Yi 34B 200K DARE Megamerge V8 AWQ by TheBloke

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Yi 34B 200K DARE Megamerge V8 AWQ is an open-source language model by TheBloke. Features: 34b LLM, VRAM: 19.3GB, Context: 195K, License: other, Quantized, LLM Explorer Score: 0.11.

  Arxiv:2306.01708   Arxiv:2311.03099   4-bit   Awq Base model:brucethemoose/yi-34... Base model:quantized:brucethem...   En   Llama   Merge   Mergekit   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Yi

Yi 34B 200K DARE Megamerge V8 AWQ Benchmarks

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

Yi 34B 200K DARE Megamerge V8 AWQ Parameters and Internals

Model Type 
yi
Supported Languages 
en (English)
LLM NameYi 34B 200K DARE Megamerge V8 AWQ
Repository 🤗https://huggingface.co/TheBloke/Yi-34B-200K-DARE-megamerge-v8-AWQ 
Model NameYi 34B 200K DARE MegaMerge V8
Model Creatorbrucethemoose
Base Model(s)  Yi 34B 200K DARE Megamerge V8   brucethemoose/Yi-34B-200K-DARE-megamerge-v8
Model Size34b
Required VRAM19.3 GB
Updated2026-04-21
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   9.3 GB: 2-of-2
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length200000
Model Max Length200000
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64002
Torch Data Typefloat16

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Bagel 34B V0.2 AWQ195K / 19.3 GB62
Nontoxic Bagel 34B V0.2 AWQ195K / 19.3 GB42
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Yi-34B-200K-DARE-megamerge-v8-AWQ.

Rank the Yi 34B 200K DARE Megamerge V8 AWQ 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 v20260328a