What are the hardware requirements for FastContext 1.0 4B SFT?

FastContext 1.0 4B SFT requires approximately 8.1 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 FastContext 1.0 4B SFT and how large is it?

FastContext 1.0 4B SFT is developed by ShaunGves, 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 FastContext 1.0 4B SFT?

FastContext 1.0 4B SFT is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

FastContext 1.0 4B SFT by ShaunGves — VRAM 8.1GB, 256K context

Name: FastContext 1.0 4B SFT
Author: ShaunGves

FastContext 1.0 4B SFT is an open-source language model by ShaunGves. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: mit, Instruction-Based, LLM Explorer Score: 0.27.

Arxiv:2606.14066 Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-4b-instr... Conversational En Endpoints compatible Explorer subagent Instruct Qwen3 Region:us Repository exploration Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ShaunGves/FastContext-1.0-4B-SFT

FastContext 1.0 4B SFT Parameters and Internals

LLM Name	FastContext 1.0 4B SFT
Repository 🤗	https://huggingface.co/ShaunGves/FastContext-1.0-4B-SFT
Base Model(s)	Qwen3 4B Instruct 2507 Qwen/Qwen3-4B-Instruct-2507
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-07-25
Maintainer	ShaunGves
Model Type	qwen3
Instruction-Based	Yes
Model Files	5.4 GB: 0-of-2 2.7 GB: 1-of-2
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	mit
Context Length	262144
Model Max Length	262144
Transformers Version	4.51.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the FastContext 1.0 4B SFT 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

Quantized Models of the FastContext 1.0 4B SFT

Model	Likes	Downloads	VRAM
FastContext 1.0 4B SFT 8bit	1	120	4 GB

Best Alternatives to FastContext 1.0 4B SFT

Best Alternatives	Context / RAM	Downloads	Likes
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
Fable Traces	256K / 8.1 GB	295	210
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
...pt Full Qwen3 4b Instruct 2507	256K / 8 GB	365	1
Nexa AI 4B Instruct	256K / 8 GB	576	2
Neuron 4B Instruct	256K / 8.1 GB	313	1
Agents K1	256K / 8.8 GB	1098	28
Karnak 6B V1.0	256K / 11.9 GB	1020	1

Note: green Score (e.g. "73.2") means that the model is better than ShaunGves/FastContext-1.0-4B-SFT.