Llama 2 7B HF — Hardware Requirements & GPU Compatibility
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Meta Llama 2 7B is a 6.7-billion parameter base (pretrained) language model from Meta's Llama 2 generation, provided in Hugging Face Transformers format. It was trained on 2 trillion tokens with a 4K token context window and represented a significant step in openly available large language models when released. As a base model, it is designed for further fine-tuning and research rather than direct chat use. While superseded by Llama 3 and later releases in terms of benchmark performance, Llama 2 7B remains widely used in the research community and as a baseline for comparison. Released under the Llama 2 Community License.
848.3K downloads
2.3K likesSpecifications
- Publisher
- Meta
- Family
- Llama 2
- Parameters
- 6.7B
- Release Date
- 2024-04-17
- License
- Llama 2 Community
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HuggingFace
How Much VRAM Does Llama 2 7B HF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 3.1 GB | — | 2.86 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 3.2 GB | — | 2.95 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 3.6 GB | — | 3.28 GB | 3-bit medium quantization |
| Q3_K_L | 4.10 | 3.8 GB | — | 3.45 GB | 3-bit large quantization |
| IQ4_XS | 4.30 | 4.0 GB | — | 3.62 GB | Importance-weighted 4-bit, compact |
| Q4_K_S | 4.50 | 4.2 GB | — | 3.79 GB | 4-bit small quantization |
| Q4_K_M | 4.80 | 4.5 GB | — | 4.04 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_S | 5.50 | 5.1 GB | — | 4.63 GB | 5-bit small quantization |
| Q5_K_M | 5.70 | 5.3 GB | — | 4.80 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 6.1 GB | — | 5.56 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 7.4 GB | — | 6.74 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Llama 2 7B HF?
Q4_K_M · 4.5 GBLlama 2 7B HF (Q4_K_M) requires 4.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 6+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Llama 2 7B HF?
Q4_K_M · 4.5 GB33 devices with unified memory can run Llama 2 7B HF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Llama 2 7B HF need?
Llama 2 7B HF requires 4.5 GB of VRAM at Q4_K_M, or 7.4 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 6.7B × 4.8 bits ÷ 8 = 4 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M4.5 GB- What's the best quantization for Llama 2 7B HF?
For Llama 2 7B HF, Q4_K_M (4.5 GB) offers the best balance of quality and VRAM usage. Q5_K_S (5.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.1 GB.
VRAM requirement by quantization
Q2_K3.1 GB~75%Q3_K_L3.8 GB~86%Q4_K_S4.2 GB~88%Q4_K_M ★4.5 GB~89%Q5_K_M5.3 GB~92%Q8_07.4 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run Llama 2 7B HF on a Mac?
Llama 2 7B HF requires at least 3.1 GB at Q2_K, 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 Llama 2 7B HF locally?
Yes — Llama 2 7B HF can run locally on consumer hardware. At Q4_K_M quantization it needs 4.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llama 2 7B HF?
At Q4_K_M, Llama 2 7B HF can reach ~655 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~147 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 ÷ 4.5 × 0.55 = ~655 tok/s
Estimated speed at Q4_K_M (4.5 GB)
AMD Instinct MI300X~655 tok/sNVIDIA GeForce RTX 4090~147 tok/sNVIDIA H100 SXM~490 tok/sAMD Instinct MI250X~405 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Llama 2 7B HF?
At Q4_K_M, the download is about 4.04 GB. The full-precision Q8_0 version is 6.74 GB. The smallest option (Q2_K) is 2.86 GB.