What are the hardware requirements for Qwen3.8 2.4T A95B MXFP4 CT AutoRound?

Qwen3.8 2.4T A95B MXFP4 CT AutoRound requires approximately 273.4 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 Qwen3.8 2.4T A95B MXFP4 CT AutoRound and how large is it?

Qwen3.8 2.4T A95B MXFP4 CT AutoRound is developed by INCModel2, a model with 2446.2b 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 Qwen3.8 2.4T A95B MXFP4 CT AutoRound?

Qwen3.8 2.4T A95B MXFP4 CT AutoRound is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 2.4T A95B MXFP4 CT AutoRound by INCModel2 — VRAM 273.4GB, 256K context

Name: Qwen3.8 2.4T A95B MXFP4 CT AutoRound
Author: INCModel2

Qwen3.8 2.4T A95B MXFP4 CT AutoRound is an open-source language model by INCModel2. Features: 2446.2b LLM, VRAM: 273.4GB, Context: 256K, License: other, MoE, LLM Explorer Score: 0.31.

8-bit Compressed-tensors Conversational Endpoints compatible Moe Qwen3 5 moe text Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/INCModel2/Qwen3.8-2.4T-A95B-MXFP4-CT-AutoRound

Qwen3.8 2.4T A95B MXFP4 CT AutoRound Parameters and Internals

LLM Name	Qwen3.8 2.4T A95B MXFP4 CT AutoRound
Repository 🤗	https://huggingface.co/INCModel2/Qwen3.8-2.4T-A95B-MXFP4-CT-AutoRound
Model Size	2446.2b
Required VRAM	273.4 GB
Updated	2026-08-15
Maintainer	INCModel2
Model Type	qwen3_5_moe_text
Model Files	4.1 GB: 1-of-213 4.1 GB: 2-of-213 4.0 GB: 3-of-213 4.6 GB: 4-of-213 9.1 GB: 5-of-213 4.6 GB: 6-of-213 9.1 GB: 7-of-213 4.6 GB: 8-of-213 9.1 GB: 9-of-213 4.0 GB: 10-of-213 4.6 GB: 11-of-213 9.1 GB: 12-of-213 4.6 GB: 13-of-213 9.1 GB: 14-of-213 4.6 GB: 15-of-213 9.1 GB: 16-of-213 4.6 GB: 17-of-213 9.1 GB: 18-of-213 3.9 GB: 19-of-213 4.6 GB: 20-of-213 9.1 GB: 21-of-213 4.6 GB: 22-of-213 9.1 GB: 23-of-213 4.6 GB: 24-of-213 9.1 GB: 25-of-213 4.6 GB: 26-of-213 9.1 GB: 27-of-213 2.8 GB: 28-of-213 4.6 GB: 29-of-213 9.1 GB: 30-of-213 4.6 GB: 31-of-213 9.1 GB: 32-of-213 4.6 GB: 33-of-213 9.1 GB: 34-of-213 4.6 GB: 35-of-213 9.1 GB: 36-of-213 3.9 GB: 37-of-213 4.6 GB: 38-of-213 9.1 GB: 39-of-213 4.6 GB: 40-of-213 9.1 GB: 41-of-213 4.6 GB: 42-of-213 9.1 GB: 43-of-213
Model Architecture	Qwen3_5MoeForCausalLM
License	other
Context Length	262144
Model Max Length	262144
Transformers Version	4.57.3
Vocabulary Size	248320

Rank the Qwen3.8 2.4T A95B MXFP4 CT AutoRound 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 Qwen3.8 2.4T A95B MXFP4 CT AutoRound

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 2.4T A95B	256K / 999.3 GB	978	407
Qwen3.8 2.4T A95B FP8	256K / 509.1 GB	3851	99

Note: green Score (e.g. "73.2") means that the model is better than INCModel2/Qwen3.8-2.4T-A95B-MXFP4-CT-AutoRound.