What are the hardware requirements for Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct?

Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct requires approximately 84.8 GB of VRAM and supports a context window of 986K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct and how large is it?

Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct is developed by DavidAU, a model with 30b 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 Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct?

Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct by DavidAU — VRAM 84.8GB, 986K context

Name: Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct
Author: DavidAU

Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct is an open-source language model by DavidAU. Features: 30b LLM, VRAM: 84.8GB, Context: 986K, License: apache-2.0, Instruction-Based, Code Generating, LLM Explorer Score: 0.2.

Arxiv:2401.02415 1 million context 128 experts 8 active experts Autotrain compatible Base model:finetune:yoyo-ai/qw... Base model:yoyo-ai/qwen3-30b-a... Brainstorm Brainstorm 20x Chat Code Code generation Codegen Codeqwen Coder Coding Conversational De En Endpoints compatible Finetuned Fr Instruct Mixture of experts Moe Optional thinking Qwen Qwen-coder Qwen2 Qwen3 Qwen3-30b-a3b Qwen3-coder-30b-a3b-instruct Qwen3 moe Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/DavidAU/Qwen3-42B-A3B-2507-YOYO2-TOTAL-RECALL-Instruct

Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct Parameters and Internals

LLM Name	Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct
Repository 🤗	https://huggingface.co/DavidAU/Qwen3-42B-A3B-2507-YOYO2-TOTAL-RECALL-Instruct
Base Model(s)	Qwen3 30B A3B YOYO V2 YOYO-AI/Qwen3-30B-A3B-YOYO-V2
Model Size	30b
Required VRAM	84.8 GB
Updated	2025-10-12
Maintainer	DavidAU
Model Type	qwen3_moe
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-17 5.0 GB: 2-of-17 5.0 GB: 3-of-17 5.0 GB: 4-of-17 5.0 GB: 5-of-17 5.0 GB: 6-of-17 5.0 GB: 7-of-17 5.0 GB: 8-of-17 5.0 GB: 9-of-17 5.0 GB: 10-of-17 5.0 GB: 11-of-17 5.0 GB: 12-of-17 5.0 GB: 13-of-17 5.0 GB: 14-of-17 5.0 GB: 15-of-17 5.0 GB: 16-of-17 4.8 GB: 17-of-17
Supported Languages	en fr zh de
Generates Code	Yes
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	1010000
Model Max Length	1010000
Transformers Version	4.55.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151669
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct 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 Qwen3 42B A3B 2507 YOYO2 TOTAL RECALL Instruct

Best Alternatives	Context / RAM	Downloads	Likes
...LL MASTER CODER M 1million Ctx	1024K / 84.8 GB	120	9
Qwen3 30B A3B YOYO V3	986K / 61.1 GB	11	7
...07 YOYO2 TOTAL RECALL Instruct	986K / 106 GB	20	0
Qwen3 30B A3B YOYO V2	986K / 61.1 GB	19	4
Qwen3 Coder 30B A3B Instruct	256K / 61.1 GB	1746771	1168
...en3 Coder 30B A3B Instruct FP8	256K / 31.2 GB	1556690	191
Tiny Pickle V3 Coder	256K / 61.2 GB	64	0
Qwen3 Coder 30B A3B Instruct	256K / 61.1 GB	9034	27
Qwen3 Coder REAP 25B A3B	256K / 49.8 GB	579	88
Qwen3 30B A3B YOYO V6	256K / 61.1 GB	19	7

Note: green Score (e.g. "73.2") means that the model is better than DavidAU/Qwen3-42B-A3B-2507-YOYO2-TOTAL-RECALL-Instruct.