What are the hardware requirements for Everyone Coder 33B Base?

Everyone Coder 33B Base requires approximately 66.5 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 Everyone Coder 33B Base and how large is it?

Everyone Coder 33B Base is developed by rombodawg, a model with 33b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Everyone Coder 33B Base perform on standard benchmarks?

Everyone Coder 33B Base has the following published scores: MMLU 44.05. Compare against reference models on this page or on the LLM Explorer leaderboards.

Everyone Coder 33B Base by rombodawg — VRAM 66.5GB, 16K context

Name: Everyone Coder 33B Base
Author: rombodawg

Everyone Coder 33B Base is an open-source language model by rombodawg. Features: 33b LLM, VRAM: 66.5GB, Context: 16K, License: other, Code Generating, LLM Explorer Score: 0.14, Arc: 46, HellaSwag: 61.7, MMLU: 44.1, GSM8K: 39.8.

Codegen Conversational Deploy:azure Endpoints compatible Llama Merge Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/rombodawg/Everyone-Coder-33b-Base

Everyone Coder 33B Base Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

coding

Additional Notes

Model faces challenges with end tokens, prompting a custom template design.

Input Output

Input Format:

Custom prompt template with end token '<|EOT|>'.

Accepted Modalities:

text

Output Format:

Text output with '<|EOT|>' end token.

Performance Tips:

Utilize '<|EOT|>' as the stop string in the text generating interface.

LLM Name	Everyone Coder 33B Base
Repository 🤗	https://huggingface.co/rombodawg/Everyone-Coder-33b-Base
Model Size	33b
Required VRAM	66.5 GB
Updated	2026-08-08
Maintainer	rombodawg
Model Type	llama
Model Files	9.7 GB: 1-of-7 9.8 GB: 2-of-7 9.8 GB: 3-of-7 9.8 GB: 4-of-7 9.9 GB: 5-of-7 9.9 GB: 6-of-7 7.6 GB: 7-of-7
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	other
Context Length	16384
Model Max Length	16384
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizerFast
Beginning of Sentence Token	<｜begin▁of▁sentence｜>
End of Sentence Token	<\|EOT\|>
Vocabulary Size	32256
Torch Data Type	float16

Rank the Everyone Coder 33B Base 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 Everyone Coder 33B Base

Model	Likes	Downloads	VRAM
Everyone Coder 33B Base GGUF	13	728	12 GB
Everyone Coder 33B Base AWQ	2	8	18 GB
Everyone Coder 33B Base GPTQ	3	2	17 GB

Best Alternatives to Everyone Coder 33B Base

Best Alternatives	Context / RAM	Downloads	Likes
ReflectionCoder DS 33B	16K / 67 GB	8293	4
Deepseek Wizard 33B Slerp	16K / 35.3 GB	7	0
ValidateAI 3 33B Ties	16K / 66.5 GB	7	0
ValidateAI 2 33B AT	16K / 66.5 GB	6	0
WhiteRabbitNeo 33B V1	16K / 67 GB	214	95
Deepseek Coder 33B Instruct	16K / 66.5 GB	3376	580
Fortran2Cpp	16K / 67.3 GB	11	4
F2C Translator	16K / 67.3 GB	10	1
Llm4decompile 33B	16K / 66.5 GB	15	8
Deepseek Coder 33B Base	16K / 66.5 GB	2052	76

Note: green Score (e.g. "73.2") means that the model is better than rombodawg/Everyone-Coder-33b-Base.