Qwen 2.5 VL 7BvsQwen 3 VL 30B-A3B
Complete comparison between Qwen 2.5 VL 7B (7B parameters, Alibaba) and Qwen 3 VL 30B-A3B (30B, Alibaba). VRAM required by quantization, tokens per second measured on 4 reference GPUs, verdict by use case, license, installation commands. All figures are calculated from catalog data — no copy-pasting between pages.
In brief
| Feature | Qwen 2.5 VL 7B | Qwen 3 VL 30B-A3B |
|---|---|---|
| Settings | 7B | 30B |
| Family | Qwen | Qwen |
| Author | Alibaba | Alibaba |
| Origin | CN | CN |
| License | Apache 2.0 | Apache 2.0 |
| Context | 128,000 tokens | 262,144 tokens |
| Output | January 2025 | May 2025 |
Memory footprint
Approximate VRAM required for inference with an average context window. The winner (in green) is the model that uses less — smaller models have the edge.
| Quantization | Qwen 2.5 VL 7B | Qwen 3 VL 30B-A3B |
|---|---|---|
| Q4_K_M (lightweight) | 6 GB | 19 GB |
| Q5_K_M (balanced) | 7 GB | 23 GB |
| Q8 (near-lossless) | 10 GB | 35 GB |
| FP16 (max quality) | 18 GB | 62 GB |
| CPU-only RAM | 10 GB | 32 GB |
Estimated speed (tokens/second)
Estimates based on the best quantization that can fit on each GPU. Actual figures depend on the prompt, context, and engine (llama.cpp, vLLM, MLX). Methodology.
| Reference GPU | Qwen 2.5 VL 7B | Qwen 3 VL 30B-A3B |
|---|---|---|
| RTX 4090 (24 GB) | 60 tok/s · FP16 | 100 tok/s · Q5_K_M |
| RTX 4080 (16 GB) | 25 tok/s · Q8 | ✗ too heavy |
| RTX 3060 12GB (12 GB) | 8 tok/s · Q8 | ✗ too heavy |
| Apple M4 Pro (48 GB) (36 GB) | 25 tok/s · FP16 | 40 tok/s · Q8 |
Verdict by use case
For each common use case, we indicate which of the two is better suited based on its tags, size, and specialization.
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Strengths and weaknesses
Qwen 2.5 VL 7B
State-of-the-art 7B vision. Video >1h, bbox grounding, multilingual OCR. DocVQA 95.7.
- SOTA vision at 7B
- Excellent multilingual OCR
- Long video
- Apache 2.0
- Requires a VLM-compatible Ollama backend ≥ 0.5
Installation
Qwen 3 VL 30B-A3B
Vision MoE with 30B/3B active. Vision sweet spot Qwen 3. 256k ctx.
- 262k multimodal context
- 19 GB VRAM Q4
- Efficient MoE
- Apache 2.0
- Worse vision than the 235B
- Fewer fine-tunes than Qwen2-VL
Installation
Frequently asked questions
Which model runs best on RTX 4090 (24 GB): Qwen 2.5 VL 7B or Qwen 3 VL 30B-A3B?
On an RTX 4090, Qwen 2.5 VL 7B runs at FP16 (~60 tok/s), Qwen 3 VL 30B-A3B in Q5_K_M (~100 tok/s). In pure throughput, Qwen 3 VL 30B-A3B wins. See the configurator to test your exact GPU.
Which uses the least VRAM?
In Q4_K_M, Qwen 2.5 VL 7B fits in 6 GB versus 19 GB for its rival — a 13 GB gap, significant if you’re targeting an RTX 3060 or an 8 GB 4060 Ti.
Can these models be used in commercial production?
Qwen 2.5 VL 7B is under Apache 2.0 — free for commercial use. Qwen 3 VL 30B-A3B is under Apache 2.0 — also free to use. For SaaS, prefer Apache 2.0 or MIT.
Which one should you choose in 2026?
Depends on your primary constraint. Smaller / faster: Qwen 2.5 VL 7B (7B). More capable: Qwen 3 VL 30B-A3B (30B). If you're unsure, run it configurator with your GPU and use case — it will decide based on both.
Alternatives to consider
If neither works for you, here are some neighboring models you could explore.