Qwen 3.7 Max is ACTUALLY INSANE! (Real Tests and Review)

Qwen 3.7 Max finished a build that took Kimi 2.6 two to three hours in under nine minutes, and the creator is switching his personal stack to it.

Speed and Tool-Call Reliability

On the ancient Chinese 3D building test, Qwen 3.7 Max completed the full assembly in 8 minutes 53 seconds (6m API time, ~3m tool time), with a 100% success rate across 18 tool calls. Kimi 2.6 and Mimo needed two to three hours for the same prompt, and DeepSeek V4 Pro never produced a roof at all. The space-shooter one-shot added a dash mechanic, screen shake, and combo system that Kimi's version skipped entirely.

Pricing vs. Peers

Output tokens cost $7.50 per 1M tokens on Model Studio, putting it "one of the most expensive flagship models" — second only to Opus in the creator's view. Compare that to DeepSeek V4 Pro at $0.87/M output tokens and Kimi 2.6's coding plan, which "you barely hit the weekly usage limit." The first test alone burned ~850,000 tokens, and all three tests combined used 1.1M tokens.

The Free-Tier Trap

Model Studio gives you 1M free tokens, but you must enter payment details up front, and it "can charge your card automatically" once the quota is gone. The creator's warning: enable "free quota only" before running anything, otherwise the auto-billing kicks in silently.

Why It Holds Up on Long Runs

Alibaba trained 3.7 Max as an "agent first design" backbone meant to run "tens of hours and hundreds of tool calls without collapsing." Training mixed frameworks including Claude Code, OpenClaw, Qwen Code, Kilo Code, Open Code, and Hermes agent, and the reward function rewards "continued progress over long runs" while suppressing reward-hacking. The result: less context rot and more consistent tool-call reasoning across hour-long sessions — which is exactly why the creator says he's switching.

Token-Plan Caveat

Alibaba's token plan is "credits per seat per month," not a refreshable usage limit like Kimi's, so credits "can finish up your credits way faster than you think" on simple tasks.