What are the hardware requirements for Carnice 9B Function Calling XLAM Unsloth?

Carnice 9B Function Calling XLAM Unsloth requires approximately 17.9 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Carnice 9B Function Calling XLAM Unsloth and how large is it?

Carnice 9B Function Calling XLAM Unsloth is developed by ermiaazarkhalili, a model with 9b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Carnice 9B Function Calling XLAM Unsloth?

Carnice 9B Function Calling XLAM Unsloth is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Carnice 9B Function Calling XLAM Unsloth by ermiaazarkhalili — VRAM 17.9GB, 256K context

Name: Carnice 9B Function Calling XLAM Unsloth
Author: ermiaazarkhalili

Carnice 9B Function Calling XLAM Unsloth is an open-source language model by ermiaazarkhalili. Features: 9b LLM, VRAM: 17.9GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.23.

Base model:adapter:kai-os/carn... Base model:kai-os/carnice-9b Conversational Dataset:salesforce/xlam-functi... En Endpoints compatible Finetuned Function-calling Gemma2 Lora Peft Qwen3 5 text Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/ermiaazarkhalili/Carnice-9B-Function-Calling-xLAM-Unsloth

Carnice 9B Function Calling XLAM Unsloth Parameters and Internals

LLM Name	Carnice 9B Function Calling XLAM Unsloth
Repository 🤗	https://huggingface.co/ermiaazarkhalili/Carnice-9B-Function-Calling-xLAM-Unsloth
Model Name	kai-os/Carnice-9b
Base Model(s)	Carnice 9B kai-os/Carnice-9b
Model Size	9b
Required VRAM	17.9 GB
Updated	2026-08-08
Maintainer	ermiaazarkhalili
Model Type	qwen3_5_text
Model Files	9.9 GB: 1-of-2 8.0 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Torch Data Type	bfloat16
Errors	replace

Rank the Carnice 9B Function Calling XLAM Unsloth capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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...thos 9B V2 Heretic Abliterated	1024K / 17.9 GB	80	3
Le Gros Chaton	256K / 17.9 GB	235	1
NeoHorse 1 9B	256K / 18 GB	1250	196
...yber Ornith 1.5 9B OBLITERATED	256K / 17.9 GB	1424	7
JEV 9B	256K / 17.8 GB	471	12
...te Qwopus MiMo Ornith 9B Coder	256K / 17.8 GB	439	6
WikiQwen 9B	256K / 17.9 GB	1039	0
JevK5 9B	256K / 17.9 GB	683	1
PentaCoder 9B	256K / 17.9 GB	293	2
Qwen3.5 9B OutsideTheBox SFT	256K / 17.9 GB	409	0

Note: green Score (e.g. "73.2") means that the model is better than ermiaazarkhalili/Carnice-9B-Function-Calling-xLAM-Unsloth.