Claude 4.6 Opus vs Qwen-Long
Compare pricing, context windows, and strengths for Claude 4.6 Opus by Anthropic and Qwen-Long by Alibaba Cloud - and see how to put either to work in Appaca.
Claude 4.6 Opus
Anthropic's most intelligent model for building agents and coding, with stronger reliability and precision for long-horizon engineering and enterprise workflows.
View Claude 4.6 OpusQwen-Long
Long-context model with 10M tokens for huge document analysis and summarization.
View Qwen-LongClaude 4.6 Opus vs Qwen-Long at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | Claude 4.6 Opus | Qwen-Long |
|---|---|---|
| Provider | Anthropic | Alibaba Cloud |
| Model type | Text | Text |
| Context window | 1M tokens | 10M tokens |
| Input price | $5 / 1M tokens | $0.072 / 1M tokens |
| Output price | $25 / 1M tokens | $0.287 / 1M tokens |
| Status | Current | Current |
How Claude 4.6 Opus and Qwen-Long differ
What the numbers mean in practice when choosing between Claude 4.6 Opus and Qwen-Long.
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Qwen-Long is 99% cheaper on input tokens ($0.072 vs $5 per million), which adds up quickly in document-heavy workloads.
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Qwen-Long is 99% cheaper on output tokens ($0.287 vs $25 per million) - the bigger factor for tools that generate long documents.
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Qwen-Long's 10M tokens context window is roughly 10x larger than Claude 4.6 Opus's 1M tokens, so it can work across bigger codebases, contracts, or archives in one pass.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
Claude 4.6 Opus
1. Anthropic's top model for coding and agents
- Anthropic positions Opus 4.6 as its most intelligent model for building agents and coding.
- It builds on Opus 4.5 with higher reliability and precision for professional software engineering, complex agentic workflows, and high-stakes enterprise tasks.
2. Strong frontier performance on real agent benchmarks
- Anthropic reports state-of-the-art results across coding and agentic evaluations.
- Public benchmark highlights include 65.4% on Terminal-Bench 2.0, 72.7% on OSWorld, and 90.2% on BigLaw Bench.
3. Best fit for long-horizon, high-context work
- Supports up to a 1M token context window in beta and up to 128K output tokens.
- Designed for long-running tasks that need sustained planning, careful debugging, code review, and strong context retention.
4. Advanced reasoning controls and workflow support
- Supports adaptive thinking and the
effortparameter, including the newmaxeffort level. - Anthropic also introduced fast mode, compaction, and dynamic filtering with web search and web fetch for Opus 4.6-era agent workflows.
Qwen-Long
1. Extremely long context window
- Up to 10 million tokens.
2. Ideal for document-heavy workflows
- Legal, financial, RAG, compliance, research.
3. Low-cost for large-scale ingestion
- Optimized pricing for big inputs.
Use Claude 4.6 Opus or Qwen-Long - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Claude 4.6 Opus or Qwen-Long - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need and it builds a working app powered by Claude 4.6 Opus or Qwen-Long. No code, no API keys, no deployment.
Switch models without rebuilding
Start on Claude 4.6 Opus, test the same tool on Qwen-Long, and keep whichever performs better - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs and it builds a working app powered by Claude 4.6 Opus or Qwen-Long - connected to the tools you already use.
Related comparisons
See how Claude 4.6 Opus and Qwen-Long stack up against other models in the directory.
FAQs
Qwen-Long is generally cheaper: $0.072 input / $0.287 output per million tokens, versus $5 / $25 for Claude 4.6 Opus. Actual cost depends on how many tokens your workload reads and writes.
Qwen-Long has the larger context window at 10M tokens, compared to 1M tokens for Claude 4.6 Opus. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.
It depends on the job. Compare the pricing, context window, and strengths above against your workload - and remember the choice isn't permanent. In Appaca you can build a tool on Claude 4.6 Opus, test the same tool on Qwen-Long, and switch at any time without rebuilding anything.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by Claude 4.6 Opus, Qwen-Long, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build AI tools with Claude 4.6 Opus or Qwen-Long
Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.