IBM·Granite·GraniteMoeForCausalLM

Granite 3.1 1B A400m Base — Hardware Requirements & GPU Compatibility

Chat

Granite 3.1 1B A400m Base is a 1.3B-parameter open language model from IBM in the Granite family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 1.20 GB of VRAM — see which GPUs and Macs can run it below.

1.7K downloads 10 likes131K context

Specifications

Publisher
IBM
Family
Granite
Parameters
1.3B
Architecture
GraniteMoeForCausalLM
Context Length
131,072 tokens
Vocabulary Size
49,152
Release Date
2024-12-06
License
Apache 2.0

Get Started

How Much VRAM Does Granite 3.1 1B A400m Base Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.401.0 GB
Q3_K_Mest.3.901.1 GB
Q4_K_Mest.4.801.2 GB
Q5_K_Mest.5.701.4 GB
Q6_Kest.6.601.5 GB
Q8_0est.8.001.7 GB
BF16est.16.003.1 GB

est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.

Which GPUs Can Run Granite 3.1 1B A400m Base?

Q4_K_M · 1.2 GB

Granite 3.1 1B A400m Base (Q4_K_M) requires 1.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2+ GB is recommended. Using the full 131K context window can add up to 6.3 GB, bringing total usage to 7.5 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Runs great

Plenty of headroom
NVIDIA GeForce RTX 5090~971 tok/sNVIDIA GeForce RTX 3090 Ti~546 tok/sNVIDIA GeForce RTX 4090~546 tok/sNVIDIA GeForce RTX 5080~520 tok/sNVIDIA GeForce RTX 3090~507 tok/sNVIDIA GeForce RTX 3080 Ti~494 tok/sNVIDIA GeForce RTX 5070 Ti~485 tok/sNVIDIA GeForce RTX 5090 Laptop GPU~485 tok/sAMD Radeon RX 7900 XTX~480 tok/sNVIDIA GeForce RTX 3080~412 tok/sAMD Radeon RX 7900 XT~400 tok/sNVIDIA GeForce RTX 4080 SUPER~399 tok/sNVIDIA GeForce RTX 4080~388 tok/sNVIDIA GeForce RTX 4070 Ti SUPER~364 tok/sNVIDIA GeForce RTX 5070~364 tok/sNVIDIA TITAN RTX~364 tok/sNVIDIA GeForce RTX 2080 Ti~334 tok/sNVIDIA GeForce RTX 3070 Ti~330 tok/sAMD Radeon RX 9070~320 tok/sAMD Radeon RX 9070 XT~320 tok/sAMD Radeon RX 7800 XT~312 tok/sNVIDIA GeForce RTX 4090 Laptop GPU~312 tok/sAMD Radeon RX 7900 GRE~288 tok/sNVIDIA GeForce RTX 4070~273 tok/sNVIDIA GeForce RTX 4070 SUPER~273 tok/sNVIDIA GeForce RTX 4070 Ti~273 tok/sNVIDIA GeForce GTX 1080 Ti~262 tok/sAMD Radeon RX 6800~256 tok/sAMD Radeon RX 6800 XT~256 tok/sAMD Radeon RX 6900 XT~256 tok/sNVIDIA GeForce RTX 3060 Ti~243 tok/sNVIDIA GeForce RTX 3070~243 tok/sNVIDIA GeForce RTX 5060~243 tok/sNVIDIA GeForce RTX 5060 Ti 16GB~243 tok/sNVIDIA GeForce RTX 5060 Ti 8GB~243 tok/sIntel Arc A770 16GB~233 tok/sAMD Radeon RX 7700 XT~216 tok/sIntel Arc A750~213 tok/sNVIDIA GeForce RTX 3060 12GB~195 tok/sAMD Radeon RX 6700 XT~192 tok/sIntel Arc B580~190 tok/sAMD Radeon RX 9060 XT 16GB~160 tok/sIntel Arc B570~158 tok/sNVIDIA GeForce RTX 4060 Ti 16GB~156 tok/sNVIDIA GeForce RTX 4060 Ti 8GB~156 tok/sNVIDIA GeForce RTX 4060~147 tok/sAMD Radeon RX 7600~144 tok/sAMD Radeon RX 7600 XT~144 tok/sNVIDIA GeForce RTX 3060 8GB~130 tok/sNVIDIA GeForce RTX 3050 8GB~121 tok/s

Which Devices Can Run Granite 3.1 1B A400m Base?

Q4_K_M · 1.2 GB

59 devices with unified memory can run Granite 3.1 1B A400m Base, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.

Runs great

Plenty of headroom
NVIDIA DGX H100~14517 tok/sNVIDIA DGX A100 640GB~8836 tok/sMac Studio (M3 Ultra, 256GB)~478 tok/sMac Studio (M3 Ultra, 512GB)~478 tok/sMac Studio (M3 Ultra, 96GB)~478 tok/sMac Pro M2 Ultra (192 GB)~467 tok/sMac Studio M2 Ultra (192 GB)~467 tok/sMacBook Pro 16" M5 Max (128 GB)~358 tok/sMac Studio M4 Max (128 GB)~319 tok/sMac Studio M4 Max (64 GB)~319 tok/sMacBook Pro 16" M4 Max (48 GB)~319 tok/sMacBook Pro 16" M4 Max (64 GB)~319 tok/sMac Studio M4 Max (36 GB)~239 tok/sMacBook Pro 14" M4 Max (36 GB)~239 tok/sMacBook Pro 16" M3 Max (48 GB)~239 tok/sMacBook Pro 14-inch (M5 Pro)~179 tok/sMac Mini M4 Pro (24 GB)~159 tok/sMac Mini M4 Pro (48 GB)~159 tok/sMacBook Pro 14" M4 Pro (24 GB)~159 tok/sMacBook Pro 16" M4 Pro (24 GB)~159 tok/sASUS Ascent GX10~148 tok/sNVIDIA DGX Spark~148 tok/sNVIDIA Jetson AGX Thor Developer Kit~148 tok/sAsus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB)~139 tok/sBeelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB)~139 tok/sFramework Desktop (Ryzen AI Max+ 395, 128 GB)~139 tok/sGMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB)~139 tok/sHP Z2 Mini G1a (Ryzen AI Max+ PRO 395, 128 GB)~139 tok/sHP ZBook Ultra G1a 14 (Ryzen AI Max+ PRO 395, 128 GB)~139 tok/sMinisforum MS-S1 MAX (Ryzen AI Max+ 395, 128 GB)~139 tok/sSnapdragon X2 Elite Extreme Copilot+ PC~124 tok/sNVIDIA Jetson AGX Orin 32GB~111 tok/sNVIDIA Jetson AGX Orin 64GB~111 tok/sMacBook Pro 14-inch (M5)~90 tok/siPad Pro M5 13" (16 GB)~89 tok/sSnapdragon X Elite Copilot+ PC~73 tok/sMac Mini M4 (16 GB)~70 tok/sMac Mini M4 (32 GB)~70 tok/sMacBook Air 13" M4 (16 GB)~70 tok/sMacBook Air 13" M4 (24 GB)~70 tok/sMacBook Air 15" M4 (16 GB)~70 tok/sMacBook Air 15" M4 (24 GB)~70 tok/sMacBook Pro 14" M4 (16 GB)~70 tok/siPad Pro M4 13" (16 GB)~70 tok/sAMD Ryzen AI 9 HX 370 (Strix Point) Laptop~60 tok/sMacBook Air 13" M3 (16 GB)~60 tok/sMacBook Air 13" M3 (24 GB)~60 tok/sMacBook Air 13" M3 (8 GB)~60 tok/sIntel Core Ultra 9 288V (Lunar Lake) Laptop~57 tok/sNVIDIA Jetson Orin NX 16GB~56 tok/sNVIDIA Jetson Orin Nano 8GB (Super)~55 tok/sApple iPhone 17 Pro~45 tok/siPhone 17 Pro Max~45 tok/siPhone 17~40 tok/siPhone Air~40 tok/siPhone 15 ProiPhone 15 Pro MaxiPhone 16 ProiPhone 16 Pro Max

Related Models

Frequently Asked Questions

How much VRAM does Granite 3.1 1B A400m Base need?

Granite 3.1 1B A400m Base requires 1.2 GB of VRAM at Q4_K_M, or 3.1 GB at BF16. Full 131K context adds up to 6.3 GB (7.5 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 1.3B × 4.8 bits ÷ 8 = 0.8 GB

KV Cache + Overhead 0.4 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 6.7 GB (at full 131K context)

VRAM usage by quantization

1.2 GB
7.5 GB

Learn more about VRAM estimation →

What's the best quantization for Granite 3.1 1B A400m Base?

For Granite 3.1 1B A400m Base, Q4_K_M (1.2 GB) offers the best balance of quality and VRAM usage. Q5_K_M (1.4 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 1.0 GB.

VRAM requirement by quantization

Q2_K
1.0 GB
Q4_K_M
1.2 GB
Q5_K_M
1.4 GB
Q6_K
1.5 GB
Q8_0
1.7 GB
BF16
3.1 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Granite 3.1 1B A400m Base on a Mac?

Granite 3.1 1B A400m Base requires at least 1.0 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.

Can I run Granite 3.1 1B A400m Base locally?

Yes — Granite 3.1 1B A400m Base can run locally on consumer hardware. At Q4_K_M quantization it needs 1.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Granite 3.1 1B A400m Base?

At Q4_K_M, Granite 3.1 1B A400m Base can reach ~4000 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~546 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: NVIDIA B2008000 ÷ 1.2 × 0.65 = ~4333 tok/s

Estimated speed at Q4_K_M (1.2 GB)

~4333 tok/s
~546 tok/s
~4333 tok/s
~4000 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of Granite 3.1 1B A400m Base?

At Q4_K_M, the download is about 0.80 GB. The full-precision BF16 version is 2.67 GB. The smallest option (Q2_K) is 0.57 GB.

Which GPUs can run Granite 3.1 1B A400m Base?

50 consumer GPUs can run Granite 3.1 1B A400m Base at Q4_K_M (1.2 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.

Which devices can run Granite 3.1 1B A400m Base?

59 devices with unified memory can run Granite 3.1 1B A400m Base at Q4_K_M (1.2 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.