What are the hardware requirements for Cevher2 Test 3?

Cevher2 Test 3 requires approximately 3 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Cevher2 Test 3 and how large is it?

Cevher2 Test 3 is developed by bcckfdn, a model with 1.5b 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 Cevher2 Test 3?

Cevher2 Test 3 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Cevher2 Test 3 by bcckfdn — VRAM 3GB, 8K context

Name: Cevher2 Test 3
Author: bcckfdn

Cevher2 Test 3 is an open-source language model by bcckfdn. Features: 1.5b LLM, VRAM: 3GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.27.

Conversational En Endpoints compatible Llama Pretrained-from-scratch Region:us Safetensors Smollm2 Tr Turkish

Model Card on HF 🤗: https://huggingface.co/bcckfdn/cevher2-test-3

Cevher2 Test 3 Parameters and Internals

LLM Name	Cevher2 Test 3
Repository 🤗	https://huggingface.co/bcckfdn/cevher2-test-3
Model Size	1.5b
Required VRAM	3 GB
Updated	2026-10-15
Maintainer	bcckfdn
Model Type	llama
Model Files	3.0 GB
Supported Languages	tr en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.46.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Vocabulary Size	65536
Torch Data Type	bfloat16

Rank the Cevher2 Test 3 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

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Note: green Score (e.g. "73.2") means that the model is better than bcckfdn/cevher2-test-3.