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Dolphin 2.7 Mixtral 8x7b by mlx-community

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Dolphin 2.7 Mixtral 8x7b is an open-source language model by mlx-community. Features: 46.7b LLM, VRAM: 92.9GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.13.

Dataset:cognitivecomputations/... Dataset:cognitivecomputations/... Dataset:ise-uiuc/magicoder-evo... Dataset:ise-uiuc/magicoder-oss... Dataset:jondurbin/airoboros-2....   Dataset:ldjnr/capybara   Dataset:teknium/openhermes   En   Instruct   Mixtral   Mlx   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mlx-community/dolphin-2.7-mixtral-8x7b 

Dolphin 2.7 Mixtral 8x7b Benchmarks

LLME Score: 0.12751
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Dolphin 2.7 Mixtral 8x7b (mlx-community/dolphin-2.7-mixtral-8x7b)
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Dolphin 2.7 Mixtral 8x7b Parameters and Internals

LLM NameDolphin 2.7 Mixtral 8x7b
Repository 🤗https://huggingface.co/mlx-community/dolphin-2.7-mixtral-8x7b 
Model Size46.7b
Required VRAM92.9 GB
Updated2026-04-07
Maintainermlx-community
Model Typemixtral
Instruction-BasedYes
Model Files  5.4 GB: 1-of-18   5.3 GB: 2-of-18   5.3 GB: 3-of-18   5.3 GB: 4-of-18   5.3 GB: 5-of-18   5.2 GB: 6-of-18   5.3 GB: 7-of-18   5.3 GB: 8-of-18   5.3 GB: 9-of-18   5.3 GB: 10-of-18   5.3 GB: 11-of-18   5.2 GB: 12-of-18   5.3 GB: 13-of-18   5.3 GB: 14-of-18   5.3 GB: 15-of-18   5.3 GB: 16-of-18   5.3 GB: 17-of-18   2.9 GB: 18-of-18
Supported Languagesen
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.39.1
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16

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Dolphin 2.6 Mixtral 8x7b32K / 93.6 GB11285211
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Dolphin 2.7 Mixtral 8x7b32K / 93.6 GB2178170
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...eqlen 4096 Bs 4 Optimum 0 0 2332K /  GB90
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Mixtral 8x7B Instruct V0.132K /  GB70
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Note: green Score (e.g. "73.2") means that the model is better than mlx-community/dolphin-2.7-mixtral-8x7b.

Rank the Dolphin 2.7 Mixtral 8x7b 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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