What are the hardware requirements for Mythos Qwen 1.5B Final?

Mythos Qwen 1.5B Final requires approximately 3.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mythos Qwen 1.5B Final and how large is it?

Mythos Qwen 1.5B Final is developed by expper, a model with 1.5b 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 Mythos Qwen 1.5B Final?

Mythos Qwen 1.5B Final is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mythos Qwen 1.5B Final by expper — VRAM 3.1GB, 32K context

Name: Mythos Qwen 1.5B Final
Author: expper

Mythos Qwen 1.5B Final is an open-source language model by expper. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Instruction-Based, Code Generating, LLM Explorer Score: 0.24.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-... Blue Blue-team Code Code-security Codegen Conversational Ctf Cve Cybersecurity En Endpoints compatible Instruct Mythos Qween Qween-security Qwen2 Region:us Safetensors Team

Model Card on HF 🤗: https://huggingface.co/expper/mythos-qwen-1.5b-final

Mythos Qwen 1.5B Final Parameters and Internals

LLM Name	Mythos Qwen 1.5B Final
Repository 🤗	https://huggingface.co/expper/mythos-qwen-1.5b-final
Base Model(s)	Qwen/Qwen2.5-Coder-1.5B-Instruct Qwen/Qwen2.5-Coder-1.5B-Instruct
Model Size	1.5b
Required VRAM	3.1 GB
Updated	2026-08-06
Maintainer	expper
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.1 GB
Supported Languages	en
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Mythos Qwen 1.5B Final 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 Mythos Qwen 1.5B Final

Best Alternatives	Context / RAM	Downloads	Likes
Merge Cord V1	128K / 3.1 GB	155	1
Replete Coder Qwen2 1.5B	128K / 3.1 GB	233	23
Pulsar Coder 1.5B	32K / 3.1 GB	13	0
Qwen2.5 Coder 1.5B Instruct	32K / 3.1 GB	695585	134
Microcoder 1.5B	32K / 3.1 GB	20	4
Qwen2.5 Coder 1.5B Instruct	32K / 3.1 GB	69796	6
...n2.5 Coder Draft 1.5B Instruct	32K / 3.1 GB	7	0
ProseFlow V1.1.5B Instruct	32K / 3.1 GB	4	1
Arch Agent 1.5B	32K / 3.1 GB	149	9
Hammer2.1 1.5B	32K / 3.1 GB	1933	15

Note: green Score (e.g. "73.2") means that the model is better than expper/mythos-qwen-1.5b-final.