What are the hardware requirements for Paradigm 7B?

Paradigm 7B requires approximately 14.4 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Paradigm 7B and how large is it?

Paradigm 7B is developed by ResplendentAI, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Paradigm 7B perform on standard benchmarks?

Paradigm 7B has the following published scores: MMLU 64.02. Compare against reference models on this page or on the LLM Explorer leaderboards.

Paradigm 7B by ResplendentAI — VRAM 14.4GB, 32K context

Name: Paradigm 7B
Author: ResplendentAI

Paradigm 7B is an open-source language model by ResplendentAI. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: cc-by-sa-4.0, Merged, LLM Explorer Score: 0.12, Arc: 73.6, HellaSwag: 88.7, MMLU: 64, GSM8K: 66.8.

Merged Model Base model:chaoticneutrals/eri... Base model:jeiku/alpaca nsfw s... Base model:liminerity/m7-7b Base model:resplendentai/datur... Dataset:resplendentai/alpaca n... Dataset:unalignment/toxic-dpo-... En Endpoints compatible Mistral Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ResplendentAI/Paradigm_7B

Paradigm 7B Parameters and Internals

Model Type

text-generation

Additional Notes

An effective and intelligent RP model designed for user effectiveness as reported and highlighted on the Open LLM Leaderboard.

Training Details

Data Sources:

liminerity/Multiverse-Experiment-slerp-7b, jeiku/Alpaca_NSFW_Shuffled_Mistral, ResplendentAI/Datura_7B, ChaoticNeutrals/Eris_Remix_7B

Methodology:

A merging methodology called 'dare_ties' was used along with weight normalization and specific model weights.

LLM Name	Paradigm 7B
Repository 🤗	https://huggingface.co/ResplendentAI/Paradigm_7B
Base Model(s)	liminerity/Multiverse-Experiment-slerp-7b Alpaca NSFW Shuffled Mistral Datura 7B Eris Remix 7B liminerity/Multiverse-Experiment-slerp-7b jeiku/Alpaca_NSFW_Shuffled_Mistral ResplendentAI/Datura_7B ChaoticNeutrals/Eris_Remix_7B
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-04
Maintainer	ResplendentAI
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Supported Languages	en
Model Architecture	MistralForCausalLM
License	cc-by-sa-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Paradigm 7B 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 Paradigm 7B

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...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than ResplendentAI/Paradigm_7B.