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StableLM Zephyr 3B

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StableLM Zephyr 3B is an open-weights language model from Stability AI, released November 2023. Its published size is 2.8B parameters and a 4k-token context window. Licence: other.

Catalogue identity notes

stabilityai/stablelm-zephyr-3b @fe1fd5e (created 2023-11-21, licence other). Independent row: Open PT-LLM (Portuguese) leaderboard average.

Model information sources

Release date ↗ · Weights licence ↗

HF safetensors metadata 2,795,443,200 parameters.

38.7±6.6#734 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 StableLM Zephyr 3B, out of 1132 with a score, then more from Stability AI.

#modelscorewhereRAMreleased
896MAP-Neo 7B Instruct v0.1 M-A-P39±3local~6.4GB2024-05
897Falcon-H1 3B Instruct TII39±4local~3.4GB2025-05
898StableLM Zephyr 3B Stability AI39±7local~3.2GB2023-11
899Phi-2 (2.7B) Microsoft39±1local~3.2GB2023-12
900Granite 3.0 2B Instruct IBM39±1local~3.2GB2024-10
more from Stability AI
661Stable LM 2 12B Chat Stability AI47±6local~8.9GB2024-04
879Stable LM 2 Zephyr 1.6B Stability AI40±7local~2.5GB2024-01
948Stable LM 2 1.6B Chat Stability AI36±7local~2.5GB2024-04

see all LLMs · find the ones that fit your machine

$ what it's good at

other tests1 not in a task · 81% of its score
testresultvs the others in its rundifficultycountswhy
Open PT-LLM Leaderboard average (9 Portuguese tasks)54.4% ✎▃▁▁▁▁▁▁▃▂█▅▁ beats 75/276medium · avg 73%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 81%at its level · noisy

$ 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 StableLM Zephyr 3B · needs ~1.7 GB · from huggingface.co/TheBloke
    chat in the terminal
    llama cli -hf TheBloke/stablelm-zephyr-3b-GGUF:Q4_K_M
  3. Or start a local server and open the address it prints (http://localhost:9931)
    llama serve -hf TheBloke/stablelm-zephyr-3b-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 StableLM Zephyr 3B · needs ~1.7 GB · from huggingface.co/TheBloke

    open in LM Studio ↗

  3. Or download it in the terminal
    lms get https://huggingface.co/TheBloke/stablelm-zephyr-3b-GGUF@Q4_K_M -y
  4. Then run lms ls to see its name, and lms chat followed by that name

Ollama

  1. Install Ollama

    download it (macOS / Windows) ↗

    Linux
    curl -fsSL https://ollama.com/install.sh | sh
  2. Run StableLM Zephyr 3B · needs ~1.6 GB · from ollama.com
    chat in the terminal
    ollama run stablelm-zephyr:3b

Official weights and documentation: huggingface.co/stabilityai ↗

$ how the score was worked out · Open Portuguese LLM Leaderboa… 81%

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
Open Portuguese LLM Leaderboard (archived)1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 81%Apache-2.0
prior · pull toward the middle▇▇▇▇▇▇ 19%
weighted average= 38.7

$ 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