+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
GLM-4.6 vs GPT-3.5 Turbo
Comprehensive side-by-side LLM comparison
GLM-4.6 leads with 50.2% higher average benchmark score. GLM-4.6 offers 176.1K more tokens in context window than GPT-3.5 Turbo. GPT-3.5 Turbo is $0.60 cheaper per million tokens. GLM-4.6 supports multimodal inputs. Overall, GLM-4.6 is the stronger choice for coding tasks.
+
+
+
+
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.
+
+
+
+
OpenAI
GPT-3.5 Turbo was developed as an optimized version of GPT-3.5, designed to provide a balance of capability and efficiency for conversational and completion tasks. Built to serve as a cost-effective option for applications requiring reliable language understanding and generation, it became widely adopted for chatbots, content generation, and general-purpose AI assistance.
2 years newer
GPT-3.5 Turbo
OpenAI
2023-03-21
GLM-4.6
Zhipu AI
2025-09-30
+
+
+
+
+
+
+
+
+
+
+
+
Pricing Comparison
Cost per million tokens (USD)
+
+
+
+
GLM-4.6
Input:$0.60
Output:$2.00
+
+
+
+
GPT-3.5 Turbo
Input:$0.50
Output:$1.50($0.60 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
+
+
+
+
GLM-4.6
Average Score:81.0%(+50.2%)
+
+
+
+
GPT-3.5 Turbo
Average Score:30.8%
+
+
+
+
Knowledge Cutoff
Training data recency comparison
GPT-3.5 Turbo
2021-09-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
GLM-4.6
2 providers
DeepInfra
Throughput: 85 tok/s
Latency: 0.7ms
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
+
+
+
+
GPT-3.5 Turbo
+
+
+
+
GLM-4.6
Avg Score:81.0%(+50.2%)
Providers:2
+
+
+
+
GPT-3.5 Turbo
Avg Score:30.8%
Providers:2