What are the hardware requirements for St3 Response Sft?

St3 Response Sft requires approximately 1.5 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 St3 Response Sft and how large is it?

St3 Response Sft is developed by SaketR1, a model with 0.8b 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 St3 Response Sft?

St3 Response Sft is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

St3 Response Sft by SaketR1 — VRAM 1.5GB, 256K context

Name: St3 Response Sft
Author: SaketR1

St3 Response Sft is an open-source language model by SaketR1. Features: 0.8b LLM, VRAM: 1.5GB, Context: 256K, LLM Explorer Score: 0.24.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-0.8b Conversational Endpoints compatible Generated from trainer Qwen3 5 text Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/SaketR1/st3-response-sft

St3 Response Sft Parameters and Internals

LLM Name	St3 Response Sft
Repository 🤗	https://huggingface.co/SaketR1/st3-response-sft
Model Name	st3-response-sft
Base Model(s)	Qwen/Qwen3.5-0.8B Qwen/Qwen3.5-0.8B
Model Size	0.8b
Required VRAM	1.5 GB
Updated	2026-05-29
Maintainer	SaketR1
Model Type	qwen3_5_text
Model Files	1.5 GB 0.0 GB
Model Architecture	Qwen3_5ForCausalLM
Context Length	262144
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the St3 Response 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

Best Alternatives to St3 Response Sft

Best Alternatives	Context / RAM	Downloads	Likes
Decider 0.8B	256K / 1.5 GB	16026	7
ThinCtx Qwen3.5 0.8B	256K / 0.1 GB	2916	1
Basal Omni Pico	256K / 1.5 GB	97	2
Jev Decisions V1 Model	256K / 1.5 GB	514	1
Starlight Small 1	256K / 1.5 GB	495	0
Unee 0.8B	256K / 1.5 GB	407	0
...en3.5 0.8B PureText ZH EN V5.2	256K / 1.4 GB	387	0
Qwen3.5 0.8B Fable GPT6	256K / 1.5 GB	177	0
PrimeMind 0.8B	256K / 1.5 GB	232	2
Qwen 3.5 0.8B Hedgehog	256K / 1.5 GB	438	0

Note: green Score (e.g. "73.2") means that the model is better than SaketR1/st3-response-sft.