What are the hardware requirements for Team Cognilex Qwen35 4B Synthetic Qa Instruct?

Team Cognilex Qwen35 4B Synthetic Qa Instruct requires approximately 9.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Team Cognilex Qwen35 4B Synthetic Qa Instruct and how large is it?

Team Cognilex Qwen35 4B Synthetic Qa Instruct is developed by SinhalaMMLU-SharedTask, a model with 4b 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 Team Cognilex Qwen35 4B Synthetic Qa Instruct?

Team Cognilex Qwen35 4B Synthetic Qa Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Team Cognilex Qwen35 4B Synthetic Qa Instruct by SinhalaMMLU-SharedTask — VRAM 9.3GB

Name: Team Cognilex Qwen35 4B Synthetic Qa Instruct
Author: SinhalaMMLU-SharedTask

Team Cognilex Qwen35 4B Synthetic Qa Instruct is an open-source language model by SinhalaMMLU-SharedTask. Features: 4b LLM, VRAM: 9.3GB, Instruction-Based, LLM Explorer Score: 0.29.

Conversational Endpoints compatible Image-text-to-text Instruct Qwen Qwen3.5 Qwen3 5 Region:us Safetensors Sharded Si Sinhala Synthetic-qa Tensorflow

Model Card on HF 🤗: https://huggingface.co/SinhalaMMLU-SharedTask/team-cognilex-qwen35-4b-synthetic-qa-instruct

Team Cognilex Qwen35 4B Synthetic Qa Instruct Parameters and Internals

LLM Name	Team Cognilex Qwen35 4B Synthetic Qa Instruct
Repository 🤗	https://huggingface.co/SinhalaMMLU-SharedTask/team-cognilex-qwen35-4b-synthetic-qa-instruct
Model Size	4b
Required VRAM	9.3 GB
Updated	2026-10-30
Maintainer	SinhalaMMLU-SharedTask
Model Type	qwen3_5
Instruction-Based	Yes
Model Files	5.3 GB: 1-of-2 4.0 GB: 2-of-2
Supported Languages	si
Model Architecture	Qwen3_5ForConditionalGeneration
Model Max Length	262144
Transformers Version	5.17.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Team Cognilex Qwen35 4B Synthetic Qa Instruct capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Team Cognilex Qwen35 4B Synthetic Qa Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Jugurtha 4B	0K / 9.3 GB	123	4
...Qwen3.5 4B 50Langs Instruct V1	0K / 8.4 GB	1669	1
Tmax 4B	0K / 8.4 GB	517	5
Qwen3.5 4B VerIH Step200	0K / 18.2 GB	192	0
Omni Edu 4B	0K / 9.1 GB	39	0
ReAligned Qwen3.5 4B	0K / 9.1 GB	126	2

Note: green Score (e.g. "73.2") means that the model is better than SinhalaMMLU-SharedTask/team-cognilex-qwen35-4b-synthetic-qa-instruct.