Gemma 3 27BvsGemma 2 27B
Complete comparison between Gemma 3 27B (27B parameters, Google) and Gemma 2 27B (27B, Google). VRAM required by quantization, tokens per second measured on 4 reference GPUs, verdict by use case, license, and installation commands. All figures are calculated from the catalog data—no copy-pasting between pages.
In brief
| Feature | Gemma 3 27B | Gemma 2 27B |
|---|---|---|
| Settings | 27B | 27B |
| Family | Gemma | Gemma |
| Author | ||
| Origin | US | US |
| License | Gemma | Gemma |
| Context | 128,000 tokens | 8,192 tokens |
| Output | March 2025 | June 2024 |
Memory footprint
Approximate VRAM required for inference with an average context window. The winner (in green) is the model that uses less — smaller models have the edge.
| Quantization | Gemma 3 27B | Gemma 2 27B |
|---|---|---|
| Q4_K_M (lightweight) | 16 GB | 16 GB |
| Q5_K_M (balanced) | 19 GB | 19 GB |
| Q8 (near-lossless) | 29 GB | 29 GB |
| FP16 (max quality) | 54 GB | 54 GB |
| CPU-only RAM | 28 GB | 28 GB |
Estimated speed (tokens/second)
Estimates based on the best quantization that can fit on each GPU. Actual figures depend on the prompt, context, and engine (llama.cpp, vLLM, MLX). Methodology.
| Reference GPU | Gemma 3 27B | Gemma 2 27B |
|---|---|---|
| RTX 4090 (24 GB) | 32 tok/s · Q5_K_M | 32 tok/s · Q5_K_M |
| RTX 4080 (16 GB) | 13 tok/s · Q4_K_M | 13 tok/s · Q4_K_M |
| RTX 3060 12GB (12 GB) | ✗ too heavy | ✗ too heavy |
| Apple M4 Pro (48 GB) (36 GB) | 13 tok/s · Q8 | 13 tok/s · Q8 |
Verdict by use case
For each common use case, we indicate which of the two is better suited based on its tags, size, and specialization.
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Strengths and weaknesses
Gemma 3 27B
High-end Gemma. LMArena Elo 1338 — beats Llama 3.1 405B at 15× smaller size.
- LMArena Elo 1338: beats Llama 3.1 405B while being 15× smaller
- Multimodal
- 128k ctx
- License Gemma
- No thinking mode
Installation
Gemma 2 27B
The high-end Gemma. Excellent in French.
- Quality close to 70B
- 16 GB VRAM Q4 (accessible)
- Very good at instruction following
- 8192 context only — the major weakness
- Gemma license (not Apache 2.0)
Installation
Frequently asked questions
Which model runs best on RTX 4090 (24 GB): Gemma 3 27B or Gemma 2 27B?
On an RTX 4090, Gemma 3 27B runs at Q5_K_M (~32 tok/s), Gemma 2 27B in Q5_K_M (~32 tok/s). In pure throughput terms, Gemma 2 27B wins. See the configurator to test your exact GPU.
Which uses the least VRAM?
Both require the same VRAM in Q4 (16 GB). The choice then comes down to licensing or perceived quality.
Can these models be used in commercial production?
Gemma 3 27B is under Gemma — check the restrictions (especially the monthly user thresholds). Gemma 2 27B is under Gemma — also check the terms. For SaaS, prefer Apache 2.0 or MIT.
Which one should you choose in 2026?
Depends on your primary constraint. Smaller / faster: Gemma 3 27B (27B). More capable: Gemma 3 27B (27B). If you're unsure, run the configurator with your GPU and use case — it will decide based on both.
Alternatives to consider
If neither works for you, here are some neighboring models you could explore.