Granite 3.3 2B on NVIDIA GeForce RTX 4080 SUPER
Can the NVIDIA GeForce RTX 4080 SUPER run Granite 3.3 2B?
Yes, it runs well
Runs well. At F16 it needs about 7.1 GB of 16.0 GB usable, with an estimated speed of 83.8 tok/s.
- Best quant
F16- Generation speed
- 83.8 tok/s
- Prompt processing
- 14,855 tok/s
- First token (1K prompt)
- 0.3 s
- Largest safe context
- 113K
Download Granite 3.3 2B
Recommended for the NVIDIA GeForce RTX 4080 SUPER: 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 granite3.3:2bQuantized 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/ibm-granite/granite-3.3-2b-instruct-GGUF (opens in a new tab)
ollama run hf.co/ibm-granite/granite-3.3-2b-instruct-GGUF:F16Original weights · Hugging Face
Full-precision files from IBM, for fine-tuning, vLLM, Transformers.
huggingface.co/ibm-granite/granite-3.3-2b-instruct (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from IBM. The weights themselves download from Hugging Face.
github.com/ibm-granite/granite-3.3-language-models (opens in a new tab)
git clone https://github.com/ibm-granite/granite-3.3-language-modelsHow the B grade is scored
Every result gets up to 100 points from four parts. The points decide the letter grade.
| Model quality | 13.5 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 15.0 / 15 | |
| Memory use | 10.3 / 15 | |
| Total | 63.8 / 100 | 63 ptsGood (B) · 63 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.3/15 |
Every quantization on the NVIDIA GeForce RTX 4080 SUPER
| Quant | Memory needed | Available | Speed | Fit | Grade · points | Download |
|---|---|---|---|---|---|---|
Q2_K | 3.1 GB | 16.0 GB | 586 tok/s | Runs well | 53 ptsUsable (C) · 53 of 100 points: Model quality 9.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.4/15 | GGUF (opens in a new tab) |
Q3_K_M | 3.3 GB | 16.0 GB | 462 tok/s | Runs well | 56 ptsUsable (C) · 56 of 100 points: Model quality 11.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.8/15 | GGUF (opens in a new tab) |
Q4_K_M | 3.6 GB | 16.0 GB | 357 tok/s | Runs well | 58 ptsGood (B) · 58 of 100 points: Model quality 12.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.2/15 | GGUF (opens in a new tab) |
Q5_K_M | 3.9 GB | 16.0 GB | 295 tok/s | Runs well | 58 ptsGood (B) · 58 of 100 points: Model quality 13.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.6/15 | GGUF (opens in a new tab) |
Q6_K | 4.1 GB | 16.0 GB | 248 tok/s | Runs well | 59 ptsGood (B) · 59 of 100 points: Model quality 13.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.0/15 | GGUF (opens in a new tab) |
Q8_0 | 4.8 GB | 16.0 GB | 182 tok/s | Runs well | 60 ptsGood (B) · 60 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.9/15 | GGUF (opens in a new tab) |
F16 | 7.1 GB | 16.0 GB | 83.8 tok/s | Runs well | 63 ptsGood (B) · 63 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.3/15 | 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
- 66 ptsGood (B) · 66 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.3/15 NVIDIA GeForce RTX 3060 12GB
- 66 ptsGood (B) · 66 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.3/15 NVIDIA GeForce RTX 4070 SUPER
- 66 ptsGood (B) · 66 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.6/15 NVIDIA GeForce RTX 4060
- 63 ptsGood (B) · 63 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.3/15 AMD Radeon RX 9070 XT
- 63 ptsGood (B) · 63 of 100 points: Model quality 13.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.3/15 NVIDIA GeForce RTX 4070 Ti SUPER
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.