What are the hardware requirements for Navya 1c Sft?

Navya 1c Sft requires approximately 5.3 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Navya 1c Sft and how large is it?

Navya 1c Sft is developed by navyam-ai, a model with 1.3b 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 Navya 1c Sft?

Navya 1c Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Navya 1c Sft by navyam-ai — VRAM 5.3GB, 4K context

Name: Navya 1c Sft
Author: navyam-ai

Navya 1c Sft is an open-source language model by navyam-ai. Features: 1.3b LLM, VRAM: 5.3GB, Context: 4K, License: apache-2.0, LLM Explorer Score: 0.3.

En Endpoints compatible Finance From-scratch Hi India Llama Navya Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/navyam-ai/navya-1c-sft

Navya 1c Sft Parameters and Internals

LLM Name	Navya 1c Sft
Repository 🤗	https://huggingface.co/navyam-ai/navya-1c-sft
Model Size	1.3b
Required VRAM	5.3 GB
Updated	2026-09-10
Maintainer	navyam-ai
Model Type	llama
Model Files	5.0 GB: 1-of-2 0.3 GB: 2-of-2
Supported Languages	en hi
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.57.6
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|pad\|>
Vocabulary Size	65536

Rank the Navya 1c Sft 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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