LLM ComparisonClaude 4.5 OpusQwen3-Max

Claude 4.5 Opus vs Qwen3-Max

Compare Claude 4.5 Opus and Qwen3-Max. Build AI products powered by either model on Appaca.

Model Comparison

FeatureClaude 4.5 OpusQwen3-Max
ProviderAnthropicAlibaba Cloud
Model Typetexttext
Context Window200,000 tokens262,144 tokens
Input Cost
$5.00/ 1M tokens
$0.86/ 1M tokens
Output Cost
$25.00/ 1M tokens
$3.44/ 1M tokens

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Strengths & Best Use Cases

Claude 4.5 Opus

Anthropic

1. Maximum capability with more practical pricing

  • Anthropic introduced Opus 4.5 as its most intelligent model, combining maximum capability with practical performance.
  • It was positioned as the best model in the world for coding, agents, and computer use at launch, with pricing reduced to $5/M input and $25/M output.

2. Step-change gains for coding and advanced agent work

  • Anthropic describes Opus 4.5 as state-of-the-art on real-world software engineering tests.
  • It also improved everyday knowledge-work tasks like deep research, slides, and spreadsheets while staying strong on long-horizon agent workflows.

3. Better control over reasoning depth

  • Opus 4.5 introduced the effort parameter, letting developers trade off response thoroughness against token efficiency.
  • This made it easier to use one flagship model across both high-depth analysis and more cost-sensitive production workloads.

4. Stronger computer use and continuity

  • Added enhanced computer use with a zoom action for inspecting detailed screen regions.
  • Preserves prior thinking blocks across turns, helping the model maintain reasoning continuity in extended multi-step tasks.

Qwen3-Max

Alibaba Cloud

1. Best performance in Qwen3 series

  • Handles complex multi-step reasoning.
  • Excellent for agent programming and tool calling.

2. Massive context window

  • 262K tokens enable long multi-document tasks.
  • Useful for RAG pipelines, analysis, and long-form workflows.

3. Tiered pricing support

  • More cost-efficient for small requests.
  • Supports context caching for repeated inputs.

4. Strong general-purpose intelligence

  • High accuracy in coding, reasoning, and structured tasks.
  • Reliable for enterprise automation.

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