Qwen2.5 72B — Hardware Requirements & GPU Compatibility
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Qwen2.5 72B is a 72.7B-parameter open language model from Alibaba in the Qwen 2.5 family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 44.59 GB of VRAM — see which GPUs and Macs can run it below.
23.7K downloads
102 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen 2.5
- Parameters
- 72.7B
- Architecture
- Qwen2ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 152,064
- Release Date
- 2024-09-15
- License
- Other
Get Started
HuggingFace
How Much VRAM Does Qwen2.5 72B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 31.9 GB | 74.2 GB | 30.90 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 32.8 GB | 75.1 GB | 31.81 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 36.4 GB | 78.7 GB | 35.44 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 37.3 GB | 79.6 GB | 36.35 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 44.6 GB | 86.9 GB | 43.62 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 52.8 GB | 95.0 GB | 51.80 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 61.0 GB | 103.2 GB | 59.98 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 73.7 GB | 116.0 GB | 72.71 GB | 8-bit quantization, near-lossless |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Qwen2.5 72B?
Q4_K_M · 44.6 GBQwen2.5 72B (Q4_K_M) requires 44.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 58+ GB is recommended. Using the full 131K context window can add up to 42.3 GB, bringing total usage to 86.9 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen2.5 72B?
Q4_K_M · 44.6 GB26 devices with unified memory can run Qwen2.5 72B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Where to Download Qwen2.5 72B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does Qwen2.5 72B need?
Qwen2.5 72B requires 44.6 GB of VRAM at Q4_K_M, or 146.4 GB at BF16. Full 131K context adds up to 42.3 GB (86.9 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 72.7B × 4.8 bits ÷ 8 = 43.6 GB
KV Cache + Overhead ≈ 1 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 43.3 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M44.6 GBQ4_K_M + full context86.9 GB- Can NVIDIA GeForce RTX 5090 run Qwen2.5 72B?
Yes, at Q2_K (31.9 GB) or lower. Higher quantizations like Q3_K_S (32.8 GB) exceed the NVIDIA GeForce RTX 5090's 32 GB.
- What's the best quantization for Qwen2.5 72B?
For Qwen2.5 72B, Q4_K_M (44.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (52.8 GB) provides better quality if you have the VRAM. The smallest option is IQ3_XS at 31.0 GB.
VRAM requirement by quantization
IQ3_XS31.0 GBIQ3_M33.7 GBIQ4_XS40.0 GBQ4_K_M ★44.6 GBQ5_K_M52.8 GBBF16146.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen2.5 72B on a Mac?
Qwen2.5 72B requires at least 31.0 GB at IQ3_XS, 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 72B locally?
Yes — Qwen2.5 72B can run locally on consumer hardware. At Q4_K_M quantization it needs 44.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen2.5 72B?
At Q4_K_M, Qwen2.5 72B can reach ~99 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 44.6 × 0.65 = ~117 tok/s
Estimated speed at Q4_K_M (44.6 GB)
~117 tok/s~117 tok/s~99 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 72B?
At Q4_K_M, the download is about 43.62 GB. The full-precision BF16 version is 145.41 GB. The smallest option (IQ3_XS) is 29.99 GB.
- Which GPUs can run Qwen2.5 72B?
No single consumer GPU has enough VRAM to run Qwen2.5 72B at Q4_K_M (44.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen2.5 72B?
27 devices with unified memory can run Qwen2.5 72B at Q4_K_M (44.6 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.