What are the hardware requirements for Ling 2.6 Flash Mlx 8bit?

Ling 2.6 Flash Mlx 8bit requires approximately 111.2 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ling 2.6 Flash Mlx 8bit and how large is it?

Ling 2.6 Flash Mlx 8bit is developed by mlx-community, a model with 104.2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Ling 2.6 Flash Mlx 8bit perform on standard benchmarks?

Ling 2.6 Flash Mlx 8bit has the following published scores: LMSYS ELO 1485. Compare against reference models on this page or on the LLM Explorer leaderboards.

Ling 2.6 Flash Mlx 8bit by mlx-community — VRAM 111.2GB, 128K context

Name: Ling 2.6 Flash Mlx 8bit
Author: mlx-community

Ling 2.6 Flash Mlx 8bit is an open-source language model by mlx-community. Features: 104.2b LLM, VRAM: 111.2GB, Context: 128K, License: mit, Quantized, LLM Explorer Score: 0.38, ELO: 1485.

8-bit 8bit Bailing hybrid Base model:inclusionai/ling-2.... Base model:quantized:inclusion... Conversational Custom code En Mlx Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/Ling-2.6-flash-mlx-8bit

Ling 2.6 Flash Mlx 8bit Benchmarks

LMSys ELO 1485 vs 1272 (so35) 16.7%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Ling 2.6 Flash Mlx 8bit Parameters and Internals

LLM Name	Ling 2.6 Flash Mlx 8bit
Repository 🤗	https://huggingface.co/mlx-community/Ling-2.6-flash-mlx-8bit
Base Model(s)	inclusionAI/Ling-2.6-flash inclusionAI/Ling-2.6-flash
Model Size	104.2b
Required VRAM	111.2 GB
Updated	2026-08-10
Maintainer	mlx-community
Model Type	bailing_hybrid
Model Files	4.5 GB: 1-of-24 4.7 GB: 2-of-24 4.7 GB: 3-of-24 4.8 GB: 4-of-24 4.6 GB: 5-of-24 4.7 GB: 6-of-24 4.8 GB: 7-of-24 4.7 GB: 8-of-24 4.7 GB: 9-of-24 4.8 GB: 10-of-24 4.6 GB: 11-of-24 4.7 GB: 12-of-24 4.8 GB: 13-of-24 4.7 GB: 14-of-24 4.7 GB: 15-of-24 4.8 GB: 16-of-24 4.6 GB: 17-of-24 4.7 GB: 18-of-24 4.8 GB: 19-of-24 4.7 GB: 20-of-24 4.7 GB: 21-of-24 4.8 GB: 22-of-24 4.6 GB: 23-of-24 3.0 GB: 24-of-24
Supported Languages	en
Quantization Type	8bit
Model Architecture	BailingMoeV2_5ForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.56.2
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	157184
Torch Data Type	bfloat16

Rank the Ling 2.6 Flash Mlx 8bit 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 Ling 2.6 Flash Mlx 8bit

Best Alternatives	Context / RAM	Downloads	Likes
Ling 2.6 Flash Mlx 5bit	128K / 71.6 GB	45	1
Ling 2.6 Flash Mlx 6bit	128K / 85 GB	36	1
Ling 2.6 Flash Mlx 4bit DWQ	128K / 58.6 GB	82	7
Ling 2.6 Flash Mlx 4bit	128K / 58.6 GB	68	2
Ling 2.6 Flash Mlx 4bit Gs32	128K / 65.2 GB	22	2