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GLM-4.5 vs Granite 3.3 8B Instruct
Comprehensive side-by-side LLM comparison
Granite 3.3 8B Instruct leads with 3.2% higher average benchmark score. Granite 3.3 8B Instruct supports multimodal inputs. GLM-4.5 is available on 3 providers. Both models have their strengths depending on your specific coding needs.
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Zhipu AI
GLM-4.5 is a language model developed by Zhipu AI. It achieves strong performance with an average score of 64.0% across 14 benchmarks. It excels particularly in MATH-500 (98.2%), AIME 2024 (91.0%), MMLU-Pro (84.6%). It supports a 262K token context window for handling large documents. The model is available through 3 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Zhipu AI's latest advancement in AI technology.
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IBM
Granite 3.3 8B Instruct is a multimodal language model developed by IBM. It achieves strong performance with an average score of 69.8% across 14 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents IBM's latest advancement in AI technology.
3 months newer
Granite 3.3 8B Instruct
IBM
2025-04-16
GLM-4.5
Zhipu AI
2025-07-28
Performance Metrics
Context window and performance specifications
Average performance across 26 common benchmarks
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GLM-4.5
Average Score:34.4%
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Granite 3.3 8B Instruct
Average Score:37.6%(+3.2%)
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Knowledge Cutoff
Training data recency comparison
Granite 3.3 8B Instruct
2024-04-01
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-4.5
3 providers
DeepInfra
Novita
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
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Granite 3.3 8B Instruct
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GLM-4.5
Avg Score:34.4%
Providers:3
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Granite 3.3 8B Instruct
Avg Score:37.6%(+3.2%)
Providers:0