Qwen2.5-Max

Qwen2.5-Max

Alibaba
Tinker

Tinker

Thinking Machines Lab
+
+

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About

Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.

About

Tinker is a training API designed for researchers and developers that allows full control over model fine-tuning while abstracting away the infrastructure complexity. It supports primitives and enables users to build custom training loops, supervision logic, and reinforcement learning flows. It currently supports LoRA fine-tuning on open-weight models across both LLama and Qwen families, ranging from small models to large mixture-of-experts architectures. Users write Python code to handle data, loss functions, and algorithmic logic; Tinker handles scheduling, resource allocation, distributed training, and failure recovery behind the scenes. The service lets users download model weights at different checkpoints and doesn’t force them to manage the compute environment. Tinker is delivered as a managed offering; training jobs run on Thinking Machines’ internal GPU infrastructure, freeing users from cluster orchestration.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI researchers, developers, and enterprises seeking a high-performance Mixture-of-Experts model for advanced reasoning, coding, and language tasks, accessible via API and interactive chat

Audience

AI researchers and ML engineers requiring a solution to experiment with fine-tuning open source language models while outsourcing infrastructure complexity

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Alibaba
Founded: 1999
China
qwenlm.github.io/blog/qwen2.5-max/

Company Information

Thinking Machines Lab
United States
thinkingmachines.ai/tinker/

Alternatives

DeepSeek R2

DeepSeek R2

DeepSeek

Alternatives

ERNIE 4.5

ERNIE 4.5

Baidu
ERNIE X1

ERNIE X1

Baidu
Qwen2

Qwen2

Alibaba
LLaMA-Factory

LLaMA-Factory

hoshi-hiyouga
Qwen3.6

Qwen3.6

Alibaba

Categories

Categories

Integrations

Alibaba Cloud
Hugging Face
Llama 3
Llama 3.1
Llama 3.2
Llama 3.3
ModelScope
Python
Qwen
Qwen Studio
Qwen3

Integrations

Alibaba Cloud
Hugging Face
Llama 3
Llama 3.1
Llama 3.2
Llama 3.3
ModelScope
Python
Qwen
Qwen Studio
Qwen3
Claim Qwen2.5-Max and update features and information
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