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Qwen3.5-Flash vs GLM-5.2

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Qwen3.5-Flash Cost
$0.18
GLM-5.2 Cost
$2.28
Qwen3.5-Flash is 92% cheaper
FeatureQwen3.5-FlashGLM-5.2
ProviderAlibabaZhipu AI
Input Price (1M)$0.10$1.40
Output Price (1M)$0.40$4.40
Context Window1,000,0001,000,000

Verdict

Qwen3.5-Flash costs $0.10 per 1M input tokens and $0.40 per 1M output tokens. GLM-5.2 costs $1.40 per 1M input tokens and $4.40 per 1M output tokens. Qwen3.5-Flash is 93% cheaper on input tokens than GLM-5.2. For output tokens, Qwen3.5-Flash is the more affordable option at $0.40/1M vs $4.40.

On context window, Qwen3.5-Flash supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.

When to choose Qwen3.5-Flash

  • ✓ You need the lowest input token cost ($ 0.10/1M)
  • ✓ Your workload is output-heavy — Qwen3.5-Flash generates text cheaper
  • ✓ You are already integrated with Alibaba

When to choose GLM-5.2

  • ✓ You are already integrated with Zhipu AI

Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.

Frequently Asked Questions

Is Qwen3.5-Flash cheaper than GLM-5.2?

Qwen3.5-Flash is cheaper on input tokens at $0.10/1M vs $1.40/1M for GLM-5.2 — a 93% saving.

What is the context window of Qwen3.5-Flash vs GLM-5.2?

Qwen3.5-Flash has a 1,000,000-token context window. GLM-5.2 has a 1,000,000-token context window. Qwen3.5-Flash supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: Qwen3.5-Flash or GLM-5.2?

The best choice depends on your use case. For cost efficiency on input tokens, Qwen3.5-Flash is the cheaper option. For maximum context length, Qwen3.5-Flash supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.