What are the hardware requirements for Matter 0.2 7B DPO?

Matter 0.2 7B DPO requires approximately 14.5 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 Matter 0.2 7B DPO and how large is it?

Matter 0.2 7B DPO is developed by 0-hero, 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 Matter 0.2 7B DPO perform on standard benchmarks?

Matter 0.2 7B DPO has the following published scores: MMLU 62.9. Compare against reference models on this page or on the LLM Explorer leaderboards.

Matter 0.2 7B DPO by 0-hero — VRAM 14.5GB, 32K context

Name: Matter 0.2 7B DPO
Author: 0-hero

Matter 0.2 7B DPO is an open-source language model by 0-hero. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.16, Arc: 63.3, HellaSwag: 83.2, MMLU: 62.9, GSM8K: 56.9.

Conversational Dataset:0-hero/matter-0.2-alph... En Endpoints compatible Mistral Model-index Pytorch Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/0-hero/Matter-0.2-7B-DPO

Matter 0.2 7B DPO Benchmarks

ARC: 63.31 vs 96.7 (so35)^-34.5%

HellaSwag: 83.16 vs 95.3 (gpt4)^-12.7%

MMLU: 62.9 vs 88.3 (so35)^-28.8%

GSM8K: 56.94 vs 96.4 (so35)^-40.9%

LLME Score: 0.16363

^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)

Matter 0.2 7B DPO (0-hero/Matter-0.2-7B-DPO)

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Matter 0.2 7B DPO Parameters and Internals

Model Type

text-generation

Training Details

Data Sources:

Matter-0.2-alpha

Data Volume:

>6B tokens

Input Output

Input Format:

ChatML prompt format

LLM Name	Matter 0.2 7B DPO
Repository 🤗	https://huggingface.co/0-hero/Matter-0.2-7B-DPO
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-05-18
Maintainer	0-hero
Model Type	mistral
Model Files	14.5 GB 14.5 GB
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32006
Torch Data Type	bfloat16

Best Alternatives to Matter 0.2 7B DPO

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	254	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8623	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	24	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	8131	17
Hebrew Mistral 7B 200K	256K / 30 GB	1378	15
Astral 256K 7B V2	250K / 14.4 GB	5	0
Astral 256K 7B	250K / 14.4 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than 0-hero/Matter-0.2-7B-DPO.

Rank the Matter 0.2 7B DPO Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Matter 0.2 7B DPO by 0-hero

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Matter 0.2 7B DPO Benchmarks

Matter 0.2 7B DPO Parameters and Internals

Best Alternatives to Matter 0.2 7B DPO

Rank the Matter 0.2 7B DPO Capabilities

What open-source LLMs or SLMs are you in search of? 53972 in total.