Back to Value Frontier

Z.ai: GLM 4.6 vs Qwen: Qwen3.5-27B

Head-to-head API cost, context, and performance comparison. Synced at 11:20:18 AM.

Executive Summary

When evaluating Z.ai: GLM 4.6 against Qwen: Qwen3.5-27B, the pricing structure is a key differentiator. Qwen: Qwen3.5-27B is approximately 23% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Qwen: Qwen3.5-27B leads with a statistical ELO score of 1120. For tasks involving complex logic, coding, or instruction-following, developers might prefer Qwen: Qwen3.5-27B, provided their budget allows for the API burn rate.

Arbitrage Alert

You are losing 23%
per million tokens by hardcoding Z.ai: GLM 4.6.

Stop guessing exactly which model to route to. Deploy the 0ms Intelligence Engine to automatically arbitrage this 23% gap in your production environment instantly.

23% Instant Profit Margin Recovery
Node.js Enterprise SDK included

Raw Technical comparison

Metric
Z.ai: GLM 4.6
Qwen: Qwen3.5-27B
Performance (ELO)
1120
1120
Input Cost / 1M
$0.39
$0.20
Output Cost / 1M
$1.90
$1.56
Context Window
204,800 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, Qwen: Qwen3.5-27B wins out aggressively in pricing.

People Also Ask

Is Z.ai: GLM 4.6 cheaper than Qwen: Qwen3.5-27B?

No. Qwen: Qwen3.5-27B is the more cost-effective model, operating at a lower price point per 1 million tokens.

Which model has the larger context window?

The Qwen: Qwen3.5-27B model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

Related Comparisons

Compare Z.ai: GLM 4.6 vs Hunter AlphaCompare Z.ai: GLM 4.6 vs Healer AlphaCompare Z.ai: GLM 4.6 vs NVIDIA: Nemotron 3 Super (free)Compare Z.ai: GLM 4.6 vs MiniMax: MiniMax M2.5 (free)