Qwen1.5 1.8B — Hardware Requirements & GPU Compatibility
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Qwen1.5 1.8B is a 1.8B-parameter open language model from Alibaba in the Qwen family. It supports a context window of up to 32,768 tokens. At BF16 it needs about 4.38 GB of VRAM — see which GPUs and Macs can run it below.
21.5K downloads
58 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen
- Parameters
- 1.8B
- Architecture
- Qwen2ForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2024-04-05
- License
- Other
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HuggingFace
How Much VRAM Does Qwen1.5 1.8B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 4.4 GB | 10.4 GB | 3.67 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Qwen1.5 1.8B?
BF16 · 4.4 GBQwen1.5 1.8B (BF16) requires 4.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 6+ GB is recommended. Using the full 33K context window can add up to 6.0 GB, bringing total usage to 10.4 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Qwen1.5 1.8B?
BF16 · 4.4 GB33 devices with unified memory can run Qwen1.5 1.8B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen1.5 1.8B need?
Qwen1.5 1.8B requires 4.4 GB of VRAM at BF16. Full 33K context adds up to 6.0 GB (10.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1.8B × 16 bits ÷ 8 = 3.7 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 6.7 GB (at full 33K context)
VRAM usage by quantization
BF164.4 GBBF16 + full context10.4 GB- Can I run Qwen1.5 1.8B on a Mac?
Qwen1.5 1.8B requires at least 4.4 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 Qwen1.5 1.8B locally?
Yes — Qwen1.5 1.8B can run locally on consumer hardware. At BF16 quantization it needs 4.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen1.5 1.8B?
At BF16, Qwen1.5 1.8B can reach ~666 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~150 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 ÷ 4.4 × 0.55 = ~666 tok/s
Estimated speed at BF16 (4.4 GB)
~666 tok/s~150 tok/s~497 tok/s~412 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen1.5 1.8B?
At BF16, the download is about 3.67 GB.
- Which GPUs can run Qwen1.5 1.8B?
35 consumer GPUs can run Qwen1.5 1.8B at BF16 (4.4 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen1.5 1.8B?
33 devices with unified memory can run Qwen1.5 1.8B at BF16 (4.4 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.