What are the hardware requirements for Gen Sim?

Gen Sim requires approximately 0.3 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gen Sim and how large is it?

Gen Sim is developed by Gen-Sim, a model with 13b 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 Gen Sim?

Gen Sim is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gen Sim by Gen-Sim — VRAM 0.3GB, 16K context

Name: Gen Sim
Author: Gen-Sim

Gen Sim is an open-source language model by Gen-Sim. Features: 13b LLM, VRAM: 0.3GB, Context: 16K, License: mit, Instruction-Based, Code Generating, LLM Explorer Score: 0.08.

Codegen Endpoints compatible Instruct Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/Gen-Sim/Gen-Sim

Gen Sim Parameters and Internals

Model Type

code generation

Use Cases

Areas:

robotic simulation tasks, code generation

Applications:

research, education, industry projects

Primary Use Cases:

simulation task code generation

Limitations:

may not handle tasks outside of training scope, limited to simulation-focused tasks

Considerations:

Ensure outputs are reviewed for correctness

Additional Notes

Optimized for code generation in robotic simulations

Training Details

Data Sources:

100 simulation tasks generated by GPT-4 and humans

Methodology:

Finetuning

Input Output

Input Format:

[INST] <RLTask> <Description> [Code Snippet]

Accepted Modalities:

text

Output Format:

Python code block

LLM Name	Gen Sim
Repository 🤗	https://huggingface.co/Gen-Sim/Gen-Sim
Model Size	13b
Required VRAM	0.3 GB
Updated	2026-07-19
Maintainer	Gen-Sim
Model Type	llama
Instruction-Based	Yes
Model Files	0.3 GB: 1-of-3 0.0 GB: 2-of-3 0.0 GB: 3-of-3
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	mit
Context Length	16384
Model Max Length	16384
Transformers Version	4.29.2
Vocabulary Size	32016
Torch Data Type	float16

Rank the Gen Sim 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 Gen Sim

Best Alternatives	Context / RAM	Downloads	Likes
NexusRaven V2 13B	16K / 26 GB	105	472
CodeLlama 13B Instruct Hf	16K / 26 GB	2469	160
CodeLlama 13B MORepair	16K / 26 GB	9	2
CodeLlama 13B Instruct Hf	16K / 26 GB	369	29
TableLLM 13B	16K / 26 GB	98	34
NexusRaven 13B	16K / 26 GB	37	106
Panda Coder 13B	16K / 26 GB	11	14
... Llama 2 13B Instruct Text2sql	16K / 26 GB	8	28
CodeLlama 13B Instruct Fp16	16K / 26 GB	137	28
...Llama 13B Instruct Hf 4bit MLX	16K / 7.8 GB	113	3

Note: green Score (e.g. "73.2") means that the model is better than Gen-Sim/Gen-Sim.