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GLM-4.6 vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
GLM-4.6 leads with 30.7% higher average benchmark score. GPT-4.1 nano offers 883.7K more tokens in context window than GLM-4.6. GPT-4.1 nano is $2.10 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-4.1 Nano was developed as the smallest and most efficient variant in the GPT-4.1 family, designed for applications requiring minimal latency and resource usage. Built to enable AI capabilities on edge devices and resource-constrained environments, it distills GPT-4.1 capabilities into an ultra-compact form factor.
5 months newer
GPT-4.1 nano
OpenAI
2025-04-14
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-4.1 nano
Input:$0.10
Output:$0.40($2.10 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GLM-4.6
Average Score:81.0%(+30.7%)
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GPT-4.1 nano
Average Score:50.3%
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
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-4.1 nano
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GLM-4.6
Avg Score:81.0%(+30.7%)
Providers:2
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GPT-4.1 nano
Avg Score:50.3%
Providers:1