TII UAE·Falcon·FalconH1ForCausalLM

Falcon H1 0.5B Instruct — Hardware Requirements & GPU Compatibility

Chat

Falcon H1 0.5B Instruct is a 521M-parameter open language model from TII UAE in the Falcon family. It supports a context window of up to 16,384 tokens. At Q4_K_M it needs about 0.69 GB of VRAM — see which GPUs and Macs can run it below.

1.3K downloads 33 likes16K context

Specifications

Publisher
TII UAE
Family
Falcon
Parameters
521M
Architecture
FalconH1ForCausalLM
Context Length
16,384 tokens
Vocabulary Size
32,784
Release Date
2025-05-01
License
Other

Get Started

How Much VRAM Does Falcon H1 0.5B Instruct Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.400.6 GB
Q3_K_Mest.3.900.6 GB
Q4_K_Mest.4.800.7 GB
Q5_K_Mest.5.700.8 GB
Q6_Kest.6.600.8 GB
Q8_0est.8.000.9 GB
BF16est.16.001.4 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 Falcon H1 0.5B Instruct?

Q4_K_M · 0.7 GB

Falcon H1 0.5B Instruct (Q4_K_M) requires 0.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ GB is recommended. Using the full 16K context window can add up to 0.5 GB, bringing total usage to 1.2 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Runs great

Plenty of headroom
NVIDIA GeForce RTX 5090~1688 tok/sNVIDIA GeForce RTX 3090 Ti~950 tok/sNVIDIA GeForce RTX 4090~950 tok/sNVIDIA GeForce RTX 5080~904 tok/sNVIDIA GeForce RTX 3090~882 tok/sNVIDIA GeForce RTX 3080 Ti~860 tok/sNVIDIA GeForce RTX 5070 Ti~844 tok/sNVIDIA GeForce RTX 5090 Laptop GPU~844 tok/sAMD Radeon RX 7900 XTX~765 tok/sNVIDIA GeForce RTX 3080~716 tok/sNVIDIA GeForce RTX 4080 SUPER~693 tok/sNVIDIA GeForce RTX 4080~675 tok/sAMD Radeon RX 7900 XT~638 tok/sNVIDIA GeForce RTX 4070 Ti SUPER~633 tok/sNVIDIA GeForce RTX 5070~633 tok/sNVIDIA TITAN RTX~633 tok/sNVIDIA GeForce RTX 2080 Ti~580 tok/sNVIDIA GeForce RTX 3070 Ti~573 tok/sNVIDIA GeForce RTX 4090 Laptop GPU~543 tok/sAMD Radeon RX 9070~510 tok/sAMD Radeon RX 9070 XT~510 tok/sAMD Radeon RX 7800 XT~497 tok/sNVIDIA GeForce RTX 4070~475 tok/sNVIDIA GeForce RTX 4070 SUPER~475 tok/sNVIDIA GeForce RTX 4070 Ti~475 tok/sAMD Radeon RX 7900 GRE~459 tok/sNVIDIA GeForce GTX 1080 Ti~456 tok/sNVIDIA GeForce RTX 3060 Ti~422 tok/sNVIDIA GeForce RTX 3070~422 tok/sNVIDIA GeForce RTX 5060~422 tok/sNVIDIA GeForce RTX 5060 Ti 16GB~422 tok/sNVIDIA GeForce RTX 5060 Ti 8GB~422 tok/sAMD Radeon RX 6800~408 tok/sAMD Radeon RX 6800 XT~408 tok/sAMD Radeon RX 6900 XT~408 tok/sIntel Arc A770 16GB~406 tok/sIntel Arc A750~371 tok/sAMD Radeon RX 7700 XT~344 tok/sNVIDIA GeForce RTX 3060 12GB~339 tok/sIntel Arc B580~330 tok/sAMD Radeon RX 6700 XT~306 tok/sIntel Arc B570~275 tok/sNVIDIA GeForce RTX 4060 Ti 16GB~271 tok/sNVIDIA GeForce RTX 4060 Ti 8GB~271 tok/sNVIDIA GeForce RTX 4060~256 tok/sAMD Radeon RX 9060 XT 16GB~255 tok/sAMD Radeon RX 7600~230 tok/sAMD Radeon RX 7600 XT~230 tok/sNVIDIA GeForce RTX 3060 8GB~226 tok/sNVIDIA GeForce RTX 3050 8GB~211 tok/s

Which Devices Can Run Falcon H1 0.5B Instruct?

Q4_K_M · 0.7 GB

59 devices with unified memory can run Falcon H1 0.5B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.

Runs great

Plenty of headroom
NVIDIA DGX H100~25246 tok/sNVIDIA DGX A100 640GB~15366 tok/sMac Studio (M3 Ultra, 256GB)~831 tok/sMac Studio (M3 Ultra, 512GB)~831 tok/sMac Studio (M3 Ultra, 96GB)~831 tok/sMac Pro M2 Ultra (192 GB)~812 tok/sMac Studio M2 Ultra (192 GB)~812 tok/sMacBook Pro 16" M5 Max (128 GB)~623 tok/sMac Studio M4 Max (128 GB)~554 tok/sMac Studio M4 Max (64 GB)~554 tok/sMacBook Pro 16" M4 Max (48 GB)~554 tok/sMacBook Pro 16" M4 Max (64 GB)~554 tok/sMac Studio M4 Max (36 GB)~416 tok/sMacBook Pro 14" M4 Max (36 GB)~416 tok/sMacBook Pro 16" M3 Max (48 GB)~416 tok/sMacBook Pro 14-inch (M5 Pro)~311 tok/sMac Mini M4 Pro (24 GB)~277 tok/sMac Mini M4 Pro (48 GB)~277 tok/sMacBook Pro 14" M4 Pro (24 GB)~277 tok/sMacBook Pro 16" M4 Pro (24 GB)~277 tok/sASUS Ascent GX10~257 tok/sNVIDIA DGX Spark~257 tok/sNVIDIA Jetson AGX Thor Developer Kit~257 tok/sAsus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB)~241 tok/sBeelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB)~241 tok/sFramework Desktop (Ryzen AI Max+ 395, 128 GB)~241 tok/sGMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB)~241 tok/sHP Z2 Mini G1a (Ryzen AI Max+ PRO 395, 128 GB)~241 tok/sHP ZBook Ultra G1a 14 (Ryzen AI Max+ PRO 395, 128 GB)~241 tok/sMinisforum MS-S1 MAX (Ryzen AI Max+ 395, 128 GB)~241 tok/sSnapdragon X2 Elite Extreme Copilot+ PC~215 tok/sNVIDIA Jetson AGX Orin 32GB~193 tok/sNVIDIA Jetson AGX Orin 64GB~193 tok/sMacBook Pro 14-inch (M5)~156 tok/siPad Pro M5 13" (16 GB)~155 tok/sSnapdragon X Elite Copilot+ PC~127 tok/sMac Mini M4 (16 GB)~122 tok/sMac Mini M4 (32 GB)~122 tok/sMacBook Air 13" M4 (16 GB)~122 tok/sMacBook Air 13" M4 (24 GB)~122 tok/sMacBook Air 15" M4 (16 GB)~122 tok/sMacBook Air 15" M4 (24 GB)~122 tok/sMacBook Pro 14" M4 (16 GB)~122 tok/siPad Pro M4 13" (16 GB)~122 tok/sMacBook Air 13" M3 (16 GB)~104 tok/sMacBook Air 13" M3 (24 GB)~104 tok/sMacBook Air 13" M3 (8 GB)~104 tok/sIntel Core Ultra 9 288V (Lunar Lake) Laptop~99 tok/sNVIDIA Jetson Orin NX 16GB~97 tok/sNVIDIA Jetson Orin Nano 8GB (Super)~96 tok/sAMD Ryzen AI 9 HX 370 (Strix Point) Laptop~96 tok/sApple iPhone 17 Pro~78 tok/siPhone 17 Pro Max~78 tok/siPhone 17~69 tok/siPhone Air~69 tok/siPhone 15 ProiPhone 15 Pro MaxiPhone 16 ProiPhone 16 Pro Max

Related Models

Frequently Asked Questions

How much VRAM does Falcon H1 0.5B Instruct need?

Falcon H1 0.5B Instruct requires 0.7 GB of VRAM at Q4_K_M, or 1.4 GB at BF16. Full 16K context adds up to 0.5 GB (1.2 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 521M × 4.8 bits ÷ 8 = 0.3 GB

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

KV Cache + Overhead 0.9 GB (at full 16K context)

VRAM usage by quantization

0.7 GB
1.2 GB

Learn more about VRAM estimation →

What's the best quantization for Falcon H1 0.5B Instruct?

For Falcon H1 0.5B Instruct, Q4_K_M (0.7 GB) offers the best balance of quality and VRAM usage. Q5_K_M (0.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 0.6 GB.

VRAM requirement by quantization

Q2_K
0.6 GB
Q4_K_M
0.7 GB
Q5_K_M
0.8 GB
Q6_K
0.8 GB
Q8_0
0.9 GB
BF16
1.4 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Falcon H1 0.5B Instruct on a Mac?

Falcon H1 0.5B Instruct requires at least 0.6 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 Falcon H1 0.5B Instruct locally?

Yes — Falcon H1 0.5B Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 0.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Falcon H1 0.5B Instruct?

At Q4_K_M, Falcon H1 0.5B Instruct can reach ~6377 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~950 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 ÷ 0.7 × 0.65 = ~7536 tok/s

Estimated speed at Q4_K_M (0.7 GB)

~7536 tok/s
~950 tok/s
~7536 tok/s
~6377 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 Falcon H1 0.5B Instruct?

At Q4_K_M, the download is about 0.31 GB. The full-precision BF16 version is 1.04 GB. The smallest option (Q2_K) is 0.22 GB.

Which GPUs can run Falcon H1 0.5B Instruct?

50 consumer GPUs can run Falcon H1 0.5B Instruct at Q4_K_M (0.7 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 Falcon H1 0.5B Instruct?

59 devices with unified memory can run Falcon H1 0.5B Instruct at Q4_K_M (0.7 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.