Gemma3 1B IT — Hardware Requirements & GPU Compatibility
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Gemma3 1B IT is a 1B-parameter open language model from litert-community in the Gemma family. At BF16 it needs about 2.20 GB of VRAM — see which GPUs and Macs can run it below.
14.8K downloads
615 likesSpecifications
- Publisher
- litert-community
- Family
- Gemma
- Parameters
- 1B
- Release Date
- 2026-05-18
- License
- Gemma Terms
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HuggingFace
How Much VRAM Does Gemma3 1B IT Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 2.2 GB | — | 2.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Gemma3 1B IT?
BF16 · 2.2 GBGemma3 1B IT (BF16) requires 2.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Gemma3 1B IT?
BF16 · 2.2 GB33 devices with unified memory can run Gemma3 1B IT, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Gemma3 1B IT need?
Gemma3 1B IT requires 2.2 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 1B × 16 bits ÷ 8 = 2 GB
KV Cache + Overhead ≈ 0.2 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF162.2 GB- Can I run Gemma3 1B IT on a Mac?
Gemma3 1B IT requires at least 2.2 GB at BF16, 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 IT locally?
Yes — Gemma3 1B IT can run locally on consumer hardware. At BF16 quantization it needs 2.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma3 1B IT?
At BF16, Gemma3 1B IT can reach ~1325 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~298 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 2.2 × 0.55 = ~1325 tok/s
Estimated speed at BF16 (2.2 GB)
~1325 tok/s~298 tok/s~990 tok/s~819 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Gemma3 1B IT?
At BF16, the download is about 2.00 GB.
- Which GPUs can run Gemma3 1B IT?
35 consumer GPUs can run Gemma3 1B IT at BF16 (2.2 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Gemma3 1B IT?
33 devices with unified memory can run Gemma3 1B IT at BF16 (2.2 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.