Mistral Nemo 12B Instruct vs Gemma 3 12B
Side-by-side specs, benchmarks, and a verdict by use case.
Updated 2026-07-13
| Spec | Mistral Nemo 12B Instruct | Gemma 3 12B |
|---|---|---|
| Parameters | 12B | 12B |
| Author | Mistral AI | |
| License | Apache 2.0 | Gemma |
| Context window | 0k | 0k |
| VRAM at Q4 | 7 GB | 7 GB |
| VRAM at Q5 | 9 GB | 9 GB |
| VRAM at Q8 | 13 GB | 13 GB |
| VRAM at FP16 | 24 GB | 24 GB |
| Use cases | chat, general, multilingual, fr | chat, general, vision, multilingual |
Verdict
Both models sit in a similar size class. The pick depends on tags, license, and benchmarks rather than raw parameter count.
For unambiguous commercial use, Mistral Nemo 12B Instruct has the safer license (Apache 2.0) compared to Gemma.
The two models at a glance
About Mistral Nemo 12B Instruct
Mistral AI and NVIDIA's co-developed 12B instruct model with 128k context, the Tekken tokenizer, and strong European multilingual coverage. Strengths: 128k context window, Strong European multilingual performance, Apache 2.0 license, Efficient Tekken tokenizer reduces token counts.
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
Mistral Nemo 12B Instruct comes from Mistral AI and Gemma 3 12B from Google, they belong to the Mistral 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.
Mistral Nemo 12B Instruct and Gemma 3 12B share the same 12B parameter class. Both need about 7 GB of VRAM at a Q4 quantization, so they fit the same GPU tier.
The two models target different sweet spots: Mistral Nemo 12B Instruct is tuned for chat, general, multilingual, fr, 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, Mistral Nemo 12B Instruct pushes roughly 25 tokens/sec versus 22, so it is the more responsive choice for interactive or high-volume use.
Memory, quantization & throughput
Across quantization levels, Mistral Nemo 12B Instruct requires Q4 ≈ 7 GB, Q5 ≈ 9 GB, Q8 ≈ 13 GB, FP16 ≈ 24 GB, while Gemma 3 12B requires Q4 ≈ 7 GB, Q5 ≈ 9 GB, Q8 ≈ 13 GB, FP16 ≈ 24 GB. In practice Mistral Nemo 12B Instruct 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, Mistral Nemo 12B Instruct needs roughly 16 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 25 tokens/sec from Mistral Nemo 12B Instruct and 22 from Gemma 3 12B, scaling up to 70 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 Mistral Nemo 12B Instruct or Gemma 3 12B to the card you actually own:
- On a 8 GB GPU: Mistral Nemo 12B Instruct runs at Q4 (7 GB); Gemma 3 12B runs at Q4 (7 GB).
- On a 12 GB GPU: Mistral Nemo 12B Instruct runs at Q5 (9 GB); Gemma 3 12B runs at Q5 (9 GB).
- On a 16 GB GPU: Mistral Nemo 12B Instruct runs at Q8 (13 GB); Gemma 3 12B runs at Q8 (13 GB).
- On a 24 GB GPU: Mistral Nemo 12B Instruct runs at FP16 (24 GB); Gemma 3 12B runs at FP16 (24 GB).
Benchmark scores
Reported benchmarks for Mistral Nemo 12B Instruct: MMLU 68, HellaSwag 83.5, Winogrande 76.8.
Bottom line: which should you pick?
- Pick Mistral Nemo 12B Instruct if you need a permissive (Apache 2.0) license for commercial deployment.
- Pick Mistral Nemo 12B Instruct if your workload is fr.
- Pick Gemma 3 12B if your workload is vision.
Which GPU should you buy to run Mistral Nemo 12B Instruct?
To run Mistral Nemo 12B Instruct locally at Q4, you need ~7 GB of VRAM. The best value for this is a RTX 5060 (8 GB VRAM).
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Frequently asked questions
What is the difference between Mistral Nemo 12B Instruct and Gemma 3 12B?
The headline differences: both are 12B models; 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 Mistral Nemo 12B Instruct and Gemma 3 12B run on a 24 GB GPU?
At a Q4 quantization, Mistral Nemo 12B Instruct needs about 7 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. Both have the same Q4 footprint.
Which license is safer for commercial use, Mistral Nemo 12B Instruct or Gemma 3 12B?
Mistral Nemo 12B Instruct ships under Apache 2.0, a permissive license with no usage restrictions, whereas the other is under Gemma — check its terms before commercial deployment.