Gemma 4 2B vs Gemma 3 27B
Side-by-side specs, benchmarks, and a verdict by use case.
Updated 2026-07-13
| Spec | Gemma 4 2B | Gemma 3 27B |
|---|---|---|
| Parameters | 2B | 27B |
| Author | ||
| License | Gemma | Gemma |
| Context window | 0k | 0k |
| VRAM at Q4 | 1.2 GB | 16 GB |
| VRAM at Q5 | 1.4 GB | 19 GB |
| VRAM at Q8 | 2.1 GB | 29 GB |
| VRAM at FP16 | 4 GB | 54 GB |
| Use cases | chat, vision, multilingual, small | chat, general, vision, multilingual |
Verdict
Gemma 3 27B is significantly larger (27B vs 2B), so expect higher quality but heavier VRAM and slower throughput.
The two models at a glance
About Gemma 4 2B
Google's 2B base model in the Gemma 4 family with text and image input, 128k context, and a 1.2GB Q4 footprint that runs on integrated graphics or a Raspberry Pi 5. Strengths: Runs on integrated GPUs at ~1.2GB VRAM in Q4, Multimodal text and image input out of the box, 128k context unusual at this parameter count, Permissive Gemma license.
About Gemma 3 27B
Google's flagship Gemma 3 at 27B — multimodal, 128K context, and an LMArena Elo of 1338 that beats Llama 3.1 405B at 15x smaller. Sets the bar for open chat under 30B. Strengths: LMArena Elo 1338 — beats Llama 3.1 405B at 15x smaller, Multimodal with vision input, 128K context window, 140 language coverage.
How they compare
Gemma 4 2B comes from Google and Gemma 3 27B from Google. This comparison is built entirely from structured specs — parameter count, VRAM by quantization, context window, license, and published benchmark scores — so the verdict below reflects measurable differences rather than marketing claims.
At 2B vs 27B parameters, Gemma 3 27B is the larger of the two. At Q4, Gemma 4 2B fits in about 1.2 GB of VRAM versus 16 GB for the other — a 14.8 GB difference that matters on consumer GPUs.
The two models target different sweet spots: Gemma 4 2B is tuned for chat, vision, multilingual, small, while Gemma 3 27B leans toward chat, general, vision, multilingual. Match the model to your dominant workload rather than to raw size.
On a typical mid-range GPU, Gemma 4 2B pushes roughly 100 tokens/sec versus 13, so it is the more responsive choice for interactive or high-volume use.
Memory, quantization & throughput
Across quantization levels, Gemma 4 2B requires Q4 ≈ 1.2 GB, Q5 ≈ 1.4 GB, Q8 ≈ 2.1 GB, FP16 ≈ 4 GB, while Gemma 3 27B requires Q4 ≈ 16 GB, Q5 ≈ 19 GB, Q8 ≈ 29 GB, FP16 ≈ 54 GB. In practice Gemma 4 2B fits an 8 GB card at Q4, so plan your GPU around the Q4 or Q5 figure unless you specifically need the higher fidelity of Q8 or FP16.
Without a GPU, Gemma 4 2B needs roughly 2.6 GB of system RAM to run on CPU and Gemma 3 27B about 28 GB — workable for offline use but far slower than GPU inference. On a mid-range GPU you can expect on the order of 100 tokens/sec from Gemma 4 2B and 13 from Gemma 3 27B, scaling up to 200 and 32 tokens/sec on high-end hardware.
Which fits your GPU
Here is the highest-quality quantization of each model that fits common GPU memory budgets, so you can match Gemma 4 2B or Gemma 3 27B to the card you actually own:
- On a 8 GB GPU: Gemma 4 2B runs at FP16 (4 GB); Gemma 3 27B does not fit.
- On a 12 GB GPU: Gemma 4 2B runs at FP16 (4 GB); Gemma 3 27B does not fit.
- On a 16 GB GPU: Gemma 4 2B runs at FP16 (4 GB); Gemma 3 27B runs at Q4 (16 GB).
- On a 24 GB GPU: Gemma 4 2B runs at FP16 (4 GB); Gemma 3 27B runs at Q5 (19 GB).
Benchmark scores
Reported benchmarks for Gemma 3 27B: LMArena Elo 73, MMLU 78.6, MMLU-Pro 67.5, MATH 89.
Bottom line: which should you pick?
- Pick Gemma 4 2B for lower VRAM and faster inference; pick Gemma 3 27B for maximum headline quality.
- Pick Gemma 4 2B if your workload is small.
- Pick Gemma 3 27B if your workload is general.
Which GPU should you buy to run Gemma 3 27B?
To run Gemma 3 27B locally at Q4, you need ~16 GB of VRAM. The best value for this is a RTX 5070 Ti (16 GB VRAM).
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Frequently asked questions
What is the difference between Gemma 4 2B and Gemma 3 27B?
The headline differences: Gemma 4 2B is a 2B model and Gemma 3 27B is 27B. Below we break down VRAM by quantization, benchmark scores, and a use-case verdict so you can pick the right one.
Can Gemma 4 2B and Gemma 3 27B run on a 24 GB GPU?
At a Q4 quantization, Gemma 4 2B needs about 1.2 GB of VRAM and fits comfortably on a 24 GB GPU; Gemma 3 27B needs about 16 GB and fits comfortably on a 24 GB GPU. Gemma 4 2B is the lighter option for tight VRAM budgets.
Which is faster, Gemma 4 2B or Gemma 3 27B?
Gemma 4 2B is the smaller model (2B vs 27B), so on the same hardware it runs faster and uses less memory. The larger model trades speed for headline quality.
What licenses do Gemma 4 2B and Gemma 3 27B use?
Gemma 4 2B is licensed under Gemma and Gemma 3 27B under Gemma.