Gemma4 12B Mtp Assistant — Hardware Requirements & GPU Compatibility
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Gemma4 12B Mtp Assistant is a 12B-parameter open language model from sjakek in the Gemma family. At BF16 it needs about 26.40 GB of VRAM — see which GPUs and Macs can run it below.
2.6K downloads
3 likesSpecifications
- Publisher
- sjakek
- Family
- Gemma
- Parameters
- 12B
- Release Date
- 2026-06-03
- License
- Gemma Terms
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HuggingFace
How Much VRAM Does Gemma4 12B Mtp Assistant Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 26.4 GB | — | 24.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Gemma4 12B Mtp Assistant?
BF16 · 26.4 GBGemma4 12B Mtp Assistant (BF16) requires 26.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 35+ GB is recommended. 1 GPU can run it, including NVIDIA GeForce RTX 5090.
All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).
Decent
— Enough VRAM, may be tightWhich Devices Can Run Gemma4 12B Mtp Assistant?
BF16 · 26.4 GB15 devices with unified memory can run Gemma4 12B Mtp Assistant, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Gemma4 12B Mtp Assistant need?
Gemma4 12B Mtp Assistant requires 26.4 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 12B × 16 bits ÷ 8 = 24 GB
KV Cache + Overhead ≈ 2.4 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF1626.4 GB- Can I run Gemma4 12B Mtp Assistant on a Mac?
Gemma4 12B Mtp Assistant requires at least 26.4 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 Gemma4 12B Mtp Assistant locally?
Yes — Gemma4 12B Mtp Assistant can run locally on consumer hardware. At BF16 quantization it needs 26.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma4 12B Mtp Assistant?
At BF16, Gemma4 12B Mtp Assistant can reach ~110 tok/s on AMD Instinct MI300X. 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 ÷ 26.4 × 0.55 = ~110 tok/s
Estimated speed at BF16 (26.4 GB)
~110 tok/s~83 tok/s~68 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Gemma4 12B Mtp Assistant?
At BF16, the download is about 24.00 GB.
- Which GPUs can run Gemma4 12B Mtp Assistant?
1 consumer GPU can run Gemma4 12B Mtp Assistant at BF16 (26.4 GB). Top options include NVIDIA GeForce RTX 5090.
- Which devices can run Gemma4 12B Mtp Assistant?
15 devices with unified memory can run Gemma4 12B Mtp Assistant at BF16 (26.4 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.