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  11898   
  Arxiv:2005.14165   Arxiv:2205.01068   Autotrain compatible   En   Jax   Opt   Pytorch   Region:us   Sharded   Tf
Model Card on HF 🤗: https://huggingface.co/facebook/opt-30b 

Opt 30B Benchmarks

MMLU Pro: 1.82
GPQA: 2.57
MUSR: 4.19
BBH: 3.5
IFEval: 24.53 vs 88 (so35)-72.1%
ARC: 43.26 vs 96.7 (so35)-55.3%
HellaSwag: 74.07 vs 95.3 (gpt4)-22.3%
MMLU: 26.66 vs 88.3 (so35)-69.8%
TruthfulQA: 35.16 vs 59 (gpt4)-40.4%
WinoGrande: 70.64 vs 87.5 (gpt4)-19.3%
GSM8K: 2.2 vs 96.4 (so35)-97.7%
MATH Lvl 5: 1.06
LLME Score: 0.10232
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Opt 30B (facebook/opt-30b)
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Opt 30B Parameters and Internals

Model Type 
decoder-only, causal language modeling
Use Cases 
Primary Use Cases:
text generation, zero- and few-shot learning
Limitations:
bias and safety concerns, quality issues in generation diversity and hallucination
Considerations:
Use of unfiltered internet content can introduce bias.
Additional Notes 
OPT models range from 125M to 175B parameters.
Supported Languages 
English (predominantly), Non-English (small amount)
Training Details 
Data Sources:
BookCorpus, CC-Stories, The Pile, Pushshift.io Reddit, CCNewsV2
Data Volume:
180B tokens
Methodology:
causal language modeling (CLM) objective
Context Length:
2048
Training Time:
~33 days
Hardware Used:
992 80GB A100 GPUs
Model Architecture:
decoder-only transformers
Input Output 
Input Format:
tokenized using GPT2 byte-level BPE
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use half-precision on GPU for large models.
LLM NameOpt 30B
Repository 🤗https://huggingface.co/facebook/opt-30b 
Model Size30b
Required VRAM60.1 GB
Updated2025-08-18
Maintainerfacebook
Model Typeopt
Model Files  9.8 GB: 1-of-7   9.9 GB: 2-of-7   9.9 GB: 3-of-7   9.9 GB: 4-of-7   9.9 GB: 5-of-7   9.9 GB: 6-of-7   0.8 GB: 7-of-7
Supported Languagesen
Model ArchitectureOPTForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.21.0.dev0
Beginning of Sentence Token</s>
End of Sentence Token</s>
Unk Token</s>
Vocabulary Size50272
Torch Data Typefloat16
Activation Functionrelu
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than facebook/opt-30b.

Rank the Opt 30B Capabilities

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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 v20241124
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