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  4. Qwen3 Max
Alibaba
Released September 23, 2025Cutoff June 2025

Qwen3 Max

Qwen3 Max by Alibaba is a 1T+ parameter MoE model pretrained on 36T tokens, with Instruct and Thinking variants for coding, agentic tasks, and advanced reasoning.

Visit AlibabaAnnouncement
Inputs
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Outputs
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Model Overview

Capabilities, design details, and architectural traits

Qwen3 Max – Alibaba's Largest MoE Foundation Model

Qwen3 Max is Alibaba's largest and most capable language model to date, developed by the Qwen team under Alibaba Cloud. It is a Mixture-of-Experts (MoE) model with over 1 trillion parameters, pretrained on approximately 36 trillion tokens — roughly double the pretraining data used for its predecessor, Qwen2.5.

Two Deployment Variants

Qwen3 Max ships in two distinct variants with different operational profiles:

  • Qwen3-Max-Instruct — a production-ready non-thinking model optimized for coding, instruction following, agent tool-calling, and multilingual tasks. It is OpenAI API-compatible and available via Alibaba Cloud Model Studio (qwen3-max) and Qwen Chat.
  • Qwen3-Max-Thinking — a reasoning-focused variant that uses a code interpreter and parallel test-time compute scaling. When augmented with tool use, it is documented as achieving perfect scores on AIME 25 and HMMT mathematical reasoning benchmarks.

The Instruct variant targets low-latency inference, while the Thinking variant enables longer deliberation traces with explicit tool calls — a documented distinction that shapes how each is deployed in agentic workflows.

Access

Qwen3-Max-Instruct is available via Qwen Chat and through Alibaba Cloud Model Studio using an OpenAI-compatible API. The Thinking variant was in active training at the time of the official announcement and is being prepared for public release.

Benchmark Performance

Independent evaluations · Artificial Analysis

32.5%
Intelligence

Accuracy & Capability Details

GPQA - Graduate Science86.1%
Humanity's Last Exam28.0%
SciCode - Scientific Coding43.1%
Instruction Following70.7%
Long Context Reasoning70.3%
τ²-Bench - Agentic Tasks83.6%
TerminalBench - System Control24.2%
Specs
Context window
262Ktokens
Input pricing
$1.20per 1M tokens
Output pricing
$6per 1M tokens

Prices in USD.

Key Capabilities & Ratings

Coding70%
Advanced Math70%
Legal & E-Discovery70%
Agentic Actions70%
Financial Analysis70%

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderAlibabaAnthropicAnthropic
Release DateSeptember 23, 2025July 24, 2026June 9, 2026
Knowledge CutoffJun 2025May 2026-
Context & Limits
Context Window262K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$1.20
Best Input Pricing
$5$10
Output Pricing
$6
Best Output Pricing
$25$50
Modalities
Inputs
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textimage
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Outputs
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Benchmarks (0-100)
Intelligence Index24.5
63.1
Best Intelligence Index
62.1
Coding Index-
78.0
Best Coding Index
76.5
Agentic Index-
59.2
Best Agentic Index
56.6
Qwen3 Max
Claude Opus 5
Claude Fable 5

GPQA Benchmark

Graduate-level reasoning and expert Q&A evaluation.

76%
Qwen3 Max
GPQA Benchmark
Score: 76%
Qwen3 Max
93%
Claude Opus 5
GPQA Benchmark
Score: 93%
Claude Opus 5
93%
Claude Fable 5
GPQA Benchmark
Score: 93%
Claude Fable 5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

12%
Qwen3 Max
Humanity's Last Exam
Score: 12%
Qwen3 Max
55%
Claude Opus 5
Humanity's Last Exam
Score: 55%
Claude Opus 5
56%
Claude Fable 5
Humanity's Last Exam
Score: 56%
Claude Fable 5

Long Context Reasoning

Logical reasoning over long context windows.

48%
Qwen3 Max
Long Context Reasoning
Score: 48%
Qwen3 Max
76%
Claude Opus 5
Long Context Reasoning
Score: 76%
Claude Opus 5
77%
Claude Fable 5
Long Context Reasoning
Score: 77%
Claude Fable 5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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