What are the hardware requirements for Springer 32B 19?

Springer 32B 19 requires approximately 65.7 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 Springer 32B 19 and how large is it?

Springer 32B 19 is developed by marcuscedricridia, a model with 32b 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 Springer 32B 19?

Springer 32B 19 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Springer 32B 19 by marcuscedricridia — VRAM 65.7GB, 32K context

Name: Springer 32B 19
Author: marcuscedricridia

Springer 32B 19 is an open-source language model by marcuscedricridia. Features: 32b LLM, VRAM: 65.7GB, Context: 32K, Instruction-Based, Merged, LLM Explorer Score: 0.17.

Merged Model Arxiv:2406.11617 Base model:marcuscedricridia/s... Base model:tiger-lab/qwen2.5-3... Conversational Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/marcuscedricridia/Springer-32B-19

Springer 32B 19 Parameters and Internals

LLM Name	Springer 32B 19
Repository 🤗	https://huggingface.co/marcuscedricridia/Springer-32B-19
Base Model(s)	Springer 32B TIGER-Lab/Qwen2.5-32B-Instruct-CFT marcuscedricridia/Springer-32B TIGER-Lab/Qwen2.5-32B-Instruct-CFT
Merged Model	Yes
Model Size	32b
Required VRAM	65.7 GB
Updated	2026-08-08
Maintainer	marcuscedricridia
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-14 4.9 GB: 2-of-14 4.9 GB: 3-of-14 4.9 GB: 4-of-14 4.9 GB: 5-of-14 4.9 GB: 6-of-14 4.9 GB: 7-of-14 4.9 GB: 8-of-14 4.9 GB: 9-of-14 4.9 GB: 10-of-14 4.9 GB: 11-of-14 4.9 GB: 12-of-14 4.9 GB: 13-of-14 1.9 GB: 14-of-14
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the Springer 32B 19 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 Springer 32B 19

Best Alternatives	Context / RAM	Downloads	Likes
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	9	2
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	16	17
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	12	4
Franqwenstein 35B	128K / 69.8 GB	5	8
ELYZA Thinking 1.0 Qwen 32B	128K / 65.8 GB	23	10
Archaeo 32B KTO	128K / 65.8 GB	10	4
Hamanasu Magnum QwQ 32B	128K / 65.8 GB	295	9
Qwen2.5 32B Gokgok Step3	128K / 65.7 GB	6	0
Openthaigpt R1 32B Instruct	128K / 65.8 GB	33	8
Qwen2.5 32B Dark Days Stage2	128K / 65.8 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than marcuscedricridia/Springer-32B-19.