Anthropic Claude Opus 5 (1M context) vs Alibaba Qwen 3.8 (256k)
Side-by-side comparison of pricing, context window, capabilities, and a real-cost sample workload.
Option A
Anthropic Claude Opus 5 (1M context)
by Anthropic
Context:1M
Input:$6.00 / 1M
Output:$30.00 / 1M
Released:2026-07
Option B
Alibaba Qwen 3.8 (256k)
by Alibaba
Context:256K
Input:$0.90 / 1M
Output:$3.60 / 1M
Released:2026-07
Detailed Comparison
| Dimension | Anthropic Claude Opus 5 (1M context) | Alibaba Qwen 3.8 (256k) |
|---|---|---|
| Provider | Anthropic | Alibaba |
| Context window Winner | 1M | 256K |
| Input price ($/1M) Winner | $6.00 | $0.90 |
| Output price ($/1M) Winner | $30.00 | $3.60 |
| Sample workload cost Winner 1M input + 500K output tokens | $21.00 | $2.70 |
| Released TieTie | 2026-07 | 2026-07 |
| Tokenizer | claude-4 | qwen |
The verdict
On the dimensions we measured, Alibaba Qwen 3.8 (256k) wins more often - particularly on cost-effectiveness for a typical 1M+0.5M workload.
Anthropic Claude Opus 5 (1M context) - Key features
The 1M-token context tier of Claude Opus 5. Same model, long-context premium pricing applied to requests above 200K input tokens. Built for whole-repository and whole-corpus work.
- 1M token context window
- Whole-repository reasoning
- Long-context premium tier
- Prompt caching support
- Adaptive effort control
Alibaba Qwen 3.8 (256k) - Key features
Alibaba's Qwen 3.8 flagship. A sparse MoE model with 256K context, first-class support for more than 100 languages and a notable jump in tool-calling reliability over Qwen 3.
- 256K token context window
- 100+ language support
- Sparse MoE architecture
- Improved tool calling
- Open-weight release
How to choose
- Pick the cheaper model if your workload is mostly straightforward classification, extraction, or summarization.
- Pick the bigger context if you process long documents, large codebases, or multi-document research.
- Pick the more recent release if you need state-of-the-art reasoning quality and don't mind paying a bit more.
- Use both via a routing layer - send simple tasks to the cheaper one and complex tasks to the smarter one. This is the highest-ROI optimization in production AI.
Estimate the real cost of either model for your prompts using our Token Calculator.