Nemotron Nano v2 VL 12B vs Qwen 2.5 VL 7B

The two models at a glance

About Nemotron Nano v2 VL 12B

NVIDIA's 12.6B enterprise VLM with strong DocVQA and ChartQA scores, tuned for professional document extraction workflows. Strengths: Combined vision and text in a 12B footprint, 128k context window, Strong DocVQA and ChartQA benchmark scores, NVIDIA Open Model license.

About Qwen 2.5 VL 7B

A 7B vision-language model from Alibaba with state-of-the-art results in its class, scoring 95.7 on DocVQA. Handles hour-long video, bounding-box grounding, and multilingual OCR. Strengths: State-of-the-art vision performance at the 7B tier, Excellent multilingual OCR, Long video input (over 1 hour), Apache 2.0.

How they compare

Nemotron Nano v2 VL 12B comes from NVIDIA and Qwen 2.5 VL 7B from Alibaba, they belong to the Nemotron and Qwen 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 12.6B vs 7B parameters, Nemotron Nano v2 VL 12B is the larger of the two. At Q4, Qwen 2.5 VL 7B fits in about 6 GB of VRAM versus 8 GB for the other — a 2 GB difference that matters on consumer GPUs.

The two models target different sweet spots: Nemotron Nano v2 VL 12B is tuned for vision, chat, while Qwen 2.5 VL 7B leans toward vision, chat, general. Match the model to your dominant workload rather than to raw size.

On a typical mid-range GPU, Qwen 2.5 VL 7B 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, Nemotron Nano v2 VL 12B requires Q4 ≈ 8 GB, Q5 ≈ 10 GB, Q8 ≈ 14 GB, FP16 ≈ 25 GB, while Qwen 2.5 VL 7B requires Q4 ≈ 6 GB, Q5 ≈ 7 GB, Q8 ≈ 10 GB, FP16 ≈ 18 GB. In practice Nemotron Nano v2 VL 12B 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, Nemotron Nano v2 VL 12B needs roughly 14 GB of system RAM to run on CPU and Qwen 2.5 VL 7B about 10 GB — workable for offline use but far slower than GPU inference. On a mid-range GPU you can expect on the order of 22 tokens/sec from Nemotron Nano v2 VL 12B and 25 from Qwen 2.5 VL 7B, scaling up to 60 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 Nemotron Nano v2 VL 12B or Qwen 2.5 VL 7B to the card you actually own:

• On a 8 GB GPU: Nemotron Nano v2 VL 12B runs at Q4 (8 GB); Qwen 2.5 VL 7B runs at Q5 (7 GB).
• On a 12 GB GPU: Nemotron Nano v2 VL 12B runs at Q5 (10 GB); Qwen 2.5 VL 7B runs at Q8 (10 GB).
• On a 16 GB GPU: Nemotron Nano v2 VL 12B runs at Q8 (14 GB); Qwen 2.5 VL 7B runs at Q8 (10 GB).
• On a 24 GB GPU: Nemotron Nano v2 VL 12B runs at Q8 (14 GB); Qwen 2.5 VL 7B runs at FP16 (18 GB).

Benchmark scores

Reported benchmarks for Qwen 2.5 VL 7B: DocVQA 95.7, ChartQA 87.3, OCRBench 86.4.

Bottom line: which should you pick?

• Pick Qwen 2.5 VL 7B if you need a permissive (Apache 2.0) license for commercial deployment.
• Pick Qwen 2.5 VL 7B for lower VRAM and faster inference; pick Nemotron Nano v2 VL 12B for maximum headline quality.
• Pick Qwen 2.5 VL 7B if your workload is general.

Which GPU should you buy to run Nemotron Nano v2 VL 12B?

To run Nemotron Nano v2 VL 12B locally at Q4, you need ~8 GB of VRAM. The best value for this is a RTX 5060 (8 GB VRAM).

Frequently asked questions

What is the difference between Nemotron Nano v2 VL 12B and Qwen 2.5 VL 7B?

The headline differences: Nemotron Nano v2 VL 12B is a 12.6B model and Qwen 2.5 VL 7B is 7B; they ship under different licenses (NVIDIA Open Model License vs Apache 2.0). Below we break down VRAM by quantization, benchmark scores, and a use-case verdict so you can pick the right one.

Can Nemotron Nano v2 VL 12B and Qwen 2.5 VL 7B run on a 24 GB GPU?

At a Q4 quantization, Nemotron Nano v2 VL 12B needs about 8 GB of VRAM and fits comfortably on a 24 GB GPU; Qwen 2.5 VL 7B needs about 6 GB and fits comfortably on a 24 GB GPU. Qwen 2.5 VL 7B is the lighter option for tight VRAM budgets.

Which is faster, Nemotron Nano v2 VL 12B or Qwen 2.5 VL 7B?

Qwen 2.5 VL 7B is the smaller model (7B vs 12.6B), 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, Nemotron Nano v2 VL 12B or Qwen 2.5 VL 7B?

Qwen 2.5 VL 7B ships under Apache 2.0, a permissive license with no usage restrictions, whereas the other is under NVIDIA Open Model License — check its terms before commercial deployment.