What are the hardware requirements for Thinkless 1.5B Warmup?

Thinkless 1.5B Warmup requires approximately 7.1 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 Thinkless 1.5B Warmup and how large is it?

Thinkless 1.5B Warmup is developed by Vinnnf, 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 Thinkless 1.5B Warmup?

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

Thinkless 1.5B Warmup by Vinnnf — VRAM 7.1GB, 32K context

Name: Thinkless 1.5B Warmup
Author: Vinnnf

Thinkless 1.5B Warmup is an open-source language model by Vinnnf. Features: 1.5b LLM, VRAM: 7.1GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.18.

Arxiv:2505.13379 Base model:deepseek-ai/deepsee... Base model:finetune:deepseek-a... Conversational Dataset:open-thoughts/openthou... Dataset:vinnnf/hybrid-openthou... Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Vinnnf/Thinkless-1.5B-Warmup

Thinkless 1.5B Warmup Parameters and Internals

LLM Name	Thinkless 1.5B Warmup
Repository 🤗	https://huggingface.co/Vinnnf/Thinkless-1.5B-Warmup
Base Model(s)	deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
Model Size	1.5b
Required VRAM	7.1 GB
Updated	2026-07-17
Maintainer	Vinnnf
Model Type	qwen2
Model Files	5.0 GB: 1-of-2 2.1 GB: 2-of-2
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	LlamaTokenizerFast
Padding Token	<\|EOT\|>
Vocabulary Size	151680
Torch Data Type	float32

Rank the Thinkless 1.5B Warmup capabilities

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Best Alternatives to Thinkless 1.5B Warmup

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 1.5B 1.3M Stretched	1280K / 3.1 GB	18	0
ReaderLM V2	500K / 3.1 GB	35356	804
Reader Lm 1.5B	250K / 3.1 GB	385	608
DeepSeek R1 Distill Qwen 1.5B	128K / 3.5 GB	600051	1545
Pulsar Coder V1	128K / 3.1 GB	291	1
MLR Executor Qwen 1.5B	128K / 3.5 GB	503	0
Axiom Python 1.5B	128K / 3.1 GB	312	0
Ko R1 1.5B Preview	128K / 7.1 GB	8	9
...2 1.5B Lora Tensorboard Merged	128K / 3.1 GB	124	1
Qwen2.5 1.5B	128K / 3.1 GB	863295	203

Note: green Score (e.g. "73.2") means that the model is better than Vinnnf/Thinkless-1.5B-Warmup.