whatmodel.sh / Bielik Minitron 7B v3.0 Instruct

Bielik Minitron 7B v3.0 Instruct

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Bielik Minitron 7B v3.0 Instruct is an open-weights language model from SpeakLeash, released January 2026. Its published size is 7.48B parameters. Licence: apache-2.0.

Catalogue identity notes

Maker repo speakleash/Bielik-Minitron-7B-v3.0-Instruct @5808ff0: licence tag apache-2.0. 7,477,727,232 parameters from the Hugging Face safetensors metadata (dense, so active = total). Released 2026-01: month the maker's Hugging Face repo was created (createdAt 2026-01-22). Gated repository (licence acceptance required on Hugging Face).

51.0±4.0#416 of 949 LLMsfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of Bielik Minitron 7B v3.0 Instruct, out of 1132 with a score, then more from SpeakLeash.

#modelscorewhereRAMreleased
542Llama 3.1 Nemotron 51B Instruct NVIDIA51±2local~34GB2024-09
543OpenHands LM 32B v0.1 All Hands AI51±3local~21GB2025-03
544Bielik Minitron 7B v3.0 Instruct SpeakLeash51±4local~5.9GB2026-01
545Ministral 3 3B Reasoning 2512 Mistral51±1local~3.5GB2025-12
546Qwen3 4B Alibaba51±1local~3.7GB2025-04
more from SpeakLeash
427Bielik 11B v3.0 Instruct SpeakLeash55±2local~8.1GB2025-11
445Bielik 11B v2.6 Instruct SpeakLeash54±3local~8.1GB2025-06
473Bielik 11B v2.5 Instruct SpeakLeash53±3local~8.5GB2025-05

see all LLMs · find the ones that fit your machine

$ what it's good at

other tests1 not in a task · 93% of its score
testresultvs the others in its rundifficultycountswhy
CPTUB average (SpeakLeash, 0-5 judge scale) lab67.6% ✎▁▂▂▂▃█▃▆▅▄▂▃ beats 50/95easy · avg 66%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 93%at its level

$ where to run it

llama.cpp · recommended

version

  1. Install llama.cpp · Homebrew and winget installs name the commands llama-cli and llama-server instead.
    macOS / Linux
    curl -LsSf https://llama.app/install.sh | sh
    Windows
    irm https://llama.app/install.ps1 | iex

    other ways to install ↗

  2. Run Bielik Minitron 7B v3.0 Instruct · needs ~4.5 GB · from huggingface.co/speakleash (official)
    chat in the terminal
    llama cli -hf speakleash/Bielik-Minitron-7B-v3.0-Instruct-GGUF:Q4_K_M
  3. Or start a local server and open the address it prints (http://localhost:9931)
    llama serve -hf speakleash/Bielik-Minitron-7B-v3.0-Instruct-GGUF:Q4_K_M

LM Studio

version

  1. Install LM Studio · Open the app once before using the lms command.

    download it (macOS / Windows / Linux) ↗

  2. Run Bielik Minitron 7B v3.0 Instruct · needs ~4.5 GB · from huggingface.co/speakleash (official)

    open in LM Studio ↗

  3. Or download it in the terminal
    lms get https://huggingface.co/speakleash/Bielik-Minitron-7B-v3.0-Instruct-GGUF@Q4_K_M -y
  4. Then run lms ls to see its name, and lms chat followed by that name

Ollama

version

  1. Install Ollama

    download it (macOS / Windows) ↗

    Linux
    curl -fsSL https://ollama.com/install.sh | sh
  2. Run Bielik Minitron 7B v3.0 Instruct · needs ~4.5 GB · from huggingface.co/speakleash (official)
    chat in the terminal
    ollama run hf.co/speakleash/Bielik-Minitron-7B-v3.0-Instruct-GGUF:Q4_K_M

MLX (Mac)

version

  1. Install MLX (Mac) · Apple silicon Macs only, text only.
    with uv
    uv tool install mlx-lm
    or
    pip install mlx-lm
  2. Run Bielik Minitron 7B v3.0 Instruct · needs ~4.2 GB, Mac only · from huggingface.co/lukagra
    chat in the terminal
    mlx_lm.chat --model lukagra/Bielik-Minitron-7B-v3.0-Instruct-mlx-4Bit
  3. Or start an OpenAI-compatible server at http://localhost:8080/v1
    mlx_lm.server --model lukagra/Bielik-Minitron-7B-v3.0-Instruct-mlx-4Bit

Other ways to run it

  1. Run it as published · needs ~14.96 GB · from huggingface.co/speakleash (official)
    uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='speakleash/Bielik-Minitron-7B-v3.0-Instruct', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"

Official weights and documentation: huggingface.co/speakleash ↗

$ how the score was worked out · SpeakLeash CPTUB (Complex Pol… 93%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
SpeakLeash CPTUB (Complex Polish Text Understanding Benchmark) · lab-reported1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 93%MIT
prior · pull toward the middle▇▇ 7%
weighted average= 51.0

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json