Gemma 3 270M IT ONNX — Hardware Requirements & GPU Compatibility
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1.9K downloads
26 likesSpecifications
- Publisher
- ONNX Community
- Family
- Gemma
- Parameters
- 270M
- Architecture
- Gemma3ForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-03-13
- License
- Gemma Terms
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HuggingFace
How Much VRAM Does Gemma 3 270M IT ONNX Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 0.4 GB | 0.8 GB | 0.11 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 0.4 GB | 0.8 GB | 0.12 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 0.5 GB | 0.8 GB | 0.13 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 0.5 GB | 0.8 GB | 0.14 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 0.5 GB | 0.8 GB | 0.16 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 0.5 GB | 0.9 GB | 0.19 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 0.6 GB | 0.9 GB | 0.22 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 0.6 GB | 0.9 GB | 0.27 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Gemma 3 270M IT ONNX?
Q4_K_M · 0.5 GBGemma 3 270M IT ONNX (Q4_K_M) requires 0.5 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 33K context window can add up to 0.4 GB, bringing total usage to 0.8 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Gemma 3 270M IT ONNX?
Q4_K_M · 0.5 GB33 devices with unified memory can run Gemma 3 270M IT ONNX, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Gemma 3 270M IT ONNX need?
Gemma 3 270M IT ONNX requires 0.5 GB of VRAM at Q4_K_M, or 0.6 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 270M × 4.8 bits ÷ 8 = 0.2 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 0.6 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M0.5 GBQ4_K_M + full context0.8 GB- What's the best quantization for Gemma 3 270M IT ONNX?
For Gemma 3 270M IT ONNX, Q4_K_M (0.5 GB) offers the best balance of quality and VRAM usage. Q5_K_S (0.5 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 0.4 GB.
VRAM requirement by quantization
IQ2_XXS0.4 GB~53%Q3_K_S0.4 GB~77%Q4_10.5 GB~88%Q4_K_M ★0.5 GB~89%Q5_K_S0.5 GB~92%Q8_00.6 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run Gemma 3 270M IT ONNX on a Mac?
Gemma 3 270M IT ONNX requires at least 0.4 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 Gemma 3 270M IT ONNX locally?
Yes — Gemma 3 270M IT ONNX can run locally on consumer hardware. At Q4_K_M quantization it needs 0.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma 3 270M IT ONNX?
At Q4_K_M, Gemma 3 270M IT ONNX can reach ~5949 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~1337 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 ÷ 0.5 × 0.55 = ~5949 tok/s
Estimated speed at Q4_K_M (0.5 GB)
AMD Instinct MI300X~5949 tok/sNVIDIA GeForce RTX 4090~1337 tok/sNVIDIA H100 SXM~4447 tok/sAMD Instinct MI250X~3678 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Gemma 3 270M IT ONNX?
At Q4_K_M, the download is about 0.16 GB. The full-precision Q8_0 version is 0.27 GB. The smallest option (IQ2_XXS) is 0.07 GB.
- Which GPUs can run Gemma 3 270M IT ONNX?
35 consumer GPUs can run Gemma 3 270M IT ONNX at Q4_K_M (0.5 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 Gemma 3 270M IT ONNX?
33 devices with unified memory can run Gemma 3 270M IT ONNX at Q4_K_M (0.5 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.