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Qwen: Qwen3 235B A22B Thinking 2507 vs Z.ai: GLM 5 Turbo

Head-to-head API cost, context, and performance comparison. Synced at 11:20:23 AM.

Executive Summary

When evaluating Qwen: Qwen3 235B A22B Thinking 2507 against Z.ai: GLM 5 Turbo, the pricing structure is a key differentiator. Qwen: Qwen3 235B A22B Thinking 2507 is approximately 83% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Z.ai: GLM 5 Turbo leads with a statistical ELO score of 1120. For tasks involving complex logic, coding, or instruction-following, developers might prefer Z.ai: GLM 5 Turbo, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Qwen: Qwen3 235B A22B Thinking 2507
Z.ai: GLM 5 Turbo
Performance (ELO)
1120
1120
Input Cost / 1M
$0.11
$0.96
Output Cost / 1M
$0.60
$3.20
Context Window
262,144 tokens
202,752 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Qwen: Qwen3 235B A22B Thinking 2507 wins out aggressively in pricing.

People Also Ask

Is Qwen: Qwen3 235B A22B Thinking 2507 cheaper than Z.ai: GLM 5 Turbo?

Yes. Qwen: Qwen3 235B A22B Thinking 2507 is cheaper for both input and output generation compared to Z.ai: GLM 5 Turbo. Exploring alternatives often yields cost reductions.

Which model has the larger context window?

The Qwen: Qwen3 235B A22B Thinking 2507 model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

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