What are the hardware requirements for Fastchat T5 3B V1.0 Ct2 Int8?

Fastchat T5 3B V1.0 Ct2 Int8 requires approximately 2.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Fastchat T5 3B V1.0 Ct2 Int8 and how large is it?

Fastchat T5 3B V1.0 Ct2 Int8 is developed by jncraton, a model with 3b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Fastchat T5 3B V1.0 Ct2 Int8 perform on standard benchmarks?

Fastchat T5 3B V1.0 Ct2 Int8 has the following published scores: LMSYS ELO 992. Compare against reference models on this page or on the LLM Explorer leaderboards.

Fastchat T5 3B V1.0 Ct2 Int8 by jncraton — VRAM 2.9GB

Name: Fastchat T5 3B V1.0 Ct2 Int8
Author: jncraton

Fastchat T5 3B V1.0 Ct2 Int8 is an open-source language model by jncraton. Features: 3b LLM, VRAM: 2.9GB, License: apache-2.0, LLM Explorer Score: 0.17, ELO: 992.

Region:us

Model Card on HF 🤗: https://huggingface.co/jncraton/fastchat-t5-3b-v1.0-ct2-int8

Fastchat T5 3B V1.0 Ct2 Int8 Benchmarks

LMSys ELO 992 vs 1272 (so35) -22%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Fastchat T5 3B V1.0 Ct2 Int8 Parameters and Internals

Model Type

chatbot, text generation

Use Cases

Primary Use Cases:

Commercial usage of large language models, Chatbot for various purposes, Research purposes

Training Details

Data Sources:

ShareGPT.com

Data Volume:

70K conversations

Methodology:

The model is fine-tuned on user-shared conversations collected from ShareGPT. It uses the encoder-decoder transformer architecture where the encoder bi-directionally encodes a question and the decoder generates an answer.

Model Architecture:

Encoder-decoder transformer architecture. The encoder bi-directionally encodes questions while the decoder utilizes cross-attention and autoregressively generates answers.

LLM Name	Fastchat T5 3B V1.0 Ct2 Int8
Repository 🤗	https://huggingface.co/jncraton/fastchat-t5-3b-v1.0-ct2-int8
Model Size	3b
Required VRAM	2.9 GB
Updated	2026-08-06
Maintainer	jncraton
Model Files	2.9 GB
Model Architecture	AutoModel
License	apache-2.0
Model Max Length	512
Tokenizer Class	T5Tokenizer
Padding Token	<pad>

Rank the Fastchat T5 3B V1.0 Ct2 Int8 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 jncraton/fastchat-t5-3b-v1.0-ct2-int8.