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GLM-4.6 vs GPT-5 nano
Comprehensive side-by-side LLM comparison
GLM-4.6 leads with 9.3% higher average benchmark score. GPT-5 nano offers 331.4K more tokens in context window than GLM-4.6. GPT-5 nano is $2.15 cheaper per million tokens. Overall, GLM-4.6 is the stronger choice for coding tasks.
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Zhipu AI
GLM-4.6 was introduced as an enhanced iteration of the GLM-4 series, designed to provide improved capabilities in bilingual language understanding and generation. Built to incorporate refinements to the GLM architecture, it represents continued advancement in Zhipu AI's model development.
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OpenAI
GPT-5 Nano was developed as the most compact variant in the GPT-5 family, designed for deployment in resource-constrained environments and edge computing scenarios. Built to bring next-generation AI capabilities to devices and applications where latency and efficiency are paramount, it distills GPT-5 innovations into a minimal footprint.
1 month newer
GPT-5 nano
OpenAI
2025-08-07
GLM-4.6
Zhipu AI
2025-09-30
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Pricing Comparison
Cost per million tokens (USD)
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GLM-4.6
Input:$0.60
Output:$2.00
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GPT-5 nano
Input:$0.05
Output:$0.40($2.15 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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GLM-4.6
Average Score:87.5%(+9.3%)
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GPT-5 nano
Average Score:78.2%
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GLM-4.6
2 providers
DeepInfra
Throughput: 85 tok/s
Latency: 0.7ms
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
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GPT-5 nano
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GLM-4.6
Avg Score:87.5%(+9.3%)
Providers:2
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GPT-5 nano
Avg Score:78.2%
Providers:2