Can I run Gemma 3 27B locally?
Gemma 3 27B has 27.43 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 18.8 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2025-03-01. This is an older model; see the current list for newer options.
Memory needed by quantization
| Quant | Weights | Total needed (est.) |
|---|---|---|
| IQ1_S | 5.3 GB | 7.0 GB |
| IQ2_XXS | 7.1 GB | 8.8 GB |
| IQ2_M | 9.3 GB | 11.1 GB |
| Q2_K | 10.9 GB | 12.8 GB |
| IQ3_XXS | 10.5 GB | 12.4 GB |
| Q3_K_S | 12.5 GB | 14.5 GB |
| IQ3_M | 12.6 GB | 14.5 GB |
| Q3_K_M | 13.7 GB | 15.8 GB |
| IQ4_XS | 14.6 GB | 16.7 GB |
| Q4_0 | 15.4 GB | 17.6 GB |
| Q4_K_M | 16.6 GB | 18.8 GB |
| MXFP4 | 15.9 GB | 18.0 GB |
| Q5_K_M | 19.5 GB | 21.9 GB |
| Q6_K | 22.5 GB | 25.0 GB |
| Q8_0 | 29.1 GB | 32.0 GB |
| F16 | 54.9 GB | 59.0 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.77 GB | 0.41 GB | 0.22 GB |
| 8k | 1.11 GB | 0.59 GB | 0.31 GB |
| 16k | 1.78 GB | 0.94 GB | 0.50 GB |
| 32k | 3.12 GB | 1.66 GB | 0.88 GB |
| 64k | 5.80 GB | 3.08 GB | 1.63 GB |
| 128k | 11.17 GB | 5.94 GB | 3.14 GB |
From config.json: 10 KV-caching attention layers, 16 KV heads × 128 head dim, plus 52 sliding-window layers (1024 tokens). Max context 128k. The tables above assume 4k context.
Which GPUs and Macs can run it?
✅ fits · ⚠️ fits with little headroom · ❌ doesn't fit on this one device (multiple GPUs or RAM offload may work; check your setup). Apple Silicon assumes macOS lets the GPU use ~67–75% of unified memory. All fit verdicts are estimates.
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