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Qwen2 57B A14B Instruct by Qwen

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Qwen2 57B A14B Instruct is an open-source language model by Qwen. Features: 57b LLM, VRAM: 115.2GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.29.

  Arxiv:2309.00071 Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2-57b-a14b   Chat   Conversational   En   Endpoints compatible   Instruct   Qwen2 moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2-57B-A14B-Instruct 

Qwen2 57B A14B Instruct Benchmarks

MMLU Pro: 39.73
GPQA: 10.85
MUSR: 14.18
BBH: 41.79
IFEval: 63.38 vs 88 (so35)-28%
MATH Lvl 5: 28.17
LLME Score: 0.28711
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2 57B A14B Instruct (Qwen/Qwen2-57B-A14B-Instruct)
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Qwen2 57B A14B Instruct Parameters and Internals

Model Type 
text-generation, multimodal
Use Cases 
Areas:
research, commercial applications
Limitations:
performance on shorter texts
Considerations:
Add `rope_scaling` configuration only when processing long contexts is required.
Additional Notes 
Presently, vLLM only supports static YARN, potentially impacting performance on shorter texts.
Supported Languages 
en (advanced), others (basic)
Training Details 
Data Volume:
large amount
Methodology:
supervised finetuning and direct preference optimization
Context Length:
65536
Model Architecture:
Transformer with SwiGLU activation, attention QKV bias, group query attention
Input Output 
Input Format:
messages in JSON
Accepted Modalities:
text
Output Format:
tokenized responses
Performance Tips:
Use `apply_chat_template` in code example, add `rope_scaling` only when processing long contexts.
LLM NameQwen2 57B A14B Instruct
Repository 🤗https://huggingface.co/Qwen/Qwen2-57B-A14B-Instruct 
Base Model(s)  Qwen2 57B A14B   Qwen/Qwen2-57B-A14B
Model Size57b
Required VRAM115.2 GB
Updated2026-04-10
MaintainerQwen
Model Typeqwen2_moe
Instruction-BasedYes
Model Files  4.0 GB: 1-of-29   4.0 GB: 2-of-29   4.0 GB: 3-of-29   4.0 GB: 4-of-29   4.0 GB: 5-of-29   4.0 GB: 6-of-29   4.0 GB: 7-of-29   4.0 GB: 8-of-29   4.0 GB: 9-of-29   4.0 GB: 10-of-29   4.0 GB: 11-of-29   4.0 GB: 12-of-29   4.0 GB: 13-of-29   4.0 GB: 14-of-29   4.0 GB: 15-of-29   4.0 GB: 16-of-29   4.0 GB: 17-of-29   4.0 GB: 18-of-29   4.0 GB: 19-of-29   4.0 GB: 20-of-29   4.0 GB: 21-of-29   4.0 GB: 22-of-29   4.0 GB: 23-of-29   4.0 GB: 24-of-29   4.0 GB: 25-of-29   4.0 GB: 26-of-29   4.0 GB: 27-of-29   4.0 GB: 28-of-29   3.2 GB: 29-of-29
Supported Languagesen
Model ArchitectureQwen2MoeForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Quantized Models of the Qwen2 57B A14B Instruct

Model
Likes
Downloads
VRAM
...n2 57B A14B Instruct GPTQ Int42310431 GB
Qwen2 57B A14B Instruct 4bit26132 GB
Qwen2 57B A14B Instruct 8bit1461 GB

Best Alternatives to Qwen2 57B A14B Instruct

Best Alternatives
Context / RAM
Downloads
Likes
Qwen2 57B A14B Instruct 4bit32K / 32.3 GB612
Qwen2 57B A14B Instruct 8bit32K / 61.1 GB41
...n2 57B A14B Instruct GPTQ Int432K / 31.6 GB10423
...7B A14B Instruct GPTQ Int4 MLX32K / 32.3 GB471

Rank the Qwen2 57B A14B Instruct 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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