granite 4.2 3b
3.7B parameters · 128k context · Apache 2.0 · released 2026-08-25
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In short
granite 4.2 3b is an open model from IBM with 3.7B parameters. At Q4_K_M, granite 4.2 3b needs about 4 GB of memory at 8k context and 4 GB at 8k, counting the weights, the KV cache and runtime buffers. The cheapest hardware in Germany that runs granite 4.2 3b fully in memory at 8k context is the NVIDIA GeForce RTX 3060 12GB, 309 € at Amazon, at about 49 tok/s (estimated).
Updated . Speeds are estimates; how they are worked out.
What to run it on in Germany
Fully in memory at 8k context, priced at retailers today.
Cheapest
NVIDIA GeForce RTX 3060 12GB49tok/sest.Q8_0
309 €
Best value
NVIDIA GeForce RTX 3080 10GB103tok/sest.Q8_0
500 €
Fastest
NVIDIA GeForce RTX 5090243tok/sest.Q8_0
6.028 €
Mac
Mac mini M4 16GB17tok/sest.Q8_0
800 €
All hardware that runs it
Everything we price, best value first. Two cards split the model by layers.
| Hardware | Quant | Fits | Decode | Price | tok/s per 1,000 |
|---|---|---|---|---|---|
| NVIDIA GeForce RTX 3060 12GB | Q8_0 | fits | 49 tok/s | 309 € | 158.3 |
| Intel Arc B580 | Q8_0 | fits | 50 tok/s | 360 € | 139.0 |
| NVIDIA Tesla P40 | Q8_0 | fits | 47 tok/s | 369 € | 127.4 |
| NVIDIA GeForce RTX 3080 10GB | Q8_0 | fits | 103 tok/s | 500 € | 206.4 |
| AMD Radeon RX 9060 XT 16GB | Q8_0 | fits | 39 tok/s | 550 € | 70.2 |
| Intel Arc A770 16GB | Q8_0 | fits | 61 tok/s | 646 € | 95.1 |
| NVIDIA GeForce RTX 4060 Ti 16GB | Q8_0 | fits | 39 tok/s | 650 € | 60.2 |
| NVIDIA GeForce RTX 5070 | Q8_0 | fits | 91 tok/s | 699 € | 130.6 |
| NVIDIA GeForce RTX 4070 Super | Q8_0 | fits | 69 tok/s | 707 € | 96.9 |
| NVIDIA GeForce RTX 5060 Ti 16GB | Q8_0 | fits | 61 tok/s | 739 € | 82.4 |
| AMD Radeon RX 9070 XT | Q8_0 | fits | 77 tok/s | 778 € | 99.1 |
| Mac mini M4 16GB | Q8_0 | fits | 17 tok/s | 800 € | 21.4 |
| AMD Radeon RX 7600 XT | Q8_0 | fits | 35 tok/s | 813 € | 42.7 |
| AMD Radeon RX 7900 XT | Q8_0 | fits | 96 tok/s | 855 € | 112.8 |
| AMD Radeon RX 7800 XT | Q8_0 | fits | 75 tok/s | 1.002 € | 75.1 |
| Intel Arc Pro B60 | Q8_0 | fits | 50 tok/s | 1.074 € | 46.5 |
| NVIDIA GeForce RTX 4080 Super | Q8_0 | fits | 100 tok/s | 1.100 € | 90.9 |
| NVIDIA GeForce RTX 5070 Ti | Q8_0 | fits | 122 tok/s | 1.149 € | 105.9 |
| NVIDIA GeForce RTX 4070 Ti Super | Q8_0 | fits | 91 tok/s | 1.247 € | 73.2 |
| Mac mini M4 32GB | Q8_0 | fits | 17 tok/s | 1.400 € | 12.2 |
| NVIDIA GeForce RTX 5080 | Q8_0 | fits | 130 tok/s | 1.500 € | 86.9 |
| AMD Radeon RX 7900 XTX | Q8_0 | fits | 116 tok/s | 1.555 € | 74.4 |
| NVIDIA GeForce RTX 3090 | Q8_0 | fits | 127 tok/s | 1.850 € | 68.8 |
| AMD Radeon AI PRO R9700 | Q8_0 | fits | 77 tok/s | 1.867 € | 41.3 |
| NVIDIA GeForce RTX 3090 Ti | Q8_0 | fits | 137 tok/s | 2.500 € | 54.8 |
| Mac mini M4 Pro 48GB | Q8_0 | fits | 39 tok/s | 2.699 € | 14.4 |
| Mac mini M4 Pro 64GB | Q8_0 | fits | 39 tok/s | 2.799 € | 13.9 |
| GMKtec EVO-X2 Ryzen AI Max+ 395 128GB | Q8_0 | fits | 31 tok/s | 3.700 € | 8.4 |
| NVIDIA GeForce RTX 4090 | Q8_0 | fits | 137 tok/s | 3.955 € | 34.6 |
| Mac Studio M4 Max 64GB | Q8_0 | fits | 78 tok/s | 4.183 € | 18.6 |
| Mac Studio M4 Max 128GB | Q8_0 | fits | 78 tok/s | 5.800 € | 13.4 |
| Mac Studio M3 Ultra 96GB | Q8_0 | fits | 117 tok/s | 5.999 € | 19.4 |
| NVIDIA GeForce RTX 5090 | Q8_0 | fits | 243 tok/s | 6.028 € | 40.4 |
| NVIDIA DGX Spark 128GB | Q8_0 | fits | 37 tok/s | 8.313 € | 4.5 |
| ASUS Ascent GX10 128GB | Q8_0 | fits | 37 tok/s | 8.623 € | 4.3 |
| Mac Studio M3 Ultra 256GB | Q8_0 | fits | 117 tok/s | 15.555 € | 7.5 |
| Mac Studio M3 Ultra 512GB | Q8_0 | fits | 117 tok/s | 18.995 € | 6.1 |
| NVIDIA RTX PRO 6000 Blackwell | Q8_0 | fits | 243 tok/s | 19.076 € | 12.8 |
| Framework Desktop Ryzen AI Max+ 395 128GB | Q8_0 | fits | 31 tok/s | – | – |
| Framework Desktop Ryzen AI Max+ 395 64GB | Q8_0 | fits | 31 tok/s | – | – |
Memory needed
Weights, KV cache and runtime buffers at each context length (KV cache at fp16).
| Quant | File | @8k | @32k | @64k | @128k |
|---|---|---|---|---|---|
| Q4_K_Mgguf | 2.2 GB | 3.5 GB | 5.5 GB | 8.2 GB | 13.6 GB |
| Q5_K_Mgguf | 2.5 GB | 3.9 GB | 5.9 GB | 8.6 GB | 13.9 GB |
| Q6_Kgguf | 2.9 GB | 4.3 GB | 6.3 GB | 9.0 GB | 14.4 GB |
| Q8_0gguf | 3.6 GB | 5.0 GB | 7.0 GB | 9.7 GB | 15.1 GB |
Run it
Copy a command for the runtime you use.
- Q4_K_M
- Ollama
ollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q4_K_M - LM Studio
lms get bartowski/granite-4.2-3b-GGUF@q4_k_m - llama.cpp
llama-server -hf bartowski/granite-4.2-3b-GGUF:Q4_K_M
- Ollama
- Q5_K_M
- Ollama
ollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q5_K_M - LM Studio
lms get bartowski/granite-4.2-3b-GGUF@q5_k_m - llama.cpp
llama-server -hf bartowski/granite-4.2-3b-GGUF:Q5_K_M
- Ollama
- Q6_K
- Ollama
ollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q6_K - LM Studio
lms get bartowski/granite-4.2-3b-GGUF@q6_k - llama.cpp
llama-server -hf bartowski/granite-4.2-3b-GGUF:Q6_K
- Ollama
- Q8_0
- Ollama
ollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q8_0 - LM Studio
lms get bartowski/granite-4.2-3b-GGUF@q8_0 - llama.cpp
llama-server -hf bartowski/granite-4.2-3b-GGUF:Q8_0
- Ollama
Notes
Native context is 128K, and the card also claims a long-context extension to 512K; its serving examples use 131072. The vLLM reasoning parser needs vLLM v0.20+ (or SGLang v0.5.18+), and the recommended sampling is temperature=1.0 and top_p=0.95.
Questions
- How much VRAM does granite 4.2 3b need?
- At Q4_K_M, granite 4.2 3b needs about 4 GB of memory at 8k context and 4 GB at 8k, counting the weights, the KV cache and runtime buffers.
- What is the best GPU for running granite 4.2 3b locally?
- The cheapest hardware in Germany that runs granite 4.2 3b fully in memory at 8k context is the NVIDIA GeForce RTX 3060 12GB, 309 € at Amazon, at about 49 tok/s (estimated). The best value is the NVIDIA GeForce RTX 3080 10GB (about 103 tok/s for 500 €). The fastest we price is the NVIDIA GeForce RTX 5090, at about 243 tok/s.
- Can I run granite 4.2 3b on a 16 GB GPU?
- Yes: at Q8_0 it fits fully in 16 GB at 8k context. On the NVIDIA GeForce RTX 5080 it runs at about 130 tok/s (estimated).
- Can I run granite 4.2 3b on a 24 GB GPU?
- Yes: at Q8_0 it fits fully in 24 GB at 8k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 137 tok/s (estimated).
- How do I run granite 4.2 3b locally?
- With Ollama: ollama run hf.co/bartowski/granite-4.2-3b-GGUF:Q4_K_M (the Q4_K_M build). LM Studio and llama.cpp commands are on this page.
- What licence is granite 4.2 3b released under?
- Apache 2.0, which allows commercial use.