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Z.ai: GLM 4.6V vs Qwen: Qwen3.5-122B-A10B

Head-to-head API cost, context, and performance comparison. Synced at 11:23:04 AM.

Executive Summary

When evaluating Z.ai: GLM 4.6V against Qwen: Qwen3.5-122B-A10B, the pricing structure is a key differentiator. Z.ai: GLM 4.6V is approximately 49% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Qwen: Qwen3.5-122B-A10B leads with a statistical ELO score of 1120. For tasks involving complex logic, coding, or instruction-following, developers might prefer Qwen: Qwen3.5-122B-A10B, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Z.ai: GLM 4.6V
Qwen: Qwen3.5-122B-A10B
Performance (ELO)
1120
1120
Input Cost / 1M
$0.30
$0.26
Output Cost / 1M
$0.90
$2.08
Context Window
131,072 tokens
262,144 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Z.ai: GLM 4.6V wins out aggressively in pricing.

People Also Ask

Is Z.ai: GLM 4.6V cheaper than Qwen: Qwen3.5-122B-A10B?

Yes. Z.ai: GLM 4.6V is cheaper for both input and output generation compared to Qwen: Qwen3.5-122B-A10B. Exploring alternatives often yields cost reductions.

Which model has the larger context window?

The Qwen: Qwen3.5-122B-A10B model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

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