Qwen 3 14BvsQwen 3 8B
Complete comparison between Qwen 3 14B (14B parameters, Alibaba) and Qwen 3 8B (8B, 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 3 14B | Qwen 3 8B |
|---|---|---|
| Settings | 14B | 8B |
| Family | Qwen | Qwen |
| Author | Alibaba | Alibaba |
| Origin | CN | CN |
| License | Apache 2.0 | Apache 2.0 |
| Context | 131,072 tokens | 131,072 tokens |
| Output | April 2025 | April 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 3 14B | Qwen 3 8B |
|---|---|---|
| Q4_K_M (lightweight) | 9 GB | 5 GB |
| Q5_K_M (balanced) | 11 GB | 6 GB |
| Q8 (near-lossless) | 16 GB | 9 GB |
| FP16 (max quality) | 28 GB | 16 GB |
| CPU-only RAM | 16 GB | 10 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 3 14B | Qwen 3 8B |
|---|---|---|
| RTX 4090 (24 GB) | 55 tok/s · Q8 | 90 tok/s · FP16 |
| RTX 4080 (16 GB) | 20 tok/s · Q8 | 35 tok/s · FP16 |
| RTX 3060 12GB (12 GB) | 6 tok/s · Q5_K_M | 12 tok/s · Q8 |
| Apple M4 Pro (48 GB) (36 GB) | 20 tok/s · FP16 | 35 tok/s · FP16 |
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 3 14B
Dense 14B with hybrid thinking. Equals Qwen 2.5 32B Based on STEM/code.
- Dense 14B matching Qwen 2.5 32B Base
- Hybrid thinking
- 131k ctx
- Not yet at the level of specialized reasoners on AIME
Installation
Qwen 3 8B
Hybrid thinking/fast mode. 119 languages, 32k native (131k via YaRN).
- Toggleable thinking mode
- 119 languages
- 131k ctx (with YaRN)
- Apache 2.0
- Verbose thinking mode
- Less mature than Qwen 2.5 in terms of ecosystem
Installation
Frequently asked questions
Which model runs better on RTX 4090 (24 GB): Qwen 3 14B or Qwen 3 8B?
On an RTX 4090, Qwen 3 14B runs at Q8 (~55 tok/s), Qwen 3 8B in FP16 (~90 tok/s). In pure throughput, Qwen 3 8B wins. See the configurator to test your exact GPU.
Which uses the least VRAM?
In Q4_K_M, Qwen 3 8B fits in 5 GB versus 9 GB for its rival—a 4 GB difference, significant if you are targeting an RTX 3060 or an 8 GB 4060 Ti.
Can these models be used in commercial production?
Qwen 3 14B is under Apache 2.0 — free for commercial use. Qwen 3 8B 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 3 8B (8B). More capable: Qwen 3 14B (14B). 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.