OpenAI GPT-5.6 Sol vs Qwen3.7 Max: Code or Cost
My card goes to OpenAI GPT-5.6 Sol for serious coding work, but Qwen3.7 Max lands the cleaner value punch for broad knowledge-heavy tasks. This isn’t a wipeout. The 2026 frontier is tight, with the top 15 models separated by as little as 3 percentage points, so price now hits hard.
Coding: GPT-5.6 Sol owns the sharper jab
On the numbers we have, GPT-5.6 Sol is the coding specialist to beat. It leads SWE-bench at 96.2%, which is exactly the kind of score that matters when the job is fixing real repo issues instead of answering trivia in a vacuum.
Qwen3.7 Max doesn’t have a cited SWE-bench score in the material here, so I’m not going to pretend it loses a benchmark we weren’t given. Fair is fair. But if your team is choosing based on the visible coding stat, GPT-5.6 Sol walks to center ring with the cleaner evidence.
Knowledge: Qwen3.7 Max answers back
Qwen3.7 Max has its own belt: it leads MMLU with 93.7%. That makes it a strong pick for research support, classification, analysis, and general question-answering where broad academic-style coverage matters.
GPT-5.6 Sol may still be a strong all-around model, but the supplied numbers don’t give it the MMLU crown. In this lane, Qwen3.7 Max isn’t the budget undercard — it’s carrying a headline score.
Price: Qwen3.7 Max hits four times cheaper on output
Here’s where the fight tilts. GPT-5.6 Sol costs $5.00/1M input tokens and $30.00/1M output tokens. Qwen3.7 Max costs $2.50/1M input tokens and $7.50/1M output tokens.
That means Qwen3.7 Max is half the input price and one quarter the output price. For chatty workloads, long reports, and high-volume agents, that output gap can matter more than a narrow benchmark edge.