Qwen2.5 Coder 1.5B — Hardware Requirements & GPU Compatibility
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Qwen2.5 Coder 1.5B is a 1.5-billion parameter code-specialized model from Alibaba Cloud's Qwen 2.5 Coder series. It is the smallest Coder variant that balances meaningful code generation capability with extremely low resource requirements, running on GPUs with as little as 2-4GB of VRAM. The model is suitable for lightweight code completion, simple code generation tasks, and as a compact local coding assistant in resource-constrained environments. It supports a 128K token context window. Released under the Apache 2.0 license.
584.8K downloads
85 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen 2.5
- Parameters
- 1.5B
- 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 1.5B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q8_0 | 8.00 | 1.9 GB | 2.7 GB | 1.50 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Qwen2.5 Coder 1.5B?
Q8_0 · 1.9 GBQwen2.5 Coder 1.5B (Q8_0) requires 1.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ GB is recommended. Using the full 33K context window can add up to 0.9 GB, bringing total usage to 2.7 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 1.5B?
Q8_0 · 1.9 GB33 devices with unified memory can run Qwen2.5 Coder 1.5B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (1)
Frequently Asked Questions
- How much VRAM does Qwen2.5 Coder 1.5B need?
Qwen2.5 Coder 1.5B requires 1.9 GB of VRAM at Q8_0. Full 33K context adds up to 0.9 GB (2.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1.5B × 8 bits ÷ 8 = 1.5 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 1.2 GB (at full 33K context)
VRAM usage by quantization
Q8_01.9 GBQ8_0 + full context2.7 GB- Can I run Qwen2.5 Coder 1.5B on a Mac?
Qwen2.5 Coder 1.5B requires at least 1.9 GB at Q8_0, 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 1.5B locally?
Yes — Qwen2.5 Coder 1.5B can run locally on consumer hardware. At Q8_0 quantization it needs 1.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen2.5 Coder 1.5B?
At Q8_0, Qwen2.5 Coder 1.5B can reach ~1567 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~352 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 ÷ 1.9 × 0.55 = ~1567 tok/s
Estimated speed at Q8_0 (1.9 GB)
AMD Instinct MI300X~1567 tok/sNVIDIA GeForce RTX 4090~352 tok/sNVIDIA H100 SXM~1171 tok/sAMD Instinct MI250X~969 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 1.5B?
At Q8_0, the download is about 1.50 GB.