Functiongemma 270M Ft Mobile Actions — Hardware Requirements & GPU Compatibility
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Functiongemma 270M Ft Mobile Actions is a 270M-parameter open language model from litert-community in the Gemma family. At BF16 it needs about 0.59 GB of VRAM — see which GPUs and Macs can run it below.
764 downloads
129 likesSpecifications
- Publisher
- litert-community
- Family
- Gemma
- Parameters
- 270M
- Release Date
- 2026-02-25
- License
- Gemma Terms
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How Much VRAM Does Functiongemma 270M Ft Mobile Actions Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 0.6 GB | — | 0.54 GB | Brain floating point 16 — preferred for training |
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 Functiongemma 270M Ft Mobile Actions?
BF16 · 0.6 GBFunctiongemma 270M Ft Mobile Actions (BF16) requires 0.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1+ GB is recommended. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Functiongemma 270M Ft Mobile Actions?
BF16 · 0.6 GB59 devices with unified memory can run Functiongemma 270M Ft Mobile Actions, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Functiongemma 270M Ft Mobile Actions need?
Functiongemma 270M Ft Mobile Actions requires 0.6 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 270M × 16 bits ÷ 8 = 0.5 GB
KV Cache + Overhead ≈ 0.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF160.6 GB- Can I run Functiongemma 270M Ft Mobile Actions on a Mac?
Functiongemma 270M Ft Mobile Actions requires at least 0.6 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 Functiongemma 270M Ft Mobile Actions locally?
Yes — Functiongemma 270M Ft Mobile Actions can run locally on consumer hardware. At BF16 quantization it needs 0.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Functiongemma 270M Ft Mobile Actions?
At BF16, Functiongemma 270M Ft Mobile Actions can reach ~7458 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~1111 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 B200 → 8000 ÷ 0.6 × 0.65 = ~8814 tok/s
Estimated speed at BF16 (0.6 GB)
~8814 tok/s~1111 tok/s~8814 tok/s~7458 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Functiongemma 270M Ft Mobile Actions?
At BF16, the download is about 0.54 GB.
- Which GPUs can run Functiongemma 270M Ft Mobile Actions?
50 consumer GPUs can run Functiongemma 270M Ft Mobile Actions at BF16 (0.6 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 Functiongemma 270M Ft Mobile Actions?
59 devices with unified memory can run Functiongemma 270M Ft Mobile Actions at BF16 (0.6 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.