What are the hardware requirements for Qwen3.6 29B REAP Opus Reasoning Distill MTP?

Qwen3.6 29B REAP Opus Reasoning Distill MTP requires approximately 56.5 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.

Who developed Qwen3.6 29B REAP Opus Reasoning Distill MTP and how large is it?

Qwen3.6 29B REAP Opus Reasoning Distill MTP is developed by barozp, a model with 28.2b 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 Qwen3.6 29B REAP Opus Reasoning Distill MTP?

Qwen3.6 29B REAP Opus Reasoning Distill MTP is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.6 29B REAP Opus Reasoning Distill MTP by barozp — VRAM 56.5GB, 256K context

Name: Qwen3.6 29B REAP Opus Reasoning Distill MTP
Author: barozp

Qwen3.6 29B REAP Opus Reasoning Distill MTP is an open-source language model by barozp. Features: 28.2b LLM, VRAM: 56.5GB, Context: 256K, License: apache-2.0, MoE, LLM Explorer Score: 0.26.

Arxiv:2510.13999 Base model:barozp/qwen3.6-29b-... Base model:finetune:barozp/qwe... Conversational Expert-pruning Lora Moe Mtp Qwen3 Qwen3 5 moe text Reap Reasoning Region:us Safetensors Sharded Speculative-decoding Tensorflow

Model Card on HF 🤗: https://huggingface.co/barozp/Qwen3.6-29B-REAP-Opus-Reasoning-Distill-MTP

Qwen3.6 29B REAP Opus Reasoning Distill MTP Parameters and Internals

LLM Name	Qwen3.6 29B REAP Opus Reasoning Distill MTP
Repository 🤗	https://huggingface.co/barozp/Qwen3.6-29B-REAP-Opus-Reasoning-Distill-MTP
Base Model(s)	barozp/Qwen3.6-29B-REAP-Opus-Reasoning-Distill barozp/Qwen3.6-29B-REAP-Opus-Reasoning-Distill
Model Size	28.2b
Required VRAM	56.5 GB
Updated	2026-08-04
Maintainer	barozp
Model Type	qwen3_5_moe_text
Model Files	3.9 GB: 1-of-16 3.6 GB: 2-of-16 3.2 GB: 3-of-16 3.6 GB: 4-of-16 4.0 GB: 5-of-16 3.3 GB: 6-of-16 3.6 GB: 7-of-16 4.0 GB: 8-of-16 3.3 GB: 9-of-16 3.6 GB: 10-of-16 4.0 GB: 11-of-16 3.3 GB: 12-of-16 3.6 GB: 13-of-16 4.0 GB: 14-of-16 3.3 GB: 15-of-16 2.2 GB: 16-of-16 1.4 GB
Model Architecture	Qwen3_5MoeForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.13.1
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwen3.6 29B REAP Opus Reasoning Distill MTP 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

Quantized Models of the Qwen3.6 29B REAP Opus Reasoning Distill MTP

Model	Likes	Downloads	VRAM
...B REAP Opus Distill MTPLX 3bit	2	202	12 GB

Best Alternatives to Qwen3.6 29B REAP Opus Reasoning Distill MTP

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.6 28B REAP	256K / 56.5 GB	1773	16

Note: green Score (e.g. "73.2") means that the model is better than barozp/Qwen3.6-29B-REAP-Opus-Reasoning-Distill-MTP.