whatmodel.sh / Functionary Small v3.1
Functionary Small v3.1
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Functionary Small v3.1 is an open-weights language model from MeetKai, released July 2024. Its published size is 8.03B parameters. Licence: mit.
Catalogue identity notes
Maker repo meetkai/functionary-small-v3.1 @8e43bc1: licence tag mit. 8,030,261,248 parameters from the Hugging Face safetensors metadata (dense, so active = total). Released 2024-07: month the maker's Hugging Face repo was created (createdAt 2024-07-26).
$ how it compares
The LLMs ranked either side of Functionary Small v3.1, out of 1132 with a score, then more from MeetKai.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 485 |  Jamba 1.6 Mini | 53±10 | local | ||
| 486 |  Olmo 3 7B Think | 53±1 | local | ||
| 487 | Functionary Small v3.1 | 53±6 | local | ||
| 488 |  GPT-4.1 nano | 53±1 | api $0.17/M | ||
| 489 |  Gemini 1.5 Flash (002) | 53±1 | comparison only | ||
| more from MeetKai | |||||
| 341 | Functionary Medium v3.1 | 58±7 | local | ||
$ what it's good at
agent tasks▁▁▃▆█▆▅▄▄▃▂▁ #250 of 334 * · 82% of its score · 1 test
Beats o3-mini, Nova 2 Lite, Ministral 3 14B Reasoning 2512 here, though they rank higher overall. Trails SmolLM3 3B, Phi-3.5-mini-instruct, Jamba 1.5 Mini here, though they rank lower overall.
$ where to run it
llama.cpp · recommended
version
- 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 | shWindowsirm https://llama.app/install.ps1 | iex - Run Functionary Small v3.1 · needs ~4.9 GB · from huggingface.co/bartowskichat in the terminal
llama cli -hf bartowski/functionary-small-v3.1-GGUF:Q4_K_M - Or start a local server and open the address it prints (http://localhost:9931)
llama serve -hf bartowski/functionary-small-v3.1-GGUF:Q4_K_M
LM Studio
version
- Install LM Studio · Open the app once before using the lms command.
- Run Functionary Small v3.1 · needs ~4.9 GB · from huggingface.co/bartowski
- Or download it in the terminal
lms get https://huggingface.co/bartowski/functionary-small-v3.1-GGUF@Q4_K_M -y - Then run lms ls to see its name, and lms chat followed by that name
Ollama
version
- Install Ollama
download it (macOS / Windows) ↗
Linuxcurl -fsSL https://ollama.com/install.sh | sh - Run Functionary Small v3.1 · needs ~4.9 GB · from huggingface.co/bartowskichat in the terminal
ollama run hf.co/bartowski/functionary-small-v3.1-GGUF:Q4_K_M
Other ways to run it
- Run it as published · needs ~16.06 GB · from huggingface.co/meetkai (official)
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='meetkai/functionary-small-v3.1', torch_dtype='auto', device_map='auto', trust_remote_code=True)('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
Official weights and documentation: huggingface.co/meetkai ↗
$ how the score was worked out · Berkeley Function Calling Lea… 82%
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
| source | results | share of the score |
|---|---|---|
 Berkeley Function Calling Leaderboard result archive | 1 | 82% |
| prior · pull toward the middle | 18% | |
| weighted average | = 52.9 |
$ improve this page
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