What are the hardware requirements for Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER?

Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER requires approximately 84.8 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER?

Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER 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 Thinking TOTAL RECALL V2 Medium MASTER CODER by DavidAU — VRAM 84.8GB, 256K context

Name: Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER
Author: DavidAU

Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER is an open-source language model by DavidAU. Features: 30b LLM, VRAM: 84.8GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.19.

Arxiv:2401.02415 128 experts 256k context 8 active experts Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-30b-a3b-... Brainstorm Brainstorm 20x Chat Code Code generation Codegen Codeqwen Coder Coding Conversational De En Endpoints compatible Finetuned Fr Mixture of experts Moe Qwen Qwen-coder Qwen2 Qwen3 Qwen3-30b-a3b Qwen3-30b-a3b-thinking-2507 Qwen3 moe Reasoning Region:us Safetensors Sharded Tensorflow Thinking Zh

Model Card on HF 🤗: https://huggingface.co/DavidAU/Qwen3-42B-A3B-2507-Thinking-TOTAL-RECALL-v2-Medium-MASTER-CODER

Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER Parameters and Internals

LLM Name	Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER
Repository 🤗	https://huggingface.co/DavidAU/Qwen3-42B-A3B-2507-Thinking-TOTAL-RECALL-v2-Medium-MASTER-CODER
Base Model(s)	Qwen3 30B A3B Thinking 2507 Qwen/Qwen3-30B-A3B-Thinking-2507
Model Size	30b
Required VRAM	84.8 GB
Updated	2026-08-19
Maintainer	DavidAU
Model Type	qwen3_moe
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
Model Architecture	Qwen3MoeForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.52.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER 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 Qwen3 42B A3B 2507 Thinking TOTAL RECALL V2 Medium MASTER CODER

Best Alternatives	Context / RAM	Downloads	Likes
...LL MASTER CODER M 1million Ctx	1024K / 84.8 GB	176	9
... 42B A3B Thinking Total Recall	986K / 84.8 GB	26	0
Qwen3 30B A3B YOYO V3	986K / 61.1 GB	11	7
...07 YOYO2 TOTAL RECALL Instruct	986K / 84.8 GB	27	1
...07 YOYO2 TOTAL RECALL Instruct	986K / 106 GB	20	0
Qwen3 30B A3B YOYO V2	986K / 61.1 GB	19	4
Qwen3 30B A3B Instruct 2507	256K / 61.1 GB	3937	13
Qwen3 Coder 30B A3B Instruct	256K / 61.1 GB	1746771	1168
Qwen3 30B A3B Instruct 2507	256K / 61.1 GB	1903736	824
...en3 Coder 30B A3B Instruct FP8	256K / 31.2 GB	1556690	191

Note: green Score (e.g. "73.2") means that the model is better than DavidAU/Qwen3-42B-A3B-2507-Thinking-TOTAL-RECALL-v2-Medium-MASTER-CODER.