What are the hardware requirements for Ct2fast Codegen2 16B?

Ct2fast Codegen2 16B requires approximately 32.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ct2fast Codegen2 16B and how large is it?

Ct2fast Codegen2 16B is developed by michaelfeil, a model with 16b 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 Ct2fast Codegen2 16B?

Ct2fast Codegen2 16B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ct2fast Codegen2 16B by michaelfeil — VRAM 32.1GB

Name: Ct2fast Codegen2 16B
Author: michaelfeil

Ct2fast Codegen2 16B is an open-source language model by michaelfeil. Features: 16b LLM, VRAM: 32.1GB, License: apache-2.0, LLM Explorer Score: 0.07.

Arxiv:2305.02309 Ctranslate2 Endpoints compatible Float16 Int8 Region:us

Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-codegen2-16B

Ct2fast Codegen2 16B Parameters and Internals

Model Type

program synthesis, autoregressive language model

Use Cases

Areas:

program synthesis

Applications:

feature extraction, code generation, completion of partially generated code

Primary Use Cases:

generating executable code given English prompts

Limitations:

The model is best at program synthesis and its performance on other tasks is unknown.

Additional Notes

This version is quantized for faster inference with Ctranslate2, reducing memory requirements by 2x-4x using int8 inference.

Supported Languages

c (high), c++ (high), c-sharp (high), dart (high), go (high), java (high), javascript (high), kotlin (high), lua (high), php (high), python (high), ruby (high), rust (high), scala (high), shell (high), sql (high), swift (high), typescript (high), vue (high)

Training Details

Data Sources:

the deduplicated version of the Stack dataset (v1.1)

Methodology:

cross-entropy loss for causal language modeling and file-level span corruption

Input Output

Input Format:

text

Accepted Modalities:

text

Output Format:

text or code

LLM Name	Ct2fast Codegen2 16B
Repository 🤗	https://huggingface.co/michaelfeil/ct2fast-codegen2-16B
Model Size	16b
Required VRAM	32.1 GB
Updated	2026-07-31
Maintainer	michaelfeil
Model Files	32.1 GB
Model Architecture	AutoModel
License	apache-2.0
Model Max Length	1024
Tokenizer Class	GPT2Tokenizer

Rank the Ct2fast Codegen2 16B 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 Ct2fast Codegen2 16B

Best Alternatives	Context / RAM	Downloads	Likes
Ct2fast Codegen 16B Mono	0K / 32.1 GB	1	2
Tinyllama Gguf 16B	0K / 2.2 GB	17	0
Llama 3 16B Instruct V0.1 GGUF	0K / 6.4 GB	502	9
Nanbeige 16B Chat 32K GGUF	0K / 6.6 GB	566	6
Nanbeige 16B Base 32K GGUF	0K / 6.6 GB	352	4
Nanbeige 16B Base GGUF	0K / 6.6 GB	200	1
Nanbeige 16B Chat GGUF	0K / 6.6 GB	159	1

Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-codegen2-16B.