[whatmodel.sh](../../README.md) / Bielik 11B v3.0 Instruct
# Bielik 11B v3.0 Instruct
SpeakLeash · released 2025-11 · 11.17B params · apache-2.0
**score 55.2** ±2.1 · #278 of 732 · from 5 benchmark results across 4 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Bielik 11B v3.0 Instruct among every model on that task or test, worst to best.
other tests (5)
test result vs the others in its run difficulty counts why
Polish medical board exams, bias-… 55.8% ▄·▂▂▂··●▂▄·▄ beats 6/13 hard · avg 46% 33% at its level
CPTUB average (SpeakLeash, 0-5 ju… 74.7% ▁▂▂▂▃█▃▆●▄▂▃ beats 68/95 medium · avg 65% 30% at its level
Polish EQ-Bench v2 (SpeakLeash) (… 71.2% ▁··▁▁▂▂▆▅▆●▆ beats 57/70 medium · avg 62% 23% at its level
EuroEval HellaSwag (English), tes… 77.4% ▃·▁▁▂▁▂▅█●▄▁ beats 66/100 medium · avg 67% 7.8% sharp · at its level · noisy
EuroEval Life in the UK (English … 82.7% ▁▁▁▁▁▁▁▂▄●▄▃ beats 80/146 easy · avg 82% 4.2% noisy
source results share of the score
Reassessing High-Performing LLMs on Pol… 1 33% ▇▇▇▇
SpeakLeash CPTUB (submitted / maker-rep… 1 30% ▇▇▇▇
SpeakLeash Polish EQ-Bench leaderboard … 1 23% ▇▇▇
EuroEval leaderboards 2 12% ▇
prior: pull toward the middle 2% ▇
weighted average = 55.2
Licences: Reassessing High-Performing LLMs on Polish Medical Exams: True Competence or Bias-Driven Performance? ([CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)) · SpeakLeash CPTUB ([MIT](../../licenses/hf-leaderboard-spaces-MIT.txt)) · SpeakLeash Polish EQ-Bench 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 Bielik 11B v3.0 Instruct (Q4_K_M, needs ~6.7 GB, from [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-GGUF/tree/518fbbc2e677bf490776e4a98a300a822faca1a2))
```sh
llama cli -hf speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q4_K_M
```
Other versions: Q8_0 (~11.9 GB) `llama cli -hf speakleash/Bielik-11B-v3.0-Instruct-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 Bielik 11B v3.0 Instruct (Q4_K_M, needs ~6.7 GB, from [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-GGUF/tree/518fbbc2e677bf490776e4a98a300a822faca1a2))
```sh
lms get https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-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 (~11.9 GB) `lms get https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-GGUF@Q8_0 -y` · 4bit (~6.3 GB, Mac only) `lms get https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-MLX-4bit -y` · 8bit (~11.9 GB, Mac only) `lms get https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-MLX-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 Bielik 11B v3.0 Instruct (Q4_K_M, needs ~6.7 GB, from [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-GGUF/tree/518fbbc2e677bf490776e4a98a300a822faca1a2))
```sh
ollama run hf.co/speakleash/Bielik-11B-v3.0-Instruct-GGUF:Q4_K_M
```
Other versions: Q8_0 (~11.9 GB) `ollama run hf.co/speakleash/Bielik-11B-v3.0-Instruct-GGUF: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 Bielik 11B v3.0 Instruct (4bit, needs ~6.3 GB, Mac only, from [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct-MLX-4bit/tree/4e62550d51d2e3f61e13d3752c25f630277f53a2))
```sh
mlx_lm.chat --model speakleash/Bielik-11B-v3.0-Instruct-MLX-4bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model speakleash/Bielik-11B-v3.0-Instruct-MLX-4bit
```
Other versions: 8bit (~11.9 GB, Mac only) `mlx_lm.chat --model speakleash/Bielik-11B-v3.0-Instruct-MLX-8bit`
### Other ways to run it
1. Run it as published (BF16, needs ~22.34 GB, from [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct/tree/735bfee1125fe8b497ac2769de94822a11f77167))
```sh
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='speakleash/Bielik-11B-v3.0-Instruct', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
```
Model repository and documentation: [huggingface.co/speakleash](https://huggingface.co/speakleash/Bielik-11B-v3.0-Instruct)
[interactive version](https://whatmodel.sh/model/bielik-11b-v3-0-instruct) · [JSON](https://whatmodel.sh/api?format=json&all=1)