Qwen2.5 Coder 0.5B — Hardware Requirements & GPU Compatibility
ChatCode
Qwen2.5 Coder 0.5B is a 494-million parameter code-specialized model from Alibaba Cloud, the smallest in the Qwen 2.5 Coder series. It is designed for ultra-lightweight deployment where code-aware text generation is needed with minimal hardware resources. The model runs on virtually any GPU and even on CPU-only setups. While limited in capability compared to larger coding models, it is useful for basic code completion, prototyping, and experimentation. It supports a 128K token context window. Released under the Apache 2.0 license.
63.5K downloads
46 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen 2.5
- Parameters
- 494M
- Architecture
- Qwen2ForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2024-11-18
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen2.5 Coder 0.5B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 1.3 GB | 1.7 GB | 0.99 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Qwen2.5 Coder 0.5B?
BF16 · 1.3 GBQwen2.5 Coder 0.5B (BF16) requires 1.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2+ GB is recommended. Using the full 33K context window can add up to 0.4 GB, bringing total usage to 1.7 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Qwen2.5 Coder 0.5B?
BF16 · 1.3 GB33 devices with unified memory can run Qwen2.5 Coder 0.5B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen2.5 Coder 0.5B need?
Qwen2.5 Coder 0.5B requires 1.3 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 494M × 16 bits ÷ 8 = 1 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 0.7 GB (at full 33K context)
VRAM usage by quantization
BF161.3 GBBF16 + full context1.7 GB- Can I run Qwen2.5 Coder 0.5B on a Mac?
Qwen2.5 Coder 0.5B requires at least 1.3 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen2.5 Coder 0.5B locally?
Yes — Qwen2.5 Coder 0.5B can run locally on consumer hardware. At BF16 quantization it needs 1.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen2.5 Coder 0.5B?
At BF16, Qwen2.5 Coder 0.5B can reach ~2225 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~500 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 1.3 × 0.55 = ~2225 tok/s
Estimated speed at BF16 (1.3 GB)
AMD Instinct MI300X~2225 tok/sNVIDIA GeForce RTX 4090~500 tok/sNVIDIA H100 SXM~1663 tok/sAMD Instinct MI250X~1376 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen2.5 Coder 0.5B?
At BF16, the download is about 0.99 GB.