IBM·Granite·GraniteMoeHybridForCausalLM

Granite 4.0 H Tiny — Hardware Requirements & GPU Compatibility

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Granite 4.0 H Tiny is a 6.9B-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 4.63 GB of VRAM — see which GPUs and Macs can run it below.

57.6K downloads 209 likes 22.7K quant downloads131K context

Specifications

Publisher
IBM
Family
Granite
Parameters
6.9B
Architecture
GraniteMoeHybridForCausalLM
Context Length
131,072 tokens
Vocabulary Size
100,352
Release Date
2025-09-16
License
Apache 2.0

Get Started

How Much VRAM Does Granite 4.0 H Tiny Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_K3.403.4 GB
Q3_K_S3.503.5 GB
Q3_K_M3.903.9 GB
Q4_04.003.9 GB
Q4_K_M4.804.6 GB
Q5_K_M5.705.4 GB
Q6_K6.606.2 GB
Q8_08.007.4 GB

Which GPUs Can Run Granite 4.0 H Tiny?

Q4_K_M · 4.6 GB

Granite 4.0 H Tiny (Q4_K_M) requires 4.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. Using the full 131K context window can add up to 10.6 GB, bringing total usage to 15.2 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Runs great

— Plenty of headroom
NVIDIA GeForce RTX 5090~329 tok/sNVIDIA GeForce RTX 3090 Ti~271 tok/sNVIDIA GeForce RTX 4090~271 tok/sNVIDIA GeForce RTX 5080~266 tok/sNVIDIA GeForce RTX 3090~263 tok/sNVIDIA GeForce RTX 3080 Ti~260 tok/sNVIDIA GeForce RTX 5070 Ti~258 tok/sNVIDIA GeForce RTX 5090 Laptop GPU~258 tok/sNVIDIA GeForce RTX 3080~239 tok/sNVIDIA GeForce RTX 4080 SUPER~236 tok/sNVIDIA GeForce RTX 4080~233 tok/sNVIDIA GeForce RTX 4070 Ti SUPER~225 tok/sNVIDIA GeForce RTX 5070~225 tok/sNVIDIA TITAN RTX~225 tok/sNVIDIA GeForce RTX 2080 Ti~215 tok/sNVIDIA GeForce RTX 3070 Ti~214 tok/sNVIDIA GeForce RTX 4090 Laptop GPU~208 tok/sNVIDIA GeForce RTX 4070~193 tok/sNVIDIA GeForce RTX 4070 SUPER~193 tok/sNVIDIA GeForce RTX 4070 Ti~193 tok/sNVIDIA GeForce GTX 1080 Ti~189 tok/sNVIDIA GeForce RTX 3060 Ti~180 tok/sNVIDIA GeForce RTX 3070~180 tok/sNVIDIA GeForce RTX 5060~180 tok/sNVIDIA GeForce RTX 5060 Ti 16GB~180 tok/sNVIDIA GeForce RTX 5060 Ti 8GB~180 tok/sNVIDIA GeForce RTX 3060 12GB~157 tok/sNVIDIA GeForce RTX 4060 Ti 16GB~135 tok/sNVIDIA GeForce RTX 4060 Ti 8GB~135 tok/sNVIDIA GeForce RTX 4060~129 tok/sNVIDIA GeForce RTX 3060 8GB~118 tok/sNVIDIA GeForce RTX 3050 8GB~112 tok/sAMD Radeon RX 7900 XTX~103 tok/sAMD Radeon RX 7900 XT~100 tok/sAMD Radeon RX 9070~95 tok/sAMD Radeon RX 9070 XT~95 tok/sAMD Radeon RX 7800 XT~94 tok/sAMD Radeon RX 7900 GRE~92 tok/sAMD Radeon RX 6800~89 tok/sAMD Radeon RX 6800 XT~89 tok/sAMD Radeon RX 6900 XT~89 tok/sIntel Arc A770 16GB~87 tok/sAMD Radeon RX 7700 XT~85 tok/sAMD Radeon RX 9070 GRE~85 tok/sIntel Arc A750~85 tok/sAMD Radeon RX 6700 XT~82 tok/sIntel Arc B580~81 tok/sAMD Radeon RX 9060 XT 16GB~76 tok/sIntel Arc B570~76 tok/sAMD Radeon RX 7600~73 tok/sAMD Radeon RX 7600 XT~73 tok/sAMD Radeon RX 9050~73 tok/s

Which Devices Can Run Granite 4.0 H Tiny?

Q4_K_M · 4.6 GB

59 devices with unified memory can run Granite 4.0 H Tiny, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPhone 17.

Runs great

— Plenty of headroom
NVIDIA DGX H100~443 tok/sNVIDIA DGX A100 640GB~436 tok/sNVIDIA DGX Spark~130 tok/sNVIDIA Jetson AGX Thor Developer Kit~130 tok/sASUS Ascent GX10~105 tok/sNVIDIA Jetson AGX Orin 32GB~105 tok/sNVIDIA Jetson AGX Orin 64GB~105 tok/sMac Studio (M3 Ultra, 256GB)~103 tok/sMac Studio (M3 Ultra, 512GB)~103 tok/sMac Studio (M3 Ultra, 96GB)~103 tok/sMac Pro M2 Ultra (192 GB)~103 tok/sMac Studio M2 Ultra (192 GB)~103 tok/sAsus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB)~101 tok/sBeelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB)~101 tok/sFramework Desktop (Ryzen AI Max+ 395, 128 GB)~101 tok/sGMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB)~101 tok/sHP Z2 Mini G1a (Ryzen AI Max+ PRO 395, 128 GB)~101 tok/sHP ZBook Ultra G1a 14 (Ryzen AI Max+ PRO 395, 128 GB)~101 tok/sMinisforum MS-S1 MAX (Ryzen AI Max+ 395, 128 GB)~101 tok/sMacBook Pro 16" M5 Max (128 GB)~97 tok/sMac Studio M4 Max (128 GB)~95 tok/sMac Studio M4 Max (64 GB)~95 tok/sMacBook Pro 16" M4 Max (48 GB)~95 tok/sMacBook Pro 16" M4 Max (64 GB)~95 tok/sSnapdragon X2 Elite Extreme Copilot+ PC~94 tok/sMac Studio M4 Max (36 GB)~88 tok/sMacBook Pro 14" M4 Max (36 GB)~88 tok/sMacBook Pro 16" M3 Max (48 GB)~88 tok/sMacBook Pro 14-inch (M5 Pro)~80 tok/sMac Mini M4 Pro (24 GB)~76 tok/sMac Mini M4 Pro (48 GB)~76 tok/sMacBook Pro 14" M4 Pro (24 GB)~76 tok/sMacBook Pro 16" M4 Pro (24 GB)~76 tok/sSnapdragon X Elite Copilot+ PC~66 tok/sNVIDIA Jetson Orin NX 16GB~59 tok/sNVIDIA Jetson Orin Nano 8GB (Super)~59 tok/sMacBook Pro 14-inch (M5)~59 tok/siPad Pro M5 13" (16 GB)~58 tok/sMac Mini M4 (16 GB)~51 tok/sMac Mini M4 (32 GB)~51 tok/sMacBook Air 13" M4 (16 GB)~51 tok/sMacBook Air 13" M4 (24 GB)~51 tok/sMacBook Air 15" M4 (16 GB)~51 tok/sMacBook Air 15" M4 (24 GB)~51 tok/sMacBook Pro 14" M4 (16 GB)~51 tok/siPad Pro M4 13" (16 GB)~51 tok/sAMD Ryzen AI 9 HX 370 (Strix Point) Laptop~46 tok/sMacBook Air 13" M3 (16 GB)~46 tok/sMacBook Air 13" M3 (24 GB)~46 tok/sMacBook Air 13" M3 (8 GB)~46 tok/sIntel Core Ultra 9 288V (Lunar Lake) Laptop~45 tok/sApple iPhone 17 Pro~38 tok/siPhone 17 Pro Max~38 tok/siPhone Air~35 tok/siPhone 15 ProiPhone 15 Pro MaxiPhone 16 ProiPhone 16 Pro Max

Decent

— Enough memory, may be tight

Where to Download Granite 4.0 H Tiny

Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.

Related Models

Frequently Asked Questions

How much VRAM does Granite 4.0 H Tiny need?

Granite 4.0 H Tiny requires 4.6 GB of VRAM at Q4_K_M, or 14.3 GB at BF16. Full 131K context adds up to 10.6 GB (15.2 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 6.9B × 4.8 bits ÷ 8 = 4.2 GB

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

KV Cache + Overhead ≈ 11 GB (at full 131K context)

VRAM usage by quantization

4.6 GB
15.2 GB

Learn more about VRAM estimation →

What's the best quantization for Granite 4.0 H Tiny?

For Granite 4.0 H Tiny, Q4_K_M (4.6 GB) offers the best balance of quality and VRAM usage. Q5_0 (4.8 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 2.4 GB.

VRAM requirement by quantization

IQ2_XXS
2.4 GB
Q3_K_M
3.9 GB
Q4_1
4.4 GB
Q4_K_M ★
4.6 GB
Q5_1
5.2 GB
BF16
14.3 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Granite 4.0 H Tiny on a Mac?

Granite 4.0 H Tiny requires at least 2.4 GB at IQ2_XXS, 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 4.0 H Tiny locally?

Yes — Granite 4.0 H Tiny can run locally on consumer hardware. At Q4_K_M quantization it needs 4.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Granite 4.0 H Tiny?

At Q4_K_M, Granite 4.0 H Tiny can reach ~122 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~271 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 B200 → 8000 ÷ 4.6 × 0.65 = ~419 tok/s

Estimated speed at Q4_K_M (4.6 GB)

~419 tok/s
~271 tok/s
~419 tok/s
~399 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 4.0 H Tiny?

At Q4_K_M, the download is about 4.16 GB. The full-precision BF16 version is 13.88 GB. The smallest option (IQ2_XXS) is 1.91 GB.

Which GPUs can run Granite 4.0 H Tiny?

52 consumer GPUs can run Granite 4.0 H Tiny at Q4_K_M (4.6 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.

Which devices can run Granite 4.0 H Tiny?

59 devices with unified memory can run Granite 4.0 H Tiny at Q4_K_M (4.6 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.