Gemma 3 12B Instruct vs Mistral Nemo 12B Instruct
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Gemma 3 12B Instruct is more hardware-efficient — it needs 8.9 GB at Q4_K_M vs 9.2 GB for Mistral Nemo 12B Instruct, fitting on 105 GPUs natively.
VRAM at each quantization (8k context)
| Quant | Gemma 3 12B Instruct | Mistral Nemo 12B Instruct | Diff |
|---|---|---|---|
| FP32 | 55.8 GB | 56.2 GB | -1% |
| BF16 | 28.5 GB | 28.8 GB | -1% |
| FP16 | 28.5 GB | 28.8 GB | -1% |
| Q8_0 | 14.8 GB | 15.2 GB | -2% |
| Q6_K | 12.4 GB | 12.7 GB | -3% |
| Q5_K_M | 10.0 GB | 10.3 GB | -3% |
| Q4_K_M | 8.9 GB | 9.2 GB | -3% |
| Q3_K_M | 7.1 GB | 7.4 GB | -4% |
| Q2_K | 5.7 GB | 6.0 GB | -5% |
| NVFP4 | 8.0 GB | 8.3 GB | -4% |
Diff is Gemma 3 12B Instruct relative to Mistral Nemo 12B Instruct. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Gemma 3 12B Instruct | Mistral Nemo 12B Instruct |
|---|---|---|
| Org | Mistral AI | |
| Parameters | 12.2B | 12.2B |
| Architecture | Dense | Dense |
| Context | 128k tokens | 125k tokens |
| Modalities | text, vision | text |
| License | Gemma | Apache 2.0 |
| Commercial | Yes | Yes |
| Released | 2025-03-12 | 2024-07-18 |
| GPUs (native) | 105 / 107 | 102 / 107 |
Benchmark scores
| Benchmark | Gemma 3 12B Instruct | Mistral Nemo 12B Instruct |
|---|---|---|
| MMLU-Pro | 60.6 | 35.6 |
Green = higher score (better). — = not yet available.
GPUs that run only Gemma 3 12B Instruct(3)
GPUs that run only Mistral Nemo 12B Instruct(0)
Every GPU that runs Mistral Nemo 12B Instruct also runs Gemma 3 12B Instruct.
GPUs that run both natively(102)
- NVIDIA RTX 509032 GB
- NVIDIA RTX 508016 GB
- NVIDIA RTX 5070 Ti16 GB
- NVIDIA RTX 507012 GB
- NVIDIA RTX 5060 Ti 16GB16 GB
- NVIDIA RTX 50608 GB
- NVIDIA RTX 50508 GB
- NVIDIA RTX 409024 GB
- NVIDIA RTX 408016 GB
- NVIDIA RTX 4070 Ti12 GB
- NVIDIA RTX 407012 GB
- NVIDIA RTX 4060 Ti 16GB16 GB
- +90 more GPUs run both
Which should you use?
Choose Gemma 3 12B Instruct if:
- • Long context matters — it supports 128k tokens vs 125k
- • Benchmark quality matters — scores 60.6 vs 35.6 on MMLU-Pro
- • You need vision/image understanding
Choose Mistral Nemo 12B Instruct if:
Frequently asked questions
- Which is better, Gemma 3 12B Instruct or Mistral Nemo 12B Instruct?
- Gemma 3 12B Instruct is more hardware-efficient, needing 8.9 GB at Q4_K_M vs 9.2 GB. Gemma 3 12B Instruct runs on more GPUs natively (105 vs 102). On MMLU-Pro, Gemma 3 12B Instruct scores higher (60.6 vs 35.6).
- How much VRAM does Gemma 3 12B Instruct need vs Mistral Nemo 12B Instruct?
- At Q4_K_M quantization with 8k context, Gemma 3 12B Instruct needs approximately 8.9 GB of VRAM, while Mistral Nemo 12B Instruct needs 9.2 GB. At FP16, Gemma 3 12B Instruct requires 28.5 GB vs 28.8 GB for Mistral Nemo 12B Instruct.
- Can you run Gemma 3 12B Instruct on the same GPUs as Mistral Nemo 12B Instruct?
- Yes, 102 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 5080, NVIDIA RTX 5070 Ti. However, 3 GPUs can run Gemma 3 12B Instruct but not Mistral Nemo 12B Instruct, and no GPU can run Mistral Nemo 12B Instruct without also fitting Gemma 3 12B Instruct.
- What is the difference between Gemma 3 12B Instruct and Mistral Nemo 12B Instruct?
- Gemma 3 12B Instruct has 12.2B parameters (dense) with a 128k context window. Mistral Nemo 12B Instruct has 12.2B parameters (dense) with a 125k context window. Licensing differs: Gemma 3 12B Instruct is Gemma while Mistral Nemo 12B Instruct is Apache 2.0.
- Which model fits in 24 GB of VRAM, Gemma 3 12B Instruct or Mistral Nemo 12B Instruct?
- Both fit in 24 GB of VRAM at Q4_K_M — Gemma 3 12B Instruct needs 8.9 GB and Mistral Nemo 12B Instruct needs 9.2 GB.