What are the hardware requirements for 7B?

7B requires approximately 15.5 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed 7B and how large is it?

7B is developed by CausalLM, 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 7B perform on standard benchmarks?

7B has the following published scores: MMLU 61.79, LMSYS ELO 12. Compare against reference models on this page or on the LLM Explorer leaderboards.

7B by CausalLM — VRAM 15.5GB, 8K context

Name: 7B
Author: CausalLM

7B is an open-source language model by CausalLM. Features: 7b LLM, VRAM: 15.5GB, Context: 8K, License: wtfpl, Instruction-Based, HF Score: 54.9, LLM Explorer Score: 0.15, ELO: 12, Arc: 50, HellaSwag: 74.6, MMLU: 61.8, TruthfulQA: 50.1, WinoGrande: 69.7, GSM8K: 23.

Causallm Dataset:baai/coig Dataset:fnlp/moss-003-sft-data Dataset:garage-baind/open-plat... Dataset:jondurbin/airoboros-3.... Dataset:josephuscheung/guanaco... Dataset:ldjnr/puffin Dataset:liuhaotian/llava-instr... Dataset:liwu/mnbvc Dataset:meta-math/metamathqa Dataset:milashkaarshif/moegirl... Dataset:open-orca/openorca Dataset:openbmb/llava zh Dataset:ryokoai/fandom23k Dataset:ryokoai/sharegpt52k Dataset:stingning/ultrachat Dataset:teknium/openhermes Dataset:tigerresearch/tigerbot... Dataset:wiki lingua Dataset:wikipedia Dataset:wizardlm/wizardlm evol... En Endpoints compatible Instruct Llama Llama2 Pytorch Qwen Region:us Sharded Zh

Model Card on HF 🤗: https://huggingface.co/CausalLM/7B

7B Benchmarks

LMSys ELO: 12 vs 1272 (so35)^-99.1%

ARC: 50 vs 96.7 (so35)^-48.3%

HellaSwag: 74.58 vs 95.3 (gpt4)^-21.7%

MMLU: 61.79 vs 88.3 (so35)^-30%

TruthfulQA: 50.13 vs 59 (gpt4)^-15%

WinoGrande: 69.69 vs 87.5 (gpt4)^-20.4%

GSM8K: 22.97 vs 96.4 (so35)^-76.2%

LLME Score: 0.14866

^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)

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7B Parameters and Internals

Model Type

text generation, causallm

Use Cases

Areas:

research, commercial applications

Limitations:

May produce hallucinations or unreliable outputs., Trained on unfiltered internet data, potentially contains objectionable content.

Considerations:

Users should implement safety checks and filter keywords in outputs.

Additional Notes

The 7B version is a distilled version of the 14B model.

Supported Languages

en (English: high proficiency), zh (Chinese: high proficiency)

Training Details

Data Sources:

JosephusCheung/GuanacoDataset, Open-Orca/OpenOrca, stingning/ultrachat, meta-math/MetaMathQA, liuhaotian/LLaVA-Instruct-150K, jondurbin/airoboros-3.1, WizardLM/WizardLM_evol_instruct_V2_196k, RyokoAI/ShareGPT52K, RyokoAI/Fandom23K, milashkaarshif/MoeGirlPedia_wikitext_raw_archive, wikipedia, wiki_lingua, fnlp/moss-003-sft-data, garage-bAInd/Open-Platypus, LDJnr/Puffin, openbmb/llava_zh, BAAI/COIG, TigerResearch/tigerbot-zhihu-zh-10k, liwu/MNBVC, teknium/openhermes

Data Volume:

1.3B tokens

Methodology:

Manually curated SFT dataset, synthetic data generation using larger language models.

Model Architecture:

Same as LLaMA2 with original MHA LLaMA2 models; no additional scaling for RoPE.

Input Output

Input Format:

chatml

Accepted Modalities:

text

Output Format:

text

Performance Tips:

Avoid unofficial GPTQ and AWQ models; prefer GGUF for quantization.

LLM Name	7B
Repository 🤗	https://huggingface.co/CausalLM/7B
Model Size	7b
Required VRAM	15.5 GB
Updated	2026-04-27
Maintainer	CausalLM
Model Type	llama
Instruction-Based	Yes
Model Files	10.0 GB: 1-of-2 5.5 GB: 2-of-2
Supported Languages	en zh
Model Architecture	LlamaForCausalLM
License	wtfpl
Context Length	8192
Model Max Length	8192
Transformers Version	4.35.0.dev0
Tokenizer Class	GPT2Tokenizer
Vocabulary Size	151936
Torch Data Type	bfloat16

Quantized Models of the 7B

Model	Likes	Downloads	VRAM
CausalLM 7B GGUF	64	2329	3 GB
CausalLM 7B GPTQ	5	8	5 GB
CausalLM 7B AWQ	3	15	5 GB

Best Alternatives to 7B

Best Alternatives	Context / RAM	Downloads	Likes
124	1024K / 16.1 GB	93	0
A5.4	1024K / 16.1 GB	12	0
A3.4	1024K / 16.1 GB	13	0
A2.4	1024K / 16.1 GB	12	0
... Qwen2.5llamaify 7B V23.1 200K	195K / 15.2 GB	24	5
SuperNeuralDreadDevil 8B	128K / 16.1 GB	22	1
Falcon3 7B Instruct	32K / 14.8 GB	18150	78
Falcon3 Jessi V0.4 7B Slerp	32K / 14.9 GB	9	9
Jessi V0.4 Falcon3 7B Instruct	32K / 14.8 GB	22	0
Jessi V0.5 Falcon3 7B Instruct	32K / 14.8 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than CausalLM/7B.

Rank the 7B 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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Release v20260328a

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7B by CausalLM