Qwen2 7B — Hardware Requirements & GPU Compatibility
Chat
Qwen2 7B is a 7.6B-parameter open language model from Alibaba in the Qwen 2 family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 4.99 GB of VRAM — see which GPUs and Macs can run it below.
81.3K downloads
172 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen 2
- Parameters
- 7.6B
- Architecture
- Qwen2ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 152,064
- Release Date
- 2024-06-04
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen2 7B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 3.6 GB | 11.1 GB | 3.24 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 3.8 GB | 11.2 GB | 3.33 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.1 GB | 11.5 GB | 3.71 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 4.2 GB | 11.6 GB | 3.81 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 5.0 GB | 12.4 GB | 4.57 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 5.8 GB | 13.2 GB | 5.43 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 6.7 GB | 14.1 GB | 6.28 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 8.0 GB | 15.4 GB | 7.62 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 7B?
Q4_K_M · 5.0 GBQwen2 7B (Q4_K_M) requires 5.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. Using the full 131K context window can add up to 7.4 GB, bringing total usage to 12.4 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Qwen2 7B?
Q4_K_M · 5.0 GB59 devices with unified memory can run Qwen2 7B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Apple iPhone 17 Pro.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download Qwen2 7B
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 7B need?
Qwen2 7B requires 5.0 GB of VRAM at Q4_K_M, or 15.7 GB at BF16. Full 131K context adds up to 7.4 GB (12.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 7.6B × 4.8 bits ÷ 8 = 4.6 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 7.8 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M5.0 GBQ4_K_M + full context12.4 GB- What's the best quantization for Qwen2 7B?
For Qwen2 7B, Q4_K_M (5.0 GB) offers the best balance of quality and VRAM usage. Q5_0 (5.2 GB) provides better quality if you have the VRAM. The smallest option is IQ3_XS at 3.6 GB.
VRAM requirement by quantization
IQ3_XS3.6 GBQ3_K_M4.1 GBQ4_K_S4.7 GBQ4_K_M ★5.0 GBQ5_K_S5.7 GBBF1615.7 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen2 7B on a Mac?
Qwen2 7B requires at least 3.6 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 7B locally?
Yes — Qwen2 7B can run locally on consumer hardware. At Q4_K_M quantization it needs 5.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen2 7B?
At Q4_K_M, Qwen2 7B can reach ~882 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~131 tok/s. 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 ÷ 5.0 × 0.65 = ~1042 tok/s
Estimated speed at Q4_K_M (5.0 GB)
~1042 tok/s~131 tok/s~1042 tok/s~882 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen2 7B?
At Q4_K_M, the download is about 4.57 GB. The full-precision BF16 version is 15.23 GB. The smallest option (IQ3_XS) is 3.14 GB.
- Which GPUs can run Qwen2 7B?
50 consumer GPUs can run Qwen2 7B at Q4_K_M (5.0 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen2 7B?
59 devices with unified memory can run Qwen2 7B at Q4_K_M (5.0 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, 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.