GB 172 tok/s Runs well 60 ptsGood (B) · 60 of 100 points: Model quality 9.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.2/15
F16 11.0 GB 16.0 GB 79.4 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 9.0/45, Memory fit 25.0/25, Speed 15.0/15, 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.