[whatmodel.sh](../../README.md) / Starling-LM 7B beta
# Starling-LM 7B beta
Nexusflow · released 2024-03 · 7.24B params · apache-2.0
**score 41.5** ±1.0 · #540 of 732 · from 11 benchmark results across 9 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Starling-LM 7B beta among every model on that task or test, worst to best.
task vs the others rank counts tests
chat & writing ▁▁▁▃●▄▆█▆▇▇▃ #334 of 402 34% 3
chat & writing · #334 of 402 · 34% of its score
Beats [OpenThinker3 7B](openthinker3-7b.md), [Code Llama 70B Instruct](codellama-70b-instruct.md), [Gemma 4 E2B](gemma-4-e2b.md) here, though they rank higher overall. Trails [LFM2 350M](lfm2-350m.md), [Gemma 3 1B](gemma-3-1b.md), [Qwen3 0.6B](qwen3-0-6b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena-Hard (v0.1, GPT-4-1106 judg… 23.0% ▂▁▁▅●▅▄▃▃▅▃▁ beats 18/60 medium · avg 47% 14% sharp
LMArena (text) 1171.0 ▁▁▁▂●▃▃▆▆▇█▃ beats 50/385 avg 1260 10% blunt
Polyrating rating (bias-aware re-… 1111.0 ▂▁▂▁▃▇█●▇▄▂▂ beats 52/95 avg 1187 10% typical
other tests (8)
test result vs the others in its run difficulty counts why
LiveBench 2024-07-26 16.6% ▁▁▁▂●▃▂█▆▃▅▃ beats 9/61 medium · avg 38% 31% typical
WildBench v2 WB-Score (task macro) 30.1694 WB-Score ▁·▁▁·▃●▄▇▆▅▆ beats 15/52 avg 43.019 WB-Score 11% sharp
MedQA (USMLE, 4 options) 52.5% ▁▁··▄▁▁··▄●█ beats 11/17 medium · avg 71% 8.7% sharp · at its level
Polish EQ-Bench v2 (SpeakLeash) 45.1% ▁··▁▁▂▂●▅▆█▆ beats 14/70 medium · avg 62% 6.3% at its level
MedMCQA 50.2% ▂▂··▄▄▂▂·▄●█ beats 13/17 medium · avg 63% 4.0% at its level
Open PT-LLM Leaderboard average (… 70.9% ▃▁▁▁▁▁▁▁▂●▅▁ beats 175/276 medium · avg 72% 2.4% at its level · noisy
EuroEval Life in the UK (English … 82.8% ▁▁▁▁▁▁▁▂▄●▄▃ beats 81/146 easy · avg 82% 1.7% at its level · noisy
PubMedQA 78.2% ▂·▂▆·▄▂▄▄▂█● beats 17/17 medium · avg 75% 0.5% blunt · at its level
source results share of the score
LiveBench model judgments 1 31% ▇▇▇▇
Arena-Hard-Auto v0.1 leaderboard 1 14% ▇▇
Open Medical-LLM Leaderboard results 3 13% ▇▇
WildBench v2 leaderboard data 1 11% ▇
LMArena leaderboard dataset 1 10% ▇
Polyrating: A Cost-Effective and Bias-A… 1 10% ▇
SpeakLeash Polish EQ-Bench leaderboard 1 6% ▇
Open Portuguese LLM Leaderboard 1 2% ▇
EuroEval leaderboards 1 2% ▇
prior: pull toward the middle 0% ▇
weighted average = 41.5
Licences: LiveBench model judgments ([Apache-2.0 (stated in the LiveBench datasheet)](https://www.apache.org/licenses/LICENSE-2.0)) · Arena-Hard-Auto v0.1 leaderboard ([Apache-2.0](../../licenses/arena-hard-auto-v0-1-Apache-2.0.txt)) · Open Medical-LLM Leaderboard results ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)) · WildBench v2 leaderboard data ([Apache-2.0](https://github.com/allenai/WildBench/blob/d6b8dcaf377d173d031980f97c16e1a82618c03d/LICENSE)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · 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)) · EuroEval leaderboards ([MIT](https://github.com/EuroEval/leaderboards/blob/1a77f1d2f8ba1ba05ab73287fb090d76bf41b2e0/LICENSE))
## 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 Starling-LM 7B beta (Q4_K_M, needs ~4.4 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/Starling-LM-7B-beta-GGUF/tree/a080ea29e1798deffd25bde0c218dcad7d9dd64c))
```sh
llama cli -hf lmstudio-community/Starling-LM-7B-beta-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/Starling-LM-7B-beta-GGUF:Q4_K_M
```
Other versions: Q8_0 (~7.7 GB) `llama cli -hf lmstudio-community/Starling-LM-7B-beta-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 Starling-LM 7B beta (Q4_K_M, needs ~4.4 GB, from [huggingface.co/lmstudio-community](https://huggingface.co/lmstudio-community/Starling-LM-7B-beta-GGUF/tree/a080ea29e1798deffd25bde0c218dcad7d9dd64c))
```sh
lms get https://huggingface.co/lmstudio-community/Starling-LM-7B-beta-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 (~7.7 GB) `lms get https://huggingface.co/lmstudio-community/Starling-LM-7B-beta-GGUF@Q8_0 -y` · 4bit (~4.3 GB, Mac only) `lms get https://huggingface.co/mlx-community/Starling-LM-7B-beta-4bit -y` · 8bit (~7.8 GB, Mac only) `lms get https://huggingface.co/mlx-community/Starling-LM-7B-beta-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 Starling-LM 7B beta (Q4_K_M, needs ~4.84 GB, from [ollama.com](https://ollama.com/library/starling-lm/tags))
```sh
ollama run starling-lm:7b-beta-q4_K_M
```
Other versions: Q8_0 (~9.19 GB) `ollama run starling-lm:7b-beta-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 Starling-LM 7B beta (4bit, needs ~4.3 GB, Mac only, from [huggingface.co/mlx-community](https://huggingface.co/mlx-community/Starling-LM-7B-beta-4bit/tree/03264990e1dd1b6fd4853004c59631a5f432c9c8))
```sh
mlx_lm.chat --model mlx-community/Starling-LM-7B-beta-4bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model mlx-community/Starling-LM-7B-beta-4bit
```
Other versions: 8bit (~7.8 GB, Mac only) `mlx_lm.chat --model mlx-community/Starling-LM-7B-beta-8bit`
Model repository and documentation: [huggingface.co/Nexusflow](https://huggingface.co/Nexusflow/Starling-LM-7B-beta)
[interactive version](https://whatmodel.sh/model/starling-lm-7b-beta) · [JSON](https://whatmodel.sh/api?format=json&all=1)