Meta Llama 3 8B AQLM PV 2Bit 1x16 — Hardware Requirements & GPU Compatibility
Chat
Meta Llama 3 8B AQLM PV 2Bit 1x16 is a 2.0B-parameter open language model from ISTA-DASLab in the Llama 3 family. It supports a context window of up to 8,192 tokens. At Q4_K_M it needs about 1.79 GB of VRAM — see which GPUs and Macs can run it below.
37 downloads
4 likesSpecifications
- Publisher
- ISTA-DASLab
- Family
- Llama 3
- Parameters
- 2.0B
- Architecture
- LlamaForCausalLM
- Context Length
- 8,192 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2024-05-31
Get Started
How Much VRAM Does Meta Llama 3 8B AQLM PV 2Bit 1x16 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 1.4 GB | 2.2 GB | 0.87 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 1.5 GB | 2.3 GB | 0.89 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 1.6 GB | 2.4 GB | 1.00 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 1.6 GB | 2.4 GB | 1.02 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 1.8 GB | 2.6 GB | 1.23 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 2.0 GB | 2.8 GB | 1.46 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 2.3 GB | 3.1 GB | 1.68 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 2.6 GB | 3.4 GB | 2.04 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Meta Llama 3 8B AQLM PV 2Bit 1x16?
Q4_K_M · 1.8 GBMeta Llama 3 8B AQLM PV 2Bit 1x16 (Q4_K_M) requires 1.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 3+ GB is recommended. Using the full 8K context window can add up to 0.8 GB, bringing total usage to 2.6 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Meta Llama 3 8B AQLM PV 2Bit 1x16?
Q4_K_M · 1.8 GB33 devices with unified memory can run Meta Llama 3 8B AQLM PV 2Bit 1x16, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Meta Llama 3 8B AQLM PV 2Bit 1x16 need?
Meta Llama 3 8B AQLM PV 2Bit 1x16 requires 1.8 GB of VRAM at Q4_K_M, or 2.6 GB at Q8_0. Full 8K context adds up to 0.8 GB (2.6 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 2.0B × 4.8 bits ÷ 8 = 1.2 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 1.4 GB (at full 8K context)
VRAM usage by quantization
Q4_K_M1.8 GBQ4_K_M + full context2.6 GB- What's the best quantization for Meta Llama 3 8B AQLM PV 2Bit 1x16?
For Meta Llama 3 8B AQLM PV 2Bit 1x16, Q4_K_M (1.8 GB) offers the best balance of quality and VRAM usage. Q5_0 (1.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 1.4 GB.
VRAM requirement by quantization
Q2_K1.4 GBQ4_01.6 GBQ4_K_M ★1.8 GBQ5_01.8 GBQ5_K_S2.0 GBQ8_02.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Meta Llama 3 8B AQLM PV 2Bit 1x16 on a Mac?
Meta Llama 3 8B AQLM PV 2Bit 1x16 requires at least 1.4 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 Meta Llama 3 8B AQLM PV 2Bit 1x16 locally?
Yes — Meta Llama 3 8B AQLM PV 2Bit 1x16 can run locally on consumer hardware. At Q4_K_M quantization it needs 1.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Meta Llama 3 8B AQLM PV 2Bit 1x16?
At Q4_K_M, Meta Llama 3 8B AQLM PV 2Bit 1x16 can reach ~1629 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~366 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 ÷ 1.8 × 0.55 = ~1629 tok/s
Estimated speed at Q4_K_M (1.8 GB)
~1629 tok/s~366 tok/s~1217 tok/s~1007 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Meta Llama 3 8B AQLM PV 2Bit 1x16?
At Q4_K_M, the download is about 1.23 GB. The full-precision Q8_0 version is 2.04 GB. The smallest option (Q2_K) is 0.87 GB.
- Which GPUs can run Meta Llama 3 8B AQLM PV 2Bit 1x16?
35 consumer GPUs can run Meta Llama 3 8B AQLM PV 2Bit 1x16 at Q4_K_M (1.8 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Meta Llama 3 8B AQLM PV 2Bit 1x16?
33 devices with unified memory can run Meta Llama 3 8B AQLM PV 2Bit 1x16 at Q4_K_M (1.8 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.