This is a community discussion asking whether Qwen3.8-Max is really suitable for programming. The feedback is polarized: some users consider it close to Claude/GPT, while others find it slow, expensive, and prone to overthinking. Another user used it to generate several web games and a Rust neural-network editor and considered the model extremely strong, but said requirements need to be specific enough. The common thread is that model capability, price, task scale, and prompt quality must be evaluated together.
One user said it was “very much on par” with Claude/GPT, but that Alibaba's coding-plan quota was not generous enough.
One user said the standard plan consumed about 60% of the weekly quota in two or three prompts.
One user cited Artificial Analysis's Software Engineering metric and said it was “good, but not as good as Anthropic/OpenAI, or Qwen3.7-Max.”
One user felt that a single reasoning step could last two minutes, or even five to eight minutes.
Complex web-game and native Rust editor examples suggest the model can deliver runnable projects, but it “won't proactively add requirements you didn't mention”; goals need to be described specifically and completely.
Another user felt that in everyday create-web-app tasks, Qwen Max's advantage over the larger model may not be particularly noticeable; a reasonable harness and skills still matter.
Qwen3.8-Max is worth including in the candidate pool for complex coding and agent tasks, but it should be compared by “successful cost per task,” not one-off price. Before launch, track first-pass rate, elapsed time, output tokens, human revision time, and quota consumption.
I keep seeing people say Qwen 3.8 Max is really good for coding. Has anyone actually used it? How good is it compared to… This is a necessary excerpt; read the original source for full context.
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Qwen3.8 Max
