whatmodel.sh / AceGPT-13B-chat

AceGPT-13B-chat

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AceGPT-13B-chat is an open-weights language model from FreedomIntelligence (CUHK-SZ), released September 2023. Licence: apache-2.0.

Catalogue identity notes

Maker repo FreedomIntelligence/AceGPT-13B-chat @ab87ccb: licence tag apache-2.0. Released 2023-09: month the maker's Hugging Face repo was created (createdAt 2023-09-21).

43.6±3.1#630 of 949 LLMsfrom 2 benchmark results across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of AceGPT-13B-chat, out of 1132 with a score, then more from FreedomIntelligence (CUHK-SZ).

#modelscorewhereRAMreleased
784Code Llama 70B Python Meta44±1local~28GB2024-01
785Llama 3.1 8B (base) Meta44±3local~6.2GB2024-07
786AceGPT-13B-chat FreedomIntelligence (CUHK-SZ)44±3local~47GB2023-09
787HuatuoGPT-o1-8B FreedomIntelligence (CUHK-SZ)44±5local~6.2GB2024-12
788LFM2.5 1.2B Instruct Liquid AI44±2local~2.2GB2026-01
more from FreedomIntelligence (CUHK-SZ)
318HuatuoGPT-o1-72B FreedomIntelligence (CUHK-SZ)59±4local~28GB2024-12
432HuatuoGPT-o1-70B FreedomIntelligence (CUHK-SZ)55±4local~22GB2024-12
522AceGPT-v2-8B-Chat FreedomIntelligence (CUHK-SZ)52±5local~6.6GB2024-06

see all LLMs · find the ones that fit your machine

$ what it's good at

chat & writing▁▁▁▄▆▅▆█▆▆▆▂ #318 of 466 * · 65% of its score · 1 test

Beats Ministral 3 14B Reasoning 2512, Gemma 4 E4B, Ministral 3 8B here, though they rank higher overall. Trails Flan-T5 XXL, LFM2 700M, EXAONE 3.5 2.4B Instruct here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Arabic IFEval prompt-level (Inception)32.7% ✎▁·▁▁▂▁▄▄▆▄█▄ beats 18/38medium · avg 49%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 65%sharp · at its level
other tests1 not in a task · 30% of its score
testresultvs the others in its rundifficultycountswhy
AraGen-v3 3C3H score (Inception, Claude Sonnet 4 judge)15.9% ✎▁▁·▁▂▂▄█▄▅▄▄ beats 12/66hard · avg 31%▇▇▇▇▇▇▇▇▇▇▇▇ 30%typical

$ where to run it

Other ways to run it

  1. Run it as published · needs ~43.65 GB · from huggingface.co/FreedomIntelligence (official)
    uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='FreedomIntelligence/AceGPT-13B-chat', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"

Official weights and documentation: huggingface.co/FreedomIntelligence ↗

$ how the score was worked out · Inception Arabic/Hindi leader… 96%

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
Inception Arabic/Hindi leaderboards (AraGen-v3, HindiGen-v1, Arabic IFEval)2▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 96%Apache-2.0
prior · pull toward the middle▇ 4%
weighted average= 43.6

$ 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