Comprehensive side-by-side LLM comparison
Llama 3.1 405B Instruct leads with 41.5% higher average benchmark score. Llama 3.1 405B Instruct offers 59.4K more tokens in context window than GLM-4.6. Llama 3.1 405B Instruct is $0.82 cheaper per million tokens. GLM-4.6 supports multimodal inputs. Llama 3.1 405B Instruct is available on 8 providers. Overall, Llama 3.1 405B Instruct is the stronger choice for coding tasks.
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.
Meta
Llama 3.1 405B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 79.2% across 18 benchmarks. It excels particularly in ARC-C (96.9%), GSM8k (96.8%), API-Bank (92.0%). It supports a 256K token context window for handling large documents. The model is available through 8 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.
1 year newer
Llama 3.1 405B Instruct
Meta
2024-07-23
GLM-4.6
Zhipu AI
2025-09-30
Cost per million tokens (USD)
GLM-4.6
Llama 3.1 405B Instruct
Context window and performance specifications
Average performance across 24 common benchmarks
GLM-4.6
Llama 3.1 405B Instruct
Available providers and their performance metrics
GLM-4.6
DeepInfra
ZeroEval
Llama 3.1 405B Instruct
GLM-4.6
Llama 3.1 405B Instruct
GLM-4.6
Llama 3.1 405B Instruct
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