[whatmodel.sh](../../README.md) / Yi 1.5 6B Chat
# Yi 1.5 6B Chat
01.AI · released 2024-05 · 6.06B params · apache-2.0
**score 38.3** ±1.6 · #593 of 732 · from 6 benchmark results across 5 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Yi 1.5 6B Chat among every model on that task or test, worst to best.
other tests (6)
test result vs the others in its run difficulty counts why
WildBench v2 WB-Score (task macro) 23.3181 WB-Score ▁·▁▁·●█▄▇▆▅▆ beats 5/52 avg 43.019 WB-Score 28% sharp
BigCodeBench (Complete) 33.8% ▂▁▁▄●▅▇█▆▂▂▂ beats 14/58 medium · avg 48% 25% at its level
BigCodeBench (Instruct) 25.5% ▃●·▆▆██▆▅▃▃▃ beats 2/33 medium · avg 39% 23% typical
Polish EQ-Bench v2 (SpeakLeash) 5.2% ●··▁▁▂▂▆▅▆█▆ beats 0/70 medium · avg 62% 15% at its level
Open PT-LLM Leaderboard average (… 62.6% ▃▁▁▁▁▁▁▁●█▅▁ beats 98/276 medium · avg 72% 5.6% at its level · noisy
Vectara hallucination leaderboard… 92.1% ▁▁▂▃●▄█▆▃▂▂▁ beats 37/140 very easy · avg 94% 2.8% blunt · noisy
source results share of the score
BigCodeBench paper 2 48% ▇▇▇▇▇▇
WildBench v2 leaderboard data 1 28% ▇▇▇
SpeakLeash Polish EQ-Bench leaderboard 1 15% ▇▇
Open Portuguese LLM Leaderboard 1 6% ▇
Vectara hallucination leaderboard 1 3% ▇
prior: pull toward the middle 1% ▇
weighted average = 38.3
Licences: BigCodeBench paper ([CC BY 4.0](http://creativecommons.org/licenses/by/4.0/)) · WildBench v2 leaderboard data ([Apache-2.0](https://github.com/allenai/WildBench/blob/d6b8dcaf377d173d031980f97c16e1a82618c03d/LICENSE)) · SpeakLeash Polish EQ-Bench leaderboard ([Apache-2.0](../../licenses/hf-leaderboard-spaces-Apache-2.0.txt)) · Open Portuguese LLM Leaderboard ([Apache-2.0](../../licenses/hf-leaderboard-spaces-Apache-2.0.txt)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0))
## How to run it
### llama.cpp (recommended)
1. Install llama.cpp. Homebrew and winget installs name the commands llama-cli and llama-server instead. [Other ways to install](https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md)
```sh
# macOS / Linux
curl -LsSf https://llama.app/install.sh | sh
# Windows
irm https://llama.app/install.ps1 | iex
```
2. Run Yi 1.5 6B Chat (Q4_K_M, needs ~3.7 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/Yi-1.5-6B-Chat-GGUF/tree/c2a95a00ae640837fa27ada00b9d8212da4e1355))
```sh
llama cli -hf lmstudio-community/Yi-1.5-6B-Chat-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf lmstudio-community/Yi-1.5-6B-Chat-GGUF:Q4_K_M
```
Other versions: Q8_0 (~6.4 GB) `llama cli -hf lmstudio-community/Yi-1.5-6B-Chat-GGUF:Q8_0`
### LM Studio
1. Install LM Studio. Open the app once before using the lms command. [Download it (macOS / Windows / Linux)](https://lmstudio.ai/download)
2. Run Yi 1.5 6B Chat (Q4_K_M, needs ~3.7 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/Yi-1.5-6B-Chat-GGUF/tree/c2a95a00ae640837fa27ada00b9d8212da4e1355))
```sh
lms get https://huggingface.co/lmstudio-community/Yi-1.5-6B-Chat-GGUF@Q4_K_M -y
```
3. Then run lms ls to see its name, and lms chat followed by that name
Other versions: Q8_0 (~6.4 GB) `lms get https://huggingface.co/lmstudio-community/Yi-1.5-6B-Chat-GGUF@Q8_0 -y` · 4bit (~3.4 GB, Mac only) `lms get https://huggingface.co/mlx-community/Yi-1.5-6B-Chat-4bit -y` · 8bit (~6.4 GB, Mac only) `lms get https://huggingface.co/mlx-community/Yi-1.5-6B-Chat-8bit -y`
### Ollama
1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download)
```sh
# Linux
curl -fsSL https://ollama.com/install.sh | sh
```
2. Run Yi 1.5 6B Chat (Q4_K_M, needs ~4.14 GB, from [ollama.com](https://ollama.com/library/yi/tags))
```sh
ollama run yi:6b-chat-v1.5-q4_K_M
```
Other versions: Q8_0 (~7.77 GB) `ollama run yi:6b-chat-v1.5-q8_0`
### MLX (Mac)
1. Install MLX (Mac). Apple silicon Macs only, text only.
```sh
# with uv
uv tool install mlx-lm
# or
pip install mlx-lm
```
2. Run Yi 1.5 6B Chat (4bit, needs ~3.4 GB, Mac only, from [huggingface.co/mlx-community](https://huggingface.co/mlx-community/Yi-1.5-6B-Chat-4bit/tree/0177c9a12b869d6bc73f772b5a1981a7c966adb6))
```sh
mlx_lm.chat --model mlx-community/Yi-1.5-6B-Chat-4bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model mlx-community/Yi-1.5-6B-Chat-4bit
```
Other versions: 8bit (~6.4 GB, Mac only) `mlx_lm.chat --model mlx-community/Yi-1.5-6B-Chat-8bit`
Model repository and documentation: [huggingface.co/01-ai](https://huggingface.co/01-ai/Yi-1.5-6B-Chat)
[interactive version](https://whatmodel.sh/model/yi-1-5-6b-chat) · [JSON](https://whatmodel.sh/api?format=json&all=1)