What are the hardware requirements for Codegemma 1.1 7B It GPTQ?

Codegemma 1.1 7B It GPTQ requires approximately 7.2 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Codegemma 1.1 7B It GPTQ and how large is it?

Codegemma 1.1 7B It GPTQ is developed by TechxGenus, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Codegemma 1.1 7B It GPTQ?

Codegemma 1.1 7B It GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Codegemma 1.1 7B It GPTQ by TechxGenus — VRAM 7.2GB, 8K context

Name: Codegemma 1.1 7B It GPTQ
Author: TechxGenus

Codegemma 1.1 7B It GPTQ is an open-source language model by TechxGenus. Features: 7b LLM, VRAM: 7.2GB, Context: 8K, License: gemma, Quantized, LLM Explorer Score: 0.12.

4-bit Endpoints compatible Gemma Gptq Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TechxGenus/codegemma-1.1-7b-it-GPTQ

Codegemma 1.1 7B It GPTQ Parameters and Internals

Model Type

text-to-text, text-to-code, decoder-only

Use Cases

Areas:

code completion, code generation, code conversation, code education

Applications:

IDE integration, Conversational interfaces

Primary Use Cases:

Code fragments question answering, Natural language to code generation

Limitations:

LLM inherent limitations

Considerations:

Users should follow safety and ethical guidelines outlined by Google AI.

Additional Notes

CodeGemma models build on the successful Gemma model with specialized training for text-to-code tasks.

Supported Languages

English (high)

Training Details

Data Sources:

publicly available code repositories, open source mathematics datasets, synthetically generated code

Data Volume:

500 to 1000 billion tokens

Methodology:

Further trained variants including FIM (Fill-In-The-Middle) techniques

Hardware Used:

TPUv5e

Model Architecture:

CodeGemma models are built on top of Gemma

Safety Evaluation

Methodologies:

human evaluation, cyber-offense testing, red-teaming

Findings:

Within acceptable thresholds for meeting internal policies

Risk Categories:

child safety, content safety, representational harms, memorization, large-scale harms

Ethical Considerations:

Evaluation of ethical considerations in line with Google AI Principles

Responsible Ai Considerations

Mitigation Strategies:

Implemented rigorous safety filtering and evaluation processes.

Input Output

Input Format:

code prefix/suffix or natural language text

Accepted Modalities:

text

Output Format:

code and natural language text

LLM Name	Codegemma 1.1 7B It GPTQ
Repository 🤗	https://huggingface.co/TechxGenus/codegemma-1.1-7b-it-GPTQ
Base Model(s)	google/codegemma-1.1-7b-it google/codegemma-1.1-7b-it
Model Size	7b
Required VRAM	7.2 GB
Updated	2026-06-04
Maintainer	TechxGenus
Model Type	gemma
Model Files	7.2 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	GemmaForCausalLM
License	gemma
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float16

Rank the Codegemma 1.1 7B It GPTQ capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Best Alternatives to Codegemma 1.1 7B It GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 1.1 7B It GPTQ	8K / 7.2 GB	3	1
Codegemma 7B It GPTQ	8K / 7.2 GB	4	1
CodeGemma 7B GPTQ	8K / 7.2 GB	9	0
Google Gemma 7B 4 Bit Gptq	8K / 5.6 GB	12	1
Google Gemma 7B 8 Bit Gptq	8K / 9.5 GB	5	0
Gemma 7B Instruct GPTQ 4bit	8K / 5.6 GB	12	0
SeaLLM 7B V2.5 4bit	8K / 7.2 GB	6	2
Gemma 7B GPTQ	8K / 7.2 GB	89	0
Gemma 7B It GPTQ	8K / 7.2 GB	5	0
...t Cleaner Gemma 32k Merged 16b	31K / 17.1 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than TechxGenus/codegemma-1.1-7b-it-GPTQ.