nickprock·Gemma 3·Gemma3ForCausalLM

Gemma3 1B CulturaViva ITA — Hardware Requirements & GPU Compatibility

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Gemma3 1B CulturaViva ITA is a 1000M-parameter open language model from nickprock in the Gemma 3 family. It supports a context window of up to 32,768 tokens. At Q4_K_M it needs about 0.96 GB of VRAM — see which GPUs and Macs can run it below.

356 downloads 3 likes33K context
Based on Gemma 3 1B IT

Specifications

Publisher
nickprock
Family
Gemma 3
Parameters
1000M
Architecture
Gemma3ForCausalLM
Context Length
32,768 tokens
Vocabulary Size
262,144
Release Date
2026-03-01
License
Apache 2.0

Get Started

How Much VRAM Does Gemma3 1B CulturaViva ITA Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.400.8 GB
Q3_K_Mest.3.900.8 GB
Q4_K_Mest.4.801.0 GB
Q5_K_Mest.5.701.1 GB
Q6_Kest.6.601.2 GB
Q8_0est.8.001.4 GB
BF16est.16.002.4 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 Gemma3 1B CulturaViva ITA?

Q4_K_M · 1.0 GB

Gemma3 1B CulturaViva ITA (Q4_K_M) requires 1.0 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 33K context window can add up to 0.9 GB, bringing total usage to 1.9 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Runs great

Plenty of headroom
NVIDIA GeForce RTX 5090~1213 tok/sNVIDIA GeForce RTX 3090 Ti~683 tok/sNVIDIA GeForce RTX 4090~683 tok/sNVIDIA GeForce RTX 5080~650 tok/sNVIDIA GeForce RTX 3090~634 tok/sNVIDIA GeForce RTX 3080 Ti~618 tok/sNVIDIA GeForce RTX 5070 Ti~607 tok/sNVIDIA GeForce RTX 5090 Laptop GPU~607 tok/sAMD Radeon RX 7900 XTX~550 tok/sNVIDIA GeForce RTX 3080~515 tok/sNVIDIA GeForce RTX 4080 SUPER~498 tok/sNVIDIA GeForce RTX 4080~485 tok/sAMD Radeon RX 7900 XT~458 tok/sNVIDIA GeForce RTX 4070 Ti SUPER~455 tok/sNVIDIA GeForce RTX 5070~455 tok/sNVIDIA TITAN RTX~455 tok/sNVIDIA GeForce RTX 2080 Ti~417 tok/sNVIDIA GeForce RTX 3070 Ti~412 tok/sNVIDIA GeForce RTX 4090 Laptop GPU~390 tok/sAMD Radeon RX 9070~367 tok/sAMD Radeon RX 9070 XT~367 tok/sAMD Radeon RX 7800 XT~358 tok/sNVIDIA GeForce RTX 4070~341 tok/sNVIDIA GeForce RTX 4070 SUPER~341 tok/sNVIDIA GeForce RTX 4070 Ti~341 tok/sAMD Radeon RX 7900 GRE~330 tok/sNVIDIA GeForce GTX 1080 Ti~328 tok/sNVIDIA GeForce RTX 3060 Ti~303 tok/sNVIDIA GeForce RTX 3070~303 tok/sNVIDIA GeForce RTX 5060~303 tok/sNVIDIA GeForce RTX 5060 Ti 16GB~303 tok/sNVIDIA GeForce RTX 5060 Ti 8GB~303 tok/sAMD Radeon RX 6800~293 tok/sAMD Radeon RX 6800 XT~293 tok/sAMD Radeon RX 6900 XT~293 tok/sIntel Arc A770 16GB~292 tok/sIntel Arc A750~267 tok/sAMD Radeon RX 7700 XT~248 tok/sNVIDIA GeForce RTX 3060 12GB~244 tok/sIntel Arc B580~238 tok/sAMD Radeon RX 6700 XT~220 tok/sIntel Arc B570~198 tok/sNVIDIA GeForce RTX 4060 Ti 16GB~195 tok/sNVIDIA GeForce RTX 4060 Ti 8GB~195 tok/sNVIDIA GeForce RTX 4060~184 tok/sAMD Radeon RX 9060 XT 16GB~183 tok/sAMD Radeon RX 7600~165 tok/sAMD Radeon RX 7600 XT~165 tok/sNVIDIA GeForce RTX 3060 8GB~163 tok/sNVIDIA GeForce RTX 3050 8GB~152 tok/s

Which Devices Can Run Gemma3 1B CulturaViva ITA?

Q4_K_M · 1.0 GB

59 devices with unified memory can run Gemma3 1B CulturaViva ITA, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.

Runs great

Plenty of headroom
NVIDIA DGX H100~18146 tok/sNVIDIA DGX A100 640GB~11045 tok/sMac Studio (M3 Ultra, 256GB)~597 tok/sMac Studio (M3 Ultra, 512GB)~597 tok/sMac Studio (M3 Ultra, 96GB)~597 tok/sMac Pro M2 Ultra (192 GB)~583 tok/sMac Studio M2 Ultra (192 GB)~583 tok/sMacBook Pro 16" M5 Max (128 GB)~448 tok/sMac Studio M4 Max (128 GB)~398 tok/sMac Studio M4 Max (64 GB)~398 tok/sMacBook Pro 16" M4 Max (48 GB)~398 tok/sMacBook Pro 16" M4 Max (64 GB)~398 tok/sMac Studio M4 Max (36 GB)~299 tok/sMacBook Pro 14" M4 Max (36 GB)~299 tok/sMacBook Pro 16" M3 Max (48 GB)~299 tok/sMacBook Pro 14-inch (M5 Pro)~224 tok/sMac Mini M4 Pro (24 GB)~199 tok/sMac Mini M4 Pro (48 GB)~199 tok/sMacBook Pro 14" M4 Pro (24 GB)~199 tok/sMacBook Pro 16" M4 Pro (24 GB)~199 tok/sASUS Ascent GX10~185 tok/sNVIDIA DGX Spark~185 tok/sNVIDIA Jetson AGX Thor Developer Kit~185 tok/sAsus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB)~173 tok/sBeelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB)~173 tok/sFramework Desktop (Ryzen AI Max+ 395, 128 GB)~173 tok/sGMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB)~173 tok/sHP Z2 Mini G1a (Ryzen AI Max+ PRO 395, 128 GB)~173 tok/sHP ZBook Ultra G1a 14 (Ryzen AI Max+ PRO 395, 128 GB)~173 tok/sMinisforum MS-S1 MAX (Ryzen AI Max+ 395, 128 GB)~173 tok/sSnapdragon X2 Elite Extreme Copilot+ PC~154 tok/sNVIDIA Jetson AGX Orin 32GB~139 tok/sNVIDIA Jetson AGX Orin 64GB~139 tok/sMacBook Pro 14-inch (M5)~112 tok/siPad Pro M5 13" (16 GB)~112 tok/sSnapdragon X Elite Copilot+ PC~91 tok/sMac Mini M4 (16 GB)~88 tok/sMac Mini M4 (32 GB)~88 tok/sMacBook Air 13" M4 (16 GB)~88 tok/sMacBook Air 13" M4 (24 GB)~88 tok/sMacBook Air 15" M4 (16 GB)~88 tok/sMacBook Air 15" M4 (24 GB)~88 tok/sMacBook Pro 14" M4 (16 GB)~88 tok/siPad Pro M4 13" (16 GB)~88 tok/sMacBook Air 13" M3 (16 GB)~75 tok/sMacBook Air 13" M3 (24 GB)~75 tok/sMacBook Air 13" M3 (8 GB)~75 tok/sIntel Core Ultra 9 288V (Lunar Lake) Laptop~71 tok/sNVIDIA Jetson Orin NX 16GB~69 tok/sNVIDIA Jetson Orin Nano 8GB (Super)~69 tok/sAMD Ryzen AI 9 HX 370 (Strix Point) Laptop~69 tok/sApple iPhone 17 Pro~56 tok/siPhone 17 Pro Max~56 tok/siPhone 17~50 tok/siPhone Air~50 tok/siPhone 15 ProiPhone 15 Pro MaxiPhone 16 ProiPhone 16 Pro Max

Related Models

Frequently Asked Questions

How much VRAM does Gemma3 1B CulturaViva ITA need?

Gemma3 1B CulturaViva ITA requires 1.0 GB of VRAM at Q4_K_M, or 2.4 GB at BF16. Full 33K context adds up to 0.9 GB (1.9 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 1000M × 4.8 bits ÷ 8 = 0.6 GB

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

KV Cache + Overhead 1.3 GB (at full 33K context)

VRAM usage by quantization

1.0 GB
1.9 GB

Learn more about VRAM estimation →

What's the best quantization for Gemma3 1B CulturaViva ITA?

For Gemma3 1B CulturaViva ITA, Q4_K_M (1.0 GB) offers the best balance of quality and VRAM usage. Q5_K_M (1.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 0.8 GB.

VRAM requirement by quantization

Q2_K
0.8 GB
Q4_K_M
1.0 GB
Q5_K_M
1.1 GB
Q6_K
1.2 GB
Q8_0
1.4 GB
BF16
2.4 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Gemma3 1B CulturaViva ITA on a Mac?

Gemma3 1B CulturaViva ITA requires at least 0.8 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 Gemma3 1B CulturaViva ITA locally?

Yes — Gemma3 1B CulturaViva ITA can run locally on consumer hardware. At Q4_K_M quantization it needs 1.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Gemma3 1B CulturaViva ITA?

At Q4_K_M, Gemma3 1B CulturaViva ITA can reach ~4583 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~683 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 ÷ 1.0 × 0.65 = ~5417 tok/s

Estimated speed at Q4_K_M (1.0 GB)

~5417 tok/s
~683 tok/s
~5417 tok/s
~4583 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 Gemma3 1B CulturaViva ITA?

At Q4_K_M, the download is about 0.60 GB. The full-precision BF16 version is 2.00 GB. The smallest option (Q2_K) is 0.42 GB.

Which GPUs can run Gemma3 1B CulturaViva ITA?

50 consumer GPUs can run Gemma3 1B CulturaViva ITA at Q4_K_M (1.0 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 Gemma3 1B CulturaViva ITA?

59 devices with unified memory can run Gemma3 1B CulturaViva ITA at Q4_K_M (1.0 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.