Yi 1.5 6B Chat — Hardware Requirements & GPU Compatibility
Chat
Yi 1.5 6B Chat is a 6.1B-parameter open language model from 01.AI in the Yi 1.5 family. It supports a context window of up to 4,096 tokens. At BF16 it needs about 12.56 GB of VRAM — see which GPUs and Macs can run it below.
8.0K downloads
42 likesSpecifications
- Publisher
- 01.AI
- Family
- Yi 1.5
- Parameters
- 6.1B
- Architecture
- LlamaForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 64,000
- Release Date
- 2024-08-27
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Yi 1.5 6B Chat Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 12.6 GB | 12.7 GB | 12.12 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Yi 1.5 6B Chat?
BF16 · 12.6 GBYi 1.5 6B Chat (BF16) requires 12.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 17+ GB is recommended. Using the full 4K context window can add up to 0.1 GB, bringing total usage to 12.7 GB. 17 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Yi 1.5 6B Chat?
BF16 · 12.6 GB27 devices with unified memory can run Yi 1.5 6B Chat, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Yi 1.5 6B Chat need?
Yi 1.5 6B Chat requires 12.6 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 6.1B × 16 bits ÷ 8 = 12.1 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 0.6 GB (at full 4K context)
VRAM usage by quantization
BF1612.6 GBBF16 + full context12.7 GB- Can I run Yi 1.5 6B Chat on a Mac?
Yi 1.5 6B Chat requires at least 12.6 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 Yi 1.5 6B Chat locally?
Yes — Yi 1.5 6B Chat can run locally on consumer hardware. At BF16 quantization it needs 12.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Yi 1.5 6B Chat?
At BF16, Yi 1.5 6B Chat can reach ~232 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~52 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 ÷ 12.6 × 0.55 = ~232 tok/s
Estimated speed at BF16 (12.6 GB)
~232 tok/s~52 tok/s~174 tok/s~144 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Yi 1.5 6B Chat?
At BF16, the download is about 12.12 GB.
- Which GPUs can run Yi 1.5 6B Chat?
17 consumer GPUs can run Yi 1.5 6B Chat at BF16 (12.6 GB). Top options include AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, AMD Radeon RX 6800. 6 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Yi 1.5 6B Chat?
27 devices with unified memory can run Yi 1.5 6B Chat at BF16 (12.6 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.