What are the hardware requirements for Sandepa Ai Coder Small MoE 435M?

Sandepa Ai Coder Small MoE 435M requires approximately 1.2 GB of VRAM and supports a context window of 0.5K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Sandepa Ai Coder Small MoE 435M and how large is it?

Sandepa Ai Coder Small MoE 435M is developed by sandepaAI, a model with 582m 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 Sandepa Ai Coder Small MoE 435M?

Sandepa Ai Coder Small MoE 435M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sandepa Ai Coder Small MoE 435M by sandepaAI — VRAM 1.2GB, 0.5K context

Name: Sandepa Ai Coder Small MoE 435M
Author: sandepaAI

Sandepa Ai Coder Small MoE 435M is an open-source language model by sandepaAI. Features: 582m LLM, VRAM: 1.2GB, Context: 0.5K, MoE, Quantized, Code Generating, LLM Explorer Score: 0.29.

Codegen Conversational Endpoints compatible Gguf Mixtral Moe Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/sandepaAI/sandepa_ai_coder_small_moe_435m

Sandepa Ai Coder Small MoE 435M Parameters and Internals

LLM Name	Sandepa Ai Coder Small MoE 435m
Repository 🤗	https://huggingface.co/sandepaAI/sandepa_ai_coder_small_moe_435m
Model Size	582m
Required VRAM	1.2 GB
Updated	2026-08-14
Maintainer	sandepaAI
Model Type	mixtral
Model Files	2.3 GB 1.2 GB
GGUF Quantization	Yes
Quantization Type	gguf
Generates Code	Yes
Model Architecture	MixtralForCausalLM
Context Length	512
Model Max Length	512
Transformers Version	5.14.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	50259
Errors	replace

Rank the Sandepa Ai Coder Small MoE 435M 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

Quantized Models of the Sandepa Ai Coder Small MoE 435M

Model	Likes	Downloads	VRAM
...andepa Ai Coder 435m Small MoE	1	680	0 GB

Best Alternatives to Sandepa Ai Coder Small MoE 435M

Best Alternatives	Context / RAM	Downloads	Likes
...andepa Ai Coder 435m Small MoE	0.5K / 0.6 GB	680	1

Note: green Score (e.g. "73.2") means that the model is better than sandepaAI/sandepa_ai_coder_small_moe_435m.