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Comprehensive side-by-side LLM comparison
Jamba 1.5 Large leads with 6.8% higher average benchmark score. Jamba 1.5 Large offers 315.4K more tokens in context window than GLM-4.6. GLM-4.6 is $7.40 cheaper per million tokens. GLM-4.6 supports multimodal inputs. Overall, Jamba 1.5 Large 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.
AI21 Labs
Jamba 1.5 Large is a language model developed by AI21 Labs. It achieves strong performance with an average score of 65.5% across 8 benchmarks. It excels particularly in ARC-C (93.0%), GSM8k (87.0%), MMLU (81.2%). It supports a 512K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents AI21 Labs's latest advancement in AI technology.
1 year newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
GLM-4.6
Zhipu AI
2025-09-30
Cost per million tokens (USD)
GLM-4.6
Jamba 1.5 Large
Context window and performance specifications
Average performance across 14 common benchmarks
GLM-4.6
Jamba 1.5 Large
Jamba 1.5 Large
2024-03-05
Available providers and their performance metrics
GLM-4.6
DeepInfra
ZeroEval
Jamba 1.5 Large
GLM-4.6
Jamba 1.5 Large
GLM-4.6
Jamba 1.5 Large
Bedrock