Dolphin 2.9.1 Llama 3 70B — Hardware Requirements & GPU Compatibility
ChatSpecifications
- Publisher
- dphn
- Family
- Llama 3
- Parameters
- 70.6B
- Architecture
- LlamaForCausalLM
- Context Length
- 8,192 tokens
- Vocabulary Size
- 128,258
- Release Date
- 2024-06-14
- License
- Llama 3 Community
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HuggingFace
How Much VRAM Does Dolphin 2.9.1 Llama 3 70B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 142.1 GB | 144.1 GB | 141.11 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Dolphin 2.9.1 Llama 3 70B?
BF16 · 142.1 GBDolphin 2.9.1 Llama 3 70B (BF16) requires 142.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 185+ GB is recommended. Using the full 8K context window can add up to 2.0 GB, bringing total usage to 144.1 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Dolphin 2.9.1 Llama 3 70B?
BF16 · 142.1 GB4 devices with unified memory can run Dolphin 2.9.1 Llama 3 70B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Pro M2 Ultra (192 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Dolphin 2.9.1 Llama 3 70B need?
Dolphin 2.9.1 Llama 3 70B requires 142.1 GB of VRAM at BF16. Full 8K context adds up to 2.0 GB (144.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 70.6B × 16 bits ÷ 8 = 141.1 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
BF16142.1 GBBF16 + full context144.1 GB- Can NVIDIA GeForce RTX 5090 run Dolphin 2.9.1 Llama 3 70B?
No — Dolphin 2.9.1 Llama 3 70B requires at least 142.1 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Dolphin 2.9.1 Llama 3 70B on a Mac?
Dolphin 2.9.1 Llama 3 70B requires at least 142.1 GB at BF16, 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 Dolphin 2.9.1 Llama 3 70B locally?
Yes — Dolphin 2.9.1 Llama 3 70B can run locally on consumer hardware. At BF16 quantization it needs 142.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Dolphin 2.9.1 Llama 3 70B?
At BF16, Dolphin 2.9.1 Llama 3 70B can reach ~21 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 ÷ 142.1 × 0.55 = ~21 tok/s
Estimated speed at BF16 (142.1 GB)
AMD Instinct MI300X~21 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Dolphin 2.9.1 Llama 3 70B?
At BF16, the download is about 141.11 GB.
- Which GPUs can run Dolphin 2.9.1 Llama 3 70B?
No single consumer GPU has enough VRAM to run Dolphin 2.9.1 Llama 3 70B at BF16 (142.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run Dolphin 2.9.1 Llama 3 70B?
4 devices with unified memory can run Dolphin 2.9.1 Llama 3 70B at BF16 (142.1 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.