Qwen 3 8B vs Gemma 3 12B

The two models at a glance

About Qwen 3 8B

Alibaba's 8B dense model with a toggleable thinking mode and broad multilingual coverage. Punches well above its weight for an 8B and runs comfortably on a single consumer GPU. Strengths: Hybrid thinking/fast modes switchable per request, Strong multilingual performance across 119 languages, Up to 131K context via YaRN (32K native), Apache 2.0 — clean commercial use.

About Gemma 3 12B

The 12B sweet spot of Google's Gemma 3 line — multimodal, 128K context, and 140 languages. Fits on a single consumer GPU with room for batching. Strengths: Sweet spot for multimodal performance vs hardware cost, 128K context window, 140 language coverage, Strong general-purpose default.

How they compare

Qwen 3 8B comes from Alibaba and Gemma 3 12B from Google, they belong to the Qwen and Gemma families respectively. 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 8B vs 12B parameters, Gemma 3 12B is the larger of the two. At Q4, Qwen 3 8B fits in about 5 GB of VRAM versus 7 GB for the other — a 2 GB difference that matters on consumer GPUs.

The two models target different sweet spots: Qwen 3 8B is tuned for chat, general, reasoning, multilingual, while Gemma 3 12B leans toward chat, general, vision, multilingual. Match the model to your dominant workload rather than to raw size.

On a typical mid-range GPU, Qwen 3 8B pushes roughly 35 tokens/sec versus 22, so it is the more responsive choice for interactive or high-volume use. For long-context work, Qwen 3 8B offers the bigger window (128k vs 125k tokens).

Memory, quantization & throughput

Across quantization levels, Qwen 3 8B requires Q4 ≈ 5 GB, Q5 ≈ 6 GB, Q8 ≈ 9 GB, FP16 ≈ 16 GB, while Gemma 3 12B requires Q4 ≈ 7 GB, Q5 ≈ 9 GB, Q8 ≈ 13 GB, FP16 ≈ 24 GB. In practice Qwen 3 8B 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, Qwen 3 8B needs roughly 10 GB of system RAM to run on CPU and Gemma 3 12B about 14 GB — workable for offline use but far slower than GPU inference. On a mid-range GPU you can expect on the order of 35 tokens/sec from Qwen 3 8B and 22 from Gemma 3 12B, scaling up to 90 and 60 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 Qwen 3 8B or Gemma 3 12B to the card you actually own:

• On a 8 GB GPU: Qwen 3 8B runs at Q5 (6 GB); Gemma 3 12B runs at Q4 (7 GB).
• On a 12 GB GPU: Qwen 3 8B runs at Q8 (9 GB); Gemma 3 12B runs at Q5 (9 GB).
• On a 16 GB GPU: Qwen 3 8B runs at FP16 (16 GB); Gemma 3 12B runs at Q8 (13 GB).
• On a 24 GB GPU: Qwen 3 8B runs at FP16 (16 GB); Gemma 3 12B runs at FP16 (24 GB).

Benchmark scores

Reported benchmarks for Qwen 3 8B: MMLU-Pro 68.7, GPQA 60, LiveCodeBench 54.4.

Bottom line: which should you pick?

• Pick Qwen 3 8B if you need a permissive (Apache 2.0) license for commercial deployment.
• Pick Qwen 3 8B for long-context work (up to 128k tokens).
• Pick Qwen 3 8B for lower VRAM and faster inference; pick Gemma 3 12B for maximum headline quality.
• Pick Qwen 3 8B if your workload is reasoning.
• Pick Gemma 3 12B if your workload is vision.

Which GPU should you buy to run Gemma 3 12B?

To run Gemma 3 12B locally at Q4, you need ~7 GB of VRAM. The best value for this is a RTX 5060 (8 GB VRAM).

Frequently asked questions

What is the difference between Qwen 3 8B and Gemma 3 12B?

The headline differences: Qwen 3 8B is a 8B model and Gemma 3 12B is 12B; their context windows differ (128k vs 125k tokens); they ship under different licenses (Apache 2.0 vs Gemma). Below we break down VRAM by quantization, benchmark scores, and a use-case verdict so you can pick the right one.

Can Qwen 3 8B and Gemma 3 12B run on a 24 GB GPU?

At a Q4 quantization, Qwen 3 8B needs about 5 GB of VRAM and fits comfortably on a 24 GB GPU; Gemma 3 12B needs about 7 GB and fits comfortably on a 24 GB GPU. Qwen 3 8B is the lighter option for tight VRAM budgets.

Which is faster, Qwen 3 8B or Gemma 3 12B?

Qwen 3 8B is the smaller model (8B vs 12B), so on the same hardware it runs faster and uses less memory. The larger model trades speed for headline quality.

Which license is safer for commercial use, Qwen 3 8B or Gemma 3 12B?

Qwen 3 8B ships under Apache 2.0, a permissive license with no usage restrictions, whereas the other is under Gemma — check its terms before commercial deployment.

Which has the longer context window, Qwen 3 8B or Gemma 3 12B?

Qwen 3 8B has the larger context window (128k vs 125k tokens), so it handles longer documents and codebases in a single prompt.