Gemma 7B
Gemma 7B is an open-weights language model from Google, released February 21, 2024. It has 7B parameters (dense). On the Epoch Capabilities Index it scores 103.3, rank 210 of 256 rated models.
Check it against your own PC →
Can you run Gemma 7B locally?
The smallest common GPU it runs on is 6 GB of VRAM (with 32 GB of RAM): Q6_K, split GPU / CPU, roughly 8 tokens per second. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Runs, slowly | Q6_K (≈ lossless) | 5.2 GB | 3.3 GB | ~8 |
| 8 GB VRAM | Runs on GPU | Q4_K_M (very good) | 7.0 GB | – | ~37 |
| 12 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 8.5 GB | – | ~36 |
| 16 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 8.5 GB | – | ~50 |
| 24 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 8.5 GB | – | ~89 |
| 32 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 8.5 GB | – | ~160 |
Benchmark results
| Benchmark (Epoch AI) | Score |
|---|---|
| MMLU | 54.8% |
Links
Models with a similar score
Falcon-180B · GPT-3.5 Turbo (Jun 2023) · Llama 2-70B · Mistral 7B v0.1 · Yi-9B · Qwen-14B · LLaMA-65B · DeepSeek-Coder-V2-Lite-Base
More from Google
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