Run ibm-granite/granite-4.1-3b-GGUF locally

License: apache-2.0 ⬇ 218,936 ❤ 5
Parameters3.4B
Context131,072

ibm-granite/granite-4.1-3b-GGUF is a mid-size language model with 3.4 billion parameters, built on the granite architecture. It is released under the apache-2.0 license and has been downloaded 218,936 times.

To run ibm-granite/granite-4.1-3b-GGUF locally at a 4,096-token context, its quantized versions need between 2.39 GB (Q2_K, lowest quality) and 7.45 GB (BF16, highest quality) of memory, weights plus KV cache and a system margin included.

For most users the best balance is BF16, needing about 7.45 GB. That means ibm-granite/granite-4.1-3b-GGUF fits entirely in the VRAM of a 6 GB GPU or larger, running fully on the GPU.

→ Guide: How much VRAM do you need?

All quantizations

Quant.Bits QualityWeights KVTotal Speed~Verdict
Q2_K 3.22 Low 1.28 GB 0.31 GB 2.39 GB 313.2 t/s Fits in VRAM
Q3_K_S 3.68 Fair 1.46 GB 0.31 GB 2.57 GB 274.1 t/s Fits in VRAM
Q3_K_M 4.06 Fair 1.61 GB 0.31 GB 2.72 GB 248.9 t/s Fits in VRAM
Q3_K_L 4.38 Good 1.74 GB 0.31 GB 2.85 GB 230.4 t/s Fits in VRAM
Q4_0 4.67 Good 1.85 GB 0.31 GB 2.96 GB 216.4 t/s Fits in VRAM
Q4_K_S 4.7 Good 1.86 GB 0.31 GB 2.97 GB 214.9 t/s Fits in VRAM
Q4_K_M 4.94 Good 1.96 GB 0.31 GB 3.07 GB 204.6 t/s Fits in VRAM
Q4_1 5.13 Very good 2.03 GB 0.31 GB 3.14 GB 196.9 t/s Fits in VRAM
Q5_0 5.59 Very good 2.21 GB 0.31 GB 3.33 GB 180.6 t/s Fits in VRAM
Q5_K_S 5.59 Very good 2.21 GB 0.31 GB 3.33 GB 180.6 t/s Fits in VRAM
Q5_K_M 5.73 Very good 2.27 GB 0.31 GB 3.38 GB 176.2 t/s Fits in VRAM
Q5_1 6.05 Very good 2.4 GB 0.31 GB 3.51 GB 166.8 t/s Fits in VRAM
Q6_K 6.57 Excellent 2.6 GB 0.31 GB 3.72 GB 153.6 t/s Fits in VRAM
Q8_0 8.51 Excellent 3.37 GB 0.31 GB 4.48 GB 118.7 t/s Fits in VRAM
BF16 16.01 Excellent 6.34 GB 0.31 GB 7.45 GB 63.1 t/s Fits in VRAM

KV cache computed from the model's exact architecture. Speed is a rough estimate bounded by memory bandwidth.

Frequently asked questions

How much VRAM do you need to run ibm-granite/granite-4.1-3b-GGUF?

You need about 4.48 GB of VRAM to run ibm-granite/granite-4.1-3b-GGUF entirely on the GPU using the Q8_0 quantization (at a 4,096-token context). Smaller quantizations lower the requirement at the cost of quality.

Can I run ibm-granite/granite-4.1-3b-GGUF on an 8 GB GPU?

Yes. With 8 GB of VRAM you can run ibm-granite/granite-4.1-3b-GGUF fully on the GPU using BF16 (about 7.45 GB).

Can I run ibm-granite/granite-4.1-3b-GGUF on a 16 GB GPU?

Yes. With 16 GB of VRAM you can run ibm-granite/granite-4.1-3b-GGUF fully on the GPU using BF16 (about 7.45 GB).

Can I run ibm-granite/granite-4.1-3b-GGUF on a 24 GB GPU?

Yes. With 24 GB of VRAM you can run ibm-granite/granite-4.1-3b-GGUF fully on the GPU using BF16 (about 7.45 GB).

What is the best quantization for ibm-granite/granite-4.1-3b-GGUF?

If memory allows, higher bits-per-weight means better quality. A common sweet spot is a Q4_K_M or Q5_K_M quantization, which keeps most of the quality while roughly halving the memory versus 8-bit. Pick the highest quantization that still fits in your VRAM.