What are the hardware requirements for Ling 2.6 Flash Mlx 6bit?

Ling 2.6 Flash Mlx 6bit requires approximately 85 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 6bit and how large is it?

Ling 2.6 Flash Mlx 6bit 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 6bit perform on standard benchmarks?

Ling 2.6 Flash Mlx 6bit 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 6bit by mlx-community — VRAM 85GB, 128K context

Name: Ling 2.6 Flash Mlx 6bit
Author: mlx-community

Ling 2.6 Flash Mlx 6bit is an open-source language model by mlx-community. Features: 104.2b LLM, VRAM: 85GB, Context: 128K, License: mit, Quantized, LLM Explorer Score: 0.38, ELO: 1485.

6-bit 6bit 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-6bit

Ling 2.6 Flash Mlx 6bit 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 6bit Parameters and Internals

LLM Name	Ling 2.6 Flash Mlx 6bit
Repository 🤗	https://huggingface.co/mlx-community/Ling-2.6-flash-mlx-6bit
Base Model(s)	inclusionAI/Ling-2.6-flash inclusionAI/Ling-2.6-flash
Model Size	104.2b
Required VRAM	85 GB
Updated	2026-08-10
Maintainer	mlx-community
Model Type	bailing_hybrid
Model Files	5.2 GB: 1-of-17 5.4 GB: 2-of-17 5.4 GB: 3-of-17 5.4 GB: 4-of-17 4.6 GB: 5-of-17 5.4 GB: 6-of-17 5.4 GB: 7-of-17 5.4 GB: 8-of-17 4.6 GB: 9-of-17 5.4 GB: 10-of-17 5.3 GB: 11-of-17 5.4 GB: 12-of-17 5.3 GB: 13-of-17 5.4 GB: 14-of-17 4.6 GB: 15-of-17 5.4 GB: 16-of-17 1.4 GB: 17-of-17
Supported Languages	en
Quantization Type	6bit
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 6bit 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 Ling 2.6 Flash Mlx 6bit

Best Alternatives	Context / RAM	Downloads	Likes
Ling 2.6 Flash Mlx 8bit	128K / 111.2 GB	69	1
Ling 2.6 Flash Mlx 5bit	128K / 71.6 GB	45	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

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Ling-2.6-flash-mlx-6bit.