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GLM-4.6 vs Qwen2.5 14B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 14B Instruct leads with 31.4% higher average benchmark score. GLM-4.6 supports multimodal inputs. GLM-4.6 is available on 2 providers. Overall, Qwen2.5 14B Instruct is the stronger choice for coding tasks.
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Zhipu AI
GLM-4.6 is a multimodal language model developed by Zhipu AI. It achieves strong performance with an average score of 61.2% across 7 benchmarks. It excels particularly in AIME 2025 (93.9%), LiveCodeBench v6 (82.8%), GPQA (81.0%). It supports a 197K token context window for handling large documents. The model is available through 2 API providers. 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 Zhipu AI's latest advancement in AI technology.
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Alibaba Cloud / Qwen Team
Qwen2.5 14B Instruct is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 70.0% across 16 benchmarks. It excels particularly in GSM8k (94.8%), HumanEval (83.5%), MBPP (82.0%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
1 year newer
Qwen2.5 14B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
GLM-4.6
Zhipu AI
2025-09-30
Performance Metrics
Context window and performance specifications
Average performance across 22 common benchmarks
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GLM-4.6
Average Score:19.5%
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Qwen2.5 14B Instruct
Average Score:50.9%(+31.4%)
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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Qwen2.5 14B Instruct
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GLM-4.6
Avg Score:19.5%
Providers:2
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Qwen2.5 14B Instruct
Avg Score:50.9%(+31.4%)
Providers:0