Qwen3-Max

Qwen3-Max

Alibaba
Tev1

Tev1

Together AI
+
+

Related Products

  • Gemini Enterprise Agent Platform
    1,161 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Google AI Studio
    41 Ratings
    Visit Website
  • Dialpad Support
    1,607 Ratings
    Visit Website
  • InEight
    168 Ratings
    Visit Website
  • Admin By Request Endpoint Privilege Management
    105 Ratings
    Visit Website
  • Forethought
    166 Ratings
    Visit Website
  • Nexo
    18,780 Ratings
    Visit Website
  • kama.ai
    9 Ratings
    Visit Website
  • Checksum.ai
    2 Ratings
    Visit Website

About

Qwen3-Max is Alibaba’s latest trillion-parameter large language model, designed to push performance in agentic tasks, coding, reasoning, and long-context processing. It is built atop the Qwen3 family and benefits from the architectural, training, and inference advances introduced there; mixing thinker and non-thinker modes, a “thinking budget” mechanism, and support for dynamic mode switching based on complexity. The model reportedly processes extremely long inputs (hundreds of thousands of tokens), supports tool invocation, and exhibits strong performance on benchmarks in coding, multi-step reasoning, and agent benchmarks (e.g., Tau2-Bench). While its initial variant emphasizes instruction following (non-thinking mode), Alibaba plans to bring reasoning capabilities online to enable autonomous agent behavior. Qwen3-Max inherits multilingual support and extensive pretraining on trillions of tokens, and it is delivered via API interfaces compatible with OpenAI-style functions.

About

Tev1 is a fast decision and classification model built by Together AI and fine-tuned from Qwen3.5 4B. It is designed around a simple interface: provide a piece of state, a question, and 2 to 24 labeled options, and the model returns exactly one letter that software can map back to a semantic key. This structure supports production tasks such as routing support tickets, evaluating automated returns, applying policy rules, rating sentiment, categorizing documents, and inserting deterministic decision points into larger agent pipelines. The model has 4.7B parameters, a 32.8K-token context window, and runs with non-thinking generation for fast, predictable classification. It was trained on 37,840 examples spanning intent detection, boolean comprehension, sentiment, policy application, routing, news categories, and research-paper taxonomy. Recommended settings use temperature 0 and a very small output budget so responses remain stable and easy to parse.

Platforms Supported

Windows Supported
Mac Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI product teams and research groups building agentic systems seeking an AI model with improved performance in coding and agent capabilities

Audience

Developers and AI engineering teams seeking to route, classify, score, and apply policy decisions through fast, deterministic structured outputs

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Supported
Free Trial Supported

Pricing

$0.04 per 1M tokens
Free Version Supported
Free Trial Not Supported

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

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Alibaba
Founded: 1999
China
qwen.ai

Company Information

Together AI
Founded: 2022
United States
www.together.ai/models/tev1-4b-experimental

Alternatives

Alternatives

Clef-flash

Clef-flash

Cloudflare
Claude Opus 4.1

Claude Opus 4.1

Anthropic
Clef

Clef

Cloudflare
Claude Opus 4.5

Claude Opus 4.5

Anthropic
Jev

Jev

TypeSafe AI
Qwen 4

Qwen 4

Alibaba
Qwen2.5-Max

Qwen2.5-Max

Alibaba

Categories

AI Models Supported

Categories

AI Decision Models Supported

Integrations

Alibaba Cloud Supported
Constellation Gate AI Supported
OpenAI Supported
OpenClaw Supported
Python Not Supported
Qwen Studio Supported
Qwen3.5 Not Supported
Shiori Supported
Sup AI Supported
TypeScript Not Supported
Use AI Supported

Integrations

Alibaba Cloud Not Supported
Constellation Gate AI Not Supported
OpenAI Not Supported
OpenClaw Not Supported
Python Supported
Qwen Studio Not Supported
Qwen3.5 Supported
Shiori Not Supported
Sup AI Not Supported
TypeScript Supported
Use AI Not Supported
Claim Qwen3-Max and update features and information
Claim Qwen3-Max and update features and information
Claim Tev1 and update features and information
Claim Tev1 and update features and information