Higgs Llama 3 70B — Hardware Requirements & GPU Compatibility
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Higgs Llama 3 70B is a 70.6B-parameter open language model from bosonai in the Llama 3 family. It supports a context window of up to 8,192 tokens. At Q4_K_M it needs about 43.30 GB of VRAM — see which GPUs and Macs can run it below.
7.5K downloads
230 likesSpecifications
- Publisher
- bosonai
- Family
- Llama 3
- Parameters
- 70.6B
- Architecture
- LlamaForCausalLM
- Context Length
- 8,192 tokens
- Vocabulary Size
- 128,256
- Release Date
- 2024-06-05
- License
- Other
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HuggingFace
How Much VRAM Does Higgs Llama 3 70B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 31.0 GB | 33.0 GB | 29.99 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 35.4 GB | 37.4 GB | 34.39 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 43.3 GB | 45.3 GB | 42.33 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 51.2 GB | 53.3 GB | 50.27 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 59.2 GB | 61.2 GB | 58.21 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 71.5 GB | 73.5 GB | 70.55 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 142.1 GB | 144.1 GB | 141.11 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 Higgs Llama 3 70B?
Q4_K_M · 43.3 GBHiggs Llama 3 70B (Q4_K_M) requires 43.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 57+ GB is recommended. Using the full 8K context window can add up to 2.0 GB, bringing total usage to 45.3 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Higgs Llama 3 70B?
Q4_K_M · 43.3 GB11 devices with unified memory can run Higgs Llama 3 70B, 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 Higgs Llama 3 70B need?
Higgs Llama 3 70B requires 43.3 GB of VRAM at Q4_K_M, or 142.1 GB at BF16. Full 8K context adds up to 2.0 GB (45.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 70.6B × 4.8 bits ÷ 8 = 42.3 GB
KV Cache + Overhead ≈ 1 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 3 GB (at full 8K context)
VRAM usage by quantization
Q4_K_M43.3 GBQ4_K_M + full context45.3 GB- Can NVIDIA GeForce RTX 5090 run Higgs Llama 3 70B?
Yes, at Q2_K (31.0 GB) or lower. Higher quantizations like Q3_K_M (35.4 GB) exceed the NVIDIA GeForce RTX 5090's 32 GB.
- What's the best quantization for Higgs Llama 3 70B?
For Higgs Llama 3 70B, Q4_K_M (43.3 GB) offers the best balance of quality and VRAM usage. Q5_K_M (51.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 31.0 GB.
VRAM requirement by quantization
Q2_K31.0 GBQ4_K_M ★43.3 GBQ5_K_M51.2 GBQ6_K59.2 GBQ8_071.5 GBBF16142.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Higgs Llama 3 70B on a Mac?
Higgs Llama 3 70B requires at least 31.0 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 Higgs Llama 3 70B locally?
Yes — Higgs Llama 3 70B can run locally on consumer hardware. At Q4_K_M quantization it needs 43.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Higgs Llama 3 70B?
At Q4_K_M, Higgs Llama 3 70B can reach ~67 tok/s on AMD Instinct MI300X. 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 ÷ 43.3 × 0.55 = ~67 tok/s
Estimated speed at Q4_K_M (43.3 GB)
~67 tok/s~50 tok/s~42 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Higgs Llama 3 70B?
At Q4_K_M, the download is about 42.33 GB. The full-precision BF16 version is 141.11 GB. The smallest option (Q2_K) is 29.99 GB.
- Which GPUs can run Higgs Llama 3 70B?
No single consumer GPU has enough VRAM to run Higgs Llama 3 70B at Q4_K_M (43.3 GB). Multi-GPU or professional hardware is required.
- Which devices can run Higgs Llama 3 70B?
11 devices with unified memory can run Higgs Llama 3 70B at Q4_K_M (43.3 GB), including Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.