What are the hardware requirements for Qwen2.5 3B FinCode Reasoning Full?

Qwen2.5 3B FinCode Reasoning Full requires approximately 6.2 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 Qwen2.5 3B FinCode Reasoning Full and how large is it?

Qwen2.5 3B FinCode Reasoning Full is developed by coslinedev, a model with 3b 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 Qwen2.5 3B FinCode Reasoning Full?

Qwen2.5 3B FinCode Reasoning Full is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 3B FinCode Reasoning Full by coslinedev — VRAM 6.2GB, 32K context

Name: Qwen2.5 3B FinCode Reasoning Full
Author: coslinedev

Qwen2.5 3B FinCode Reasoning Full is an open-source language model by coslinedev. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.28.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-3b-ins... Chain-of-thought Code-generation Conversational En Endpoints compatible Execution-verified Financial-modeling Fintech Instruct Python Quant Qwen2 Reasoning Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/coslinedev/Qwen2.5-3B-FinCode-Reasoning-Full

Qwen2.5 3B FinCode Reasoning Full Parameters and Internals

LLM Name	Qwen2.5 3B FinCode Reasoning Full
Repository 🤗	https://huggingface.co/coslinedev/Qwen2.5-3B-FinCode-Reasoning-Full
Base Model(s)	Qwen/Qwen2.5-3B-Instruct Qwen/Qwen2.5-3B-Instruct
Model Size	3b
Required VRAM	6.2 GB
Updated	2026-08-14
Maintainer	coslinedev
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.0 GB: 1-of-2 2.2 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen2.5 3B FinCode Reasoning Full capabilities

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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 Qwen2.5 3B FinCode Reasoning Full

Best Alternatives	Context / RAM	Downloads	Likes
VibeThinker 3B	128K / 6.2 GB	52745	806
VibeThinker 3B	128K / 6.2 GB	361	0
Saba2 3B	128K / 6.2 GB	6	0
Tessa T1 3B	117K / 6.2 GB	10	5
UIGEN T1.5 3B	117K / 6.2 GB	7	1
Qwen2.5 3B Instruct	32K / 6.2 GB	5889234	545
SmallThinker 3B Preview	32K / 6.8 GB	30529	412
Qwen2.5 3B Haizi	32K / 6.2 GB	74	0
ResearchMate Qwen2.5 3B	32K / 6.2 GB	66	2
LeeChanRX 3B Instruct	32K / 6.2 GB	570	2

Note: green Score (e.g. "73.2") means that the model is better than coslinedev/Qwen2.5-3B-FinCode-Reasoning-Full.