What are the hardware requirements for SLM DeepResearcher V1?

SLM DeepResearcher V1 requires approximately 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 SLM DeepResearcher V1 and how large is it?

SLM DeepResearcher V1 is developed by BRR1154, a model with 0.5b 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 SLM DeepResearcher V1?

SLM DeepResearcher V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SLM DeepResearcher V1 by BRR1154 — VRAM 2GB, 32K context

Name: SLM DeepResearcher V1
Author: BRR1154

SLM DeepResearcher V1 is an open-source language model by BRR1154. Features: 0.5b LLM, VRAM: 2GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.33.

Academic Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-0.5b-i... Conversational En Endpoints compatible Instruct Literature-review Prisma Qwen2 Qwen2.5 Region:us Research Safetensors

Model Card on HF 🤗: https://huggingface.co/BRR1154/SLM-DeepResearcher-v1

SLM DeepResearcher V1 Parameters and Internals

LLM Name	SLM DeepResearcher V1
Repository 🤗	https://huggingface.co/BRR1154/SLM-DeepResearcher-v1
Base Model(s)	Qwen/Qwen2.5-0.5B-Instruct Qwen/Qwen2.5-0.5B-Instruct
Model Size	0.5b
Required VRAM	2 GB
Updated	2026-11-11
Maintainer	BRR1154
Model Type	qwen2
Instruction-Based	Yes
Model Files	2.0 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	5.16.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the SLM DeepResearcher V1 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

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