Meta·Llama 2

Llama 2 7B Chat HF — Hardware Requirements & GPU Compatibility

Chat

Meta Llama 2 7B Chat is a 7-billion parameter instruction-tuned model from Meta's Llama 2 family, optimized for dialogue use cases. It was fine-tuned using supervised fine-tuning and RLHF on top of the Llama 2 7B base model, with a 4K token context window. This model is suitable for basic conversational AI tasks and runs efficiently on consumer GPUs. While newer Llama generations offer improved performance, Llama 2 7B Chat remains a well-understood and widely-supported option for local inference. Released under the Llama 2 Community License.

355.4K downloads 4.7K likesApr 2024

Specifications

Publisher
Meta
Family
Llama 2
Parameters
7B
Release Date
2024-04-17
License
Llama 2 Community

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How Much VRAM Does Llama 2 7B Chat HF Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_K3.403.3 GB
Q3_K_S3.503.4 GB
Q3_K_M3.903.8 GB
Q3_K_L4.104.0 GB
Q4_K_S4.504.3 GB
Q4_K_M4.804.6 GB
Q5_K_S5.505.3 GB
Q5_K_M5.705.5 GB
Q6_K6.606.3 GB
Q8_08.007.7 GB

Which GPUs Can Run Llama 2 7B Chat HF?

Q4_K_M · 4.6 GB

Llama 2 7B Chat HF (Q4_K_M) requires 4.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Which Devices Can Run Llama 2 7B Chat HF?

Q4_K_M · 4.6 GB

33 devices with unified memory can run Llama 2 7B Chat HF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.

Related Models

Frequently Asked Questions

How much VRAM does Llama 2 7B Chat HF need?

Llama 2 7B Chat HF requires 4.6 GB of VRAM at Q4_K_M, or 7.7 GB at Q8_0.

VRAM = Weights + KV Cache + Overhead

Weights = 7B × 4.8 bits ÷ 8 = 4.2 GB

KV Cache + Overhead 0.4 GB (at 2K context + ~0.3 GB framework)

VRAM usage by quantization

4.6 GB

Learn more about VRAM estimation →

What's the best quantization for Llama 2 7B Chat HF?

For Llama 2 7B Chat HF, Q4_K_M (4.6 GB) offers the best balance of quality and VRAM usage. Q5_K_S (5.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.3 GB.

VRAM requirement by quantization

Q2_K
3.3 GB
Q3_K_M
3.8 GB
Q4_K_M
4.6 GB
Q5_K_S
5.3 GB
Q5_K_M
5.5 GB
Q8_0
7.7 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Llama 2 7B Chat HF on a Mac?

Llama 2 7B Chat HF requires at least 3.3 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 Chat HF locally?

Yes — Llama 2 7B Chat HF can run locally on consumer hardware. At Q4_K_M quantization it needs 4.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Llama 2 7B Chat HF?

At Q4_K_M, Llama 2 7B Chat HF can reach ~631 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~142 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 MI300X5300 ÷ 4.6 × 0.55 = ~631 tok/s

Estimated speed at Q4_K_M (4.6 GB)

~631 tok/s
~142 tok/s
~472 tok/s
~390 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of Llama 2 7B Chat HF?

At Q4_K_M, the download is about 4.20 GB. The full-precision Q8_0 version is 7.00 GB. The smallest option (Q2_K) is 2.98 GB.