Turkish Gemma 9B T1 — Hardware Requirements & GPU Compatibility
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Turkish Gemma 9B T1 is a 9B-parameter open language model from ytu-ce-cosmos in the Gemma family. It supports a context window of up to 8,192 tokens. At BF16 it needs about 18.92 GB of VRAM — see which GPUs and Macs can run it below.
5.4K downloads
166 likesSpecifications
- Publisher
- ytu-ce-cosmos
- Family
- Gemma
- Parameters
- 9B
- Architecture
- Gemma2ForCausalLM
- Context Length
- 8,192 tokens
- Vocabulary Size
- 256,000
- Release Date
- 2026-02-11
- License
- Gemma Terms
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HuggingFace
How Much VRAM Does Turkish Gemma 9B T1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 18.9 GB | 20.8 GB | 18.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Turkish Gemma 9B T1?
BF16 · 18.9 GBTurkish Gemma 9B T1 (BF16) requires 18.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 25+ GB is recommended. Using the full 8K context window can add up to 1.8 GB, bringing total usage to 20.8 GB. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Turkish Gemma 9B T1?
BF16 · 18.9 GB21 devices with unified memory can run Turkish Gemma 9B T1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Turkish Gemma 9B T1 need?
Turkish Gemma 9B T1 requires 18.9 GB of VRAM at BF16. Full 8K context adds up to 1.8 GB (20.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 9B × 16 bits ÷ 8 = 18 GB
KV Cache + Overhead ≈ 0.9 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 2.8 GB (at full 8K context)
VRAM usage by quantization
BF1618.9 GBBF16 + full context20.8 GB- Can I run Turkish Gemma 9B T1 on a Mac?
Turkish Gemma 9B T1 requires at least 18.9 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 Turkish Gemma 9B T1 locally?
Yes — Turkish Gemma 9B T1 can run locally on consumer hardware. At BF16 quantization it needs 18.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Turkish Gemma 9B T1?
At BF16, Turkish Gemma 9B T1 can reach ~154 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~35 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 ÷ 18.9 × 0.55 = ~154 tok/s
Estimated speed at BF16 (18.9 GB)
~154 tok/s~35 tok/s~115 tok/s~95 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Turkish Gemma 9B T1?
At BF16, the download is about 18.00 GB.
- Which GPUs can run Turkish Gemma 9B T1?
6 consumer GPUs can run Turkish Gemma 9B T1 at BF16 (18.9 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Turkish Gemma 9B T1?
21 devices with unified memory can run Turkish Gemma 9B T1 at BF16 (18.9 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.