TII UAE·Falcon·FalconH1ForCausalLM

Falcon H1 Tiny 90M Instruct — Hardware Requirements & GPU Compatibility

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Falcon H1 Tiny 90M Instruct is a 91M-parameter open language model from TII UAE in the Falcon family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 0.38 GB of VRAM — see which GPUs and Macs can run it below.

1.6K downloads 47 likes262K context

Specifications

Publisher
TII UAE
Family
Falcon
Parameters
91M
Architecture
FalconH1ForCausalLM
Context Length
262,144 tokens
Vocabulary Size
32,768
Release Date
2026-01-12
License
Other

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How Much VRAM Does Falcon H1 Tiny 90M Instruct Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.400.4 GB
Q3_K_Mest.3.900.4 GB
Q4_K_Mest.4.800.4 GB
Q5_K_Mest.5.700.4 GB
Q6_Kest.6.600.4 GB
Q8_0est.8.000.4 GB
BF16est.16.000.5 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 Tiny 90M Instruct?

Q4_K_M · 0.4 GB

Falcon H1 Tiny 90M Instruct (Q4_K_M) requires 0.4 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 262K context window can add up to 3.2 GB, bringing total usage to 3.6 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Runs great

Plenty of headroom
NVIDIA GeForce RTX 5090~3065 tok/sNVIDIA GeForce RTX 3090 Ti~1724 tok/sNVIDIA GeForce RTX 4090~1724 tok/sNVIDIA GeForce RTX 5080~1642 tok/sNVIDIA GeForce RTX 3090~1601 tok/sNVIDIA GeForce RTX 3080 Ti~1561 tok/sNVIDIA GeForce RTX 5070 Ti~1533 tok/sNVIDIA GeForce RTX 5090 Laptop GPU~1533 tok/sAMD Radeon RX 7900 XTX~1516 tok/sNVIDIA GeForce RTX 3080~1301 tok/sAMD Radeon RX 7900 XT~1263 tok/sNVIDIA GeForce RTX 4080 SUPER~1259 tok/sNVIDIA GeForce RTX 4080~1226 tok/sNVIDIA GeForce RTX 4070 Ti SUPER~1150 tok/sNVIDIA GeForce RTX 5070~1150 tok/sNVIDIA TITAN RTX~1150 tok/sNVIDIA GeForce RTX 2080 Ti~1054 tok/sNVIDIA GeForce RTX 3070 Ti~1041 tok/sAMD Radeon RX 9070~1011 tok/sAMD Radeon RX 9070 XT~1011 tok/sAMD Radeon RX 7800 XT~985 tok/sNVIDIA GeForce RTX 4090 Laptop GPU~985 tok/sAMD Radeon RX 7900 GRE~910 tok/sNVIDIA GeForce RTX 4070~862 tok/sNVIDIA GeForce RTX 4070 SUPER~862 tok/sNVIDIA GeForce RTX 4070 Ti~862 tok/sNVIDIA GeForce GTX 1080 Ti~829 tok/sAMD Radeon RX 6800~808 tok/sAMD Radeon RX 6800 XT~808 tok/sAMD Radeon RX 6900 XT~808 tok/sNVIDIA GeForce RTX 3060 Ti~766 tok/sNVIDIA GeForce RTX 3070~766 tok/sNVIDIA GeForce RTX 5060~766 tok/sNVIDIA GeForce RTX 5060 Ti 16GB~766 tok/sNVIDIA GeForce RTX 5060 Ti 8GB~766 tok/sIntel Arc A770 16GB~737 tok/sAMD Radeon RX 7700 XT~682 tok/sIntel Arc A750~674 tok/sNVIDIA GeForce RTX 3060 12GB~616 tok/sAMD Radeon RX 6700 XT~606 tok/sIntel Arc B580~600 tok/sAMD Radeon RX 9060 XT 16GB~505 tok/sIntel Arc B570~500 tok/sNVIDIA GeForce RTX 4060 Ti 16GB~493 tok/sNVIDIA GeForce RTX 4060 Ti 8GB~493 tok/sNVIDIA GeForce RTX 4060~465 tok/sAMD Radeon RX 7600~455 tok/sAMD Radeon RX 7600 XT~455 tok/sNVIDIA GeForce RTX 3060 8GB~411 tok/sNVIDIA GeForce RTX 3050 8GB~383 tok/s

Which Devices Can Run Falcon H1 Tiny 90M Instruct?

Q4_K_M · 0.4 GB

59 devices with unified memory can run Falcon H1 Tiny 90M Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.

Runs great

Plenty of headroom
NVIDIA DGX H100~45842 tok/sNVIDIA DGX A100 640GB~27902 tok/sMac Studio (M3 Ultra, 256GB)~1509 tok/sMac Studio (M3 Ultra, 512GB)~1509 tok/sMac Studio (M3 Ultra, 96GB)~1509 tok/sMac Pro M2 Ultra (192 GB)~1474 tok/sMac Studio M2 Ultra (192 GB)~1474 tok/sMacBook Pro 16" M5 Max (128 GB)~1131 tok/sMac Studio M4 Max (128 GB)~1006 tok/sMac Studio M4 Max (64 GB)~1006 tok/sMacBook Pro 16" M4 Max (48 GB)~1006 tok/sMacBook Pro 16" M4 Max (64 GB)~1006 tok/sMac Studio M4 Max (36 GB)~755 tok/sMacBook Pro 14" M4 Max (36 GB)~755 tok/sMacBook Pro 16" M3 Max (48 GB)~755 tok/sMacBook Pro 14-inch (M5 Pro)~566 tok/sMac Mini M4 Pro (24 GB)~503 tok/sMac Mini M4 Pro (48 GB)~503 tok/sMacBook Pro 14" M4 Pro (24 GB)~503 tok/sMacBook Pro 16" M4 Pro (24 GB)~503 tok/sASUS Ascent GX10~467 tok/sNVIDIA DGX Spark~467 tok/sNVIDIA Jetson AGX Thor Developer Kit~467 tok/sAsus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB)~438 tok/sBeelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB)~438 tok/sFramework Desktop (Ryzen AI Max+ 395, 128 GB)~438 tok/sGMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB)~438 tok/sHP Z2 Mini G1a (Ryzen AI Max+ PRO 395, 128 GB)~438 tok/sHP ZBook Ultra G1a 14 (Ryzen AI Max+ PRO 395, 128 GB)~438 tok/sMinisforum MS-S1 MAX (Ryzen AI Max+ 395, 128 GB)~438 tok/sSnapdragon X2 Elite Extreme Copilot+ PC~390 tok/sNVIDIA Jetson AGX Orin 32GB~350 tok/sNVIDIA Jetson AGX Orin 64GB~350 tok/sMacBook Pro 14-inch (M5)~283 tok/siPad Pro M5 13" (16 GB)~282 tok/sSnapdragon X Elite Copilot+ PC~231 tok/sMac Mini M4 (16 GB)~221 tok/sMac Mini M4 (32 GB)~221 tok/sMacBook Air 13" M4 (16 GB)~221 tok/sMacBook Air 13" M4 (24 GB)~221 tok/sMacBook Air 15" M4 (16 GB)~221 tok/sMacBook Air 15" M4 (24 GB)~221 tok/sMacBook Pro 14" M4 (16 GB)~221 tok/siPad Pro M4 13" (16 GB)~221 tok/sAMD Ryzen AI 9 HX 370 (Strix Point) Laptop~190 tok/sMacBook Air 13" M3 (16 GB)~189 tok/sMacBook Air 13" M3 (24 GB)~189 tok/sMacBook Air 13" M3 (8 GB)~189 tok/sIntel Core Ultra 9 288V (Lunar Lake) Laptop~180 tok/sNVIDIA Jetson Orin NX 16GB~175 tok/sNVIDIA Jetson Orin Nano 8GB (Super)~175 tok/sApple iPhone 17 Pro~142 tok/siPhone 17 Pro Max~142 tok/siPhone 17~126 tok/siPhone Air~126 tok/siPhone 15 ProiPhone 15 Pro MaxiPhone 16 ProiPhone 16 Pro Max

Related Models

Frequently Asked Questions

How much VRAM does Falcon H1 Tiny 90M Instruct need?

Falcon H1 Tiny 90M Instruct requires 0.4 GB of VRAM at Q4_K_M, or 0.5 GB at BF16. Full 262K context adds up to 3.2 GB (3.6 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 91M × 4.8 bits ÷ 8 = 0.1 GB

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

KV Cache + Overhead 3.5 GB (at full 262K context)

VRAM usage by quantization

0.4 GB
3.6 GB

Learn more about VRAM estimation →

What's the best quantization for Falcon H1 Tiny 90M Instruct?

For Falcon H1 Tiny 90M Instruct, Q4_K_M (0.4 GB) offers the best balance of quality and VRAM usage. Q5_K_M (0.4 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 0.4 GB.

VRAM requirement by quantization

Q2_K
0.4 GB
Q4_K_M
0.4 GB
Q5_K_M
0.4 GB
Q6_K
0.4 GB
Q8_0
0.4 GB
BF16
0.5 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Falcon H1 Tiny 90M Instruct on a Mac?

Falcon H1 Tiny 90M Instruct requires at least 0.4 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 Tiny 90M Instruct locally?

Yes — Falcon H1 Tiny 90M Instruct can run locally on consumer hardware. At Q4_K_M quantization it needs 0.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Falcon H1 Tiny 90M Instruct?

At Q4_K_M, Falcon H1 Tiny 90M Instruct can reach ~12632 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~1724 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 ÷ 0.4 × 0.65 = ~13684 tok/s

Estimated speed at Q4_K_M (0.4 GB)

~13684 tok/s
~1724 tok/s
~13684 tok/s
~12632 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 Tiny 90M Instruct?

At Q4_K_M, the download is about 0.05 GB. The full-precision BF16 version is 0.18 GB. The smallest option (Q2_K) is 0.04 GB.

Which GPUs can run Falcon H1 Tiny 90M Instruct?

50 consumer GPUs can run Falcon H1 Tiny 90M Instruct at Q4_K_M (0.4 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 Tiny 90M Instruct?

59 devices with unified memory can run Falcon H1 Tiny 90M Instruct at Q4_K_M (0.4 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.