32 GB VRAM · Q4 native Amazon
RTX 5090
Vorteile
- Runs Qwen2.5 Coder 14B at Q4 natively
- 32 GB VRAM — adequate headroom
CPU-capable model ready
Qwen2.5 Coder 14B
39 consumer GPUs can run Qwen2.5 Coder 14B at Q4 natively. Precise VRAM thresholds and benchmarks below.
39 Compatible GPUs
1 with offloading
14B params
131K context
Top pick
RTX 5090 · 32 GB VRAM runs Q4 natively
Prices and availability may change · affiliate link
Javier Morales AI hardware specialist — 8 years of experience
GitHub: github.com/javier-morales-ia
llama.cpp 0.2.x · CUDA 12 · ROCm 6 · updated monthly · methodology →
Execution Context
ARCHITECTURE TRANSFORMER
CONTEXT 131K TOKENS
QUANTIZATION 4-BIT GGUF
PROVIDER Alibaba
LICENSE Apache-2.0
Hardware Decision
This model requires aEntry GPU (8 GB VRAM)
Compatible GPUs for Qwen2.5 Coder 14B
Best picks by compatibility, VRAM headroom, and value — prices and availability may change.
24 GB VRAM · Q4 native Amazon
RTX 4090
Vorteile
- Runs Qwen2.5 Coder 14B at Q4 natively
- 24 GB VRAM — adequate headroom
128 GB VRAM · Q4 native Amazon
M4 Ultra
Vorteile
- Runs Qwen2.5 Coder 14B at Q4 natively
- 128 GB VRAM — adequate headroom
Einige Links sind Amazon-Partnerlinks. Wir koennen ohne Mehrkosten fuer Sie eine Provision erhalten. Amazon-Cookies koennen nach Ihrem Klick bis zu 24 Stunden bestehen.
How to run this model
CPU vs GPU for Qwen2.5 Coder 14B →
VRAM Calculator — instant compatibility check
RTX 5090
32 GB · Runs Q4 natively · Check availability
*Prices and availability may change. Some links are affiliate links.
System Requirements
GPU VRAM 8 GB Entry GPU
System RAM 16 GB
DDR4/DDR5
Storage 7.5 GB Q4 · SSD recommended
CPU i7 → 5 tok/s Runs without GPU
VRAM by Quantization
| Quantization | VRAM needed | Disk space | Quality |
|---|---|---|---|
| FP16 (max quality) | 28 GB | 28 GB | Maximum |
| Q8 (high quality) | 14 GB | 14 GB | Near-lossless |
| Q4 (recommended) Best balance | 8 GB | 7.5 GB | Recommended |
| Q2 (minimum) | 4 GB | 4 GB | Quality loss |
Model Details
| Developer | Alibaba |
| Parameters | 14B |
| Context window | 131,072 tokens |
| License | Apache-2.0 |
| Use cases | coding, chat, reasoning |
| Released | 2024-09 |
Install with Ollama
ollama run qwen2.5-coder:14b Hugging Face
Qwen/Qwen2.5-Coder-14B-Instruct Technical Requirements
Can your GPU run Qwen2.5 Coder 14B?
Qwen2.5 Coder 14B requires <strong class="text-primary-container">8 GB VRAM</strong> at Q4. 39 consumer GPUs meet this threshold. Below 8 GB or 6 GB you'll hit significant offload latency.
4GB Critical min
8GB Optimal Q4
14GB High Quality Q8
28GB Max FP16
Hardware Performance Matrix
39 Q4 native · 1 offload
Recommended GPUs for Qwen2.5 Coder 14B
Reale Benchmarks
Keine bezahlten Reviews
Redaktionelle Auswahl
Datenbasiert
Best picks by compatibility, VRAM headroom, and value — prices and availability may change.
RTX 5090
32 GB VRAM
Q4 native
Check availability →
RTX 4090
24 GB VRAM
Q4 native
Check availability →
M4 Ultra
128 GB VRAM
Q4 native
Check availability →
Einige Links sind Amazon-Partnerlinks. Wir koennen ohne Mehrkosten fuer Sie eine Provision erhalten. Amazon-Cookies koennen nach Ihrem Klick bis zu 24 Stunden bestehen.
Qwen2.5 Coder 14B — Compatibility guide
Qwen2.5 Coder 14B can run on CPU without a dedicated GPU — unusual for a 14B model. On an i7-13700K with llama.cpp Q4 it reaches 5 tok/s (slow but usable). With a GPU you get 4–6× more speed — check the VRAM calculator for specifics.
Compare GPUs for Qwen2.5 Coder 14B
Which GPU is worth it? Real specs and benchmarks side by side.
Compatible Hardware
GPUs that run Qwen2.5 Coder 14B at Q4 — sorted by AI performance score.
Reale Benchmarks
Keine bezahlten Reviews
Datenbasiert
Einige Links sind Amazon-Partnerlinks. Wir koennen ohne Mehrkosten fuer Sie eine Provision erhalten. Amazon-Cookies koennen nach Ihrem Klick bis zu 24 Stunden bestehen.
More Practical Alternatives
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Not sure which GPU you need for Qwen2.5 Coder 14B?
The VRAM Calculator tells you exactly which quantization your hardware can handle.
RTX 5090
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