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Alibaba Cloud (Qwen) Qwen3.7-Max VS OpenAI GPT-5.6 Terra

✍️ Analysis by:the whichllmmodel Editorial Team|📅 Updated: June 2026

Decision Recommendation

⚖️ Editorial Verdict: In our analysis, GPT-5.6 Terra is the premium intelligence choice, scoring 2.8% higher on coding benchmarks. However, this accuracy premium comes with a cost overhead: Qwen3.7-Max is 1.5x cheaper to run. If you are building high-volume, simple chatbots or processing massive amounts of text where budget is critical, Qwen3.7-Max offers excellent cost savings. For agentic reasoning, code refactoring, or complex logical tasks, the accuracy premium of GPT-5.6 Terra fully justifies the cost.
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Model Specs

Qwen3.7-Max

Benchmarks & Scores

Coding (swe-bench-pro)
60.6%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)
92.4%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)1.5x cheaper
$3.75Input: $2.50 | Output: $7.50
Context Window
1M tokens
Model Specs

GPT-5.6 Terra

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+2.8%)
63.4%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)Winner (+0.5%)
92.9%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)
$5.63Input: $2.50 | Output: $15.00
Context WindowLarger
1.05M tokens

Frequently Asked Questions about Qwen3.7-Max vs GPT-5.6 Terra comparison

Qwen3.7-Max is cheaper than GPT-5.6 Terra. Qwen3.7-Max has a blended cost of $3.75/1M tokens, which is about 1.5x cheaper than GPT-5.6 Terra at $5.63/1M tokens.

GPT-5.6 Terra is better for coding tasks on this benchmark. It scores 63.4% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to Qwen3.7-Max which scores 60.6%.