Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 18.7% higher average benchmark score. Jamba 1.5 Large offers 184.3K more tokens in context window than DeepSeek-V3.1. DeepSeek-V3.1 is $8.73 cheaper per million tokens. Overall, DeepSeek-V3.1 is the stronger choice for coding tasks.
DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek'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.
4 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
DeepSeek-V3.1
DeepSeek
2025-01-10
Cost per million tokens (USD)
DeepSeek-V3.1
Jamba 1.5 Large
Context window and performance specifications
Average performance across 22 common benchmarks
DeepSeek-V3.1
Jamba 1.5 Large
Jamba 1.5 Large
2024-03-05
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
Jamba 1.5 Large
DeepSeek-V3.1
Jamba 1.5 Large
DeepSeek-V3.1
Jamba 1.5 Large
Bedrock