Llama 2 70B Chat HF — Hardware Requirements & GPU Compatibility
Chat
Llama 2 70B Chat HF is a 69.0B-parameter open language model from Meta in the Llama 2 family. At Q4_K_M it needs about 45.52 GB of VRAM — see which GPUs and Macs can run it below.
72.9K downloads
2.2K likesSpecifications
- Publisher
- Meta
- Family
- Llama 2
- Parameters
- 69.0B
- Release Date
- 2023-07-14
- License
- Llama 2 Community
Get Started
HuggingFace
How Much VRAM Does Llama 2 70B Chat HF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 32.3 GB | — | 29.32 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 37.0 GB | — | 33.63 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 45.5 GB | — | 41.39 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 54.1 GB | — | 49.15 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 62.6 GB | — | 56.91 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 75.9 GB | — | 68.98 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 151.8 GB | — | 137.95 GB | Brain floating point 16 — preferred for training |
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 Llama 2 70B Chat HF?
Q4_K_M · 45.5 GBLlama 2 70B Chat HF (Q4_K_M) requires 45.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 60+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Llama 2 70B Chat HF?
Q4_K_M · 45.5 GB26 devices with unified memory can run Llama 2 70B Chat HF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does Llama 2 70B Chat HF need?
Llama 2 70B Chat HF requires 45.5 GB of VRAM at Q4_K_M, or 151.8 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 69.0B × 4.8 bits ÷ 8 = 41.4 GB
KV Cache + Overhead ≈ 4.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M45.5 GB- Can NVIDIA GeForce RTX 5090 run Llama 2 70B Chat HF?
No — Llama 2 70B Chat HF requires at least 32.3 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Llama 2 70B Chat HF?
For Llama 2 70B Chat HF, Q4_K_M (45.5 GB) offers the best balance of quality and VRAM usage. Q5_K_M (54.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 32.3 GB.
VRAM requirement by quantization
Q2_K32.3 GBQ4_K_M ★45.5 GBQ5_K_M54.1 GBQ6_K62.6 GBQ8_075.9 GBBF16151.8 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Llama 2 70B Chat HF on a Mac?
Llama 2 70B Chat HF requires at least 32.3 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 70B Chat HF locally?
Yes — Llama 2 70B Chat HF can run locally on consumer hardware. At Q4_K_M quantization it needs 45.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Llama 2 70B Chat HF?
At Q4_K_M, Llama 2 70B Chat HF can reach ~97 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 ÷ 45.5 × 0.65 = ~114 tok/s
Estimated speed at Q4_K_M (45.5 GB)
~114 tok/s~114 tok/s~97 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 70B Chat HF?
At Q4_K_M, the download is about 41.39 GB. The full-precision BF16 version is 137.95 GB. The smallest option (Q2_K) is 29.32 GB.
- Which GPUs can run Llama 2 70B Chat HF?
No single consumer GPU has enough VRAM to run Llama 2 70B Chat HF at Q4_K_M (45.5 GB). Multi-GPU or professional hardware is required.
- Which devices can run Llama 2 70B Chat HF?
27 devices with unified memory can run Llama 2 70B Chat HF at Q4_K_M (45.5 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.