Does Qwen 3.5 live up to the hype?

I tested 9 local LLMs on a Claude Code skill I actually use every day. Not a coding benchmark. A real multi-step agentic task described in natural language as a markdown file.

My /linkedin-cover-image skill works like this:

• Read a LinkedIn post file and analyze the content
• Decide if it is a post or article and choose the correct dimension
• Pick the right layout template (quote, listicle, contrast)
• Write a complete HTML cover image - typography, colors, spacing, decorative elements
• Screenshot it to PNG

One command. No hand-holding. The model handles the entire workflow.

Same post. Same skill. One shot each. All results in the images.

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Out of 9 models (5 usable / 2 issues / 2 failed):

Usable:

• GLM 4.7 Flash - Best. Highlighted both contrast keywords (“demo” and “DevOps”). Clean output.
• Qwen 3 VL (32B) - Nice layout, clean. Only highlighted “DevOps”, missed the contrast on “demo”.
• Qwen 3 VL (30B) - Similar to 32B. Clean but missed the “demo” highlight.
• GPT-OSS (20B) - Usable but not as polished.
• Qwen 3 (30B) - Clean output though arguably highlighted the wrong keyword.

Issues:

• Qwen 3.5 (35B) - Got the content right but the layout of the last sentence is off.
• Qwen 3 Coder (30B) - Long winded, highlighted the same wrong keyword as Qwen 3, and created an article cover instead of a post cover. Needed a follow-up prompt.

Failed:

• Devstral Small 2 - Kept saying “I will create the HTML cover” then produced nothing.
• Magistral 24B - Same. Repeated the loop and never wrote a file. (See screenshot)

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Last image is Opus 4.6 for comparison. Network graph decorations, gradient effects, clean text hierarchy. The gap is still visible but GLM 4.7 Flash got closer than I expected.

Everyone benchmarks local LLMs on some standard benchmark. I do it on a real daily use case.

Multi-step agentic workflows where the model reads context, makes real world decisions, and writes a complete file - that is where you see the real gap.

GLM 4.7 Flash probably got the closest I have seen from any local model. I think it is usable for some tasks now.

#AI #ClaudeCode #LocalLLM

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