Codegemma 7B by unsloth

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Codegemma 7B is an open-source language model by unsloth. Features: 7b LLM, VRAM: 17GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.13.

  Bnb   En   Endpoints compatible   Gemma   Region:us   Safetensors   Sharded   Tensorflow   Unsloth

Codegemma 7B Benchmarks

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

Codegemma 7B Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
beginner-friendly fine-tuning and text generation
Applications:
finetuning models for faster and memory-efficient performance, exporting models to various formats, uploading models to Hugging Face
Primary Use Cases:
2x faster fine-tuning
Additional Notes 
Unsloth provides free Colab notebooks for beginners to finetune models efficiently.
LLM NameCodegemma 7B
Repository 🤗https://huggingface.co/unsloth/codegemma-7b 
Model Size7b
Required VRAM17 GB
Updated2026-05-16
Maintainerunsloth
Model Typegemma
Model Files  5.8 GB: 1-of-3   5.9 GB: 2-of-3   5.3 GB: 3-of-3
Supported Languagesen
Model ArchitectureGemmaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.44.2
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

Quantized Models of the Codegemma 7B

Model
Likes
Downloads
VRAM
Codegemma 7B AWQ057 GB
CodeGemma 7B AWQ057 GB

Best Alternatives to Codegemma 7B

Best Alternatives
Context / RAM
Downloads
Likes
Kaggle Math Model Gemma V112K / 17.1 GB50
Gemma 1.1 7B It8K / 17.1 GB12200275
Gemma 1.1 7B It8K / 17.1 GB124
Gemma 7B It8K / 17.1 GB157010
SeaLLM 7B V2.58K / 17.1 GB1247651
Zephyr 7B Gemma DPO Avg8K / 17.1 GB150
Zephyr 7B Gemma Rpo Avg8K / 17.1 GB70
... Codegemma 2 7B It Alpaca V1.38K / 17.1 GB21
... 7B Finetuned Sft Navarasa 2.08K / 34 GB162023
Codegemma 7B It8K / 17.1 GB8430252
Note: green Score (e.g. "73.2") means that the model is better than unsloth/codegemma-7b.

Rank the Codegemma 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