Which is better for coding — GLM-4.7-Flash or Qwen3 VL 32B Thinking?

Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.

Which model is cheaper — GLM-4.7-Flash or Qwen3 VL 32B Thinking?

API pricing data is available on the individual model pages.

Which has a larger context window — GLM-4.7-Flash or Qwen3 VL 32B Thinking?

Context window data is available on the individual model pages.

GLM-4.7-Flash vs Qwen3 VL 32B Thinking: Specs & Benchmark Comparison

GLM-4.7-Flash

Zhipu AI

Qwen3 VL 32B Thinking

Alibaba

Characteristic	GLM-4.7-Flash	Qwen3 VL 32B Thinking
Company	Zhipu AI	Alibaba
Release Date	January 18, 2026	September 21, 2025
Parameters	30B	33B
Multimodal	No	Yes
Context (input)	128K	—
Context (output)	16K	—
Input Price / 1M	$0.07	—
Output Price / 1M	$0.40	—
Average Score	0.6	144.5

Verdict

Both models show equal results — the choice depends on your specific use case.

Overall Performance

Qwen3 VL 32B Thinking shows a higher average benchmark score: 144.5 vs 0.6.

Recency

GLM-4.7-Flash is newer: released 1/18/2026 vs 9/21/2025.

More About These Models

GLM-4.7-Flash

Zhipu AI — specs, benchmarks, API

Qwen3 VL 32B Thinking

Alibaba — specs, benchmarks, API

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GLM-4.7-Flash vs GLM-5 GLM-4.5 vs GLM-4.7-Flash GLM-4.7-Flash vs GPT-5.2 Codex GLM-4.7-Flash vs Mercury 2 GLM-4.7-Flash vs MiniMax M2.5 GLM-4.7-Flash vs GPT-5.3 Codex

All model comparisons →

The GLM-4.7-Flash and Qwen3 VL 32B Thinking comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the GLM-4.7-Flash or Qwen3 VL 32B Thinking page. See also the complete list of AI model comparisons.