Comprehensive side-by-side LLM comparison
Llama 4 Scout leads with 16.7% higher average benchmark score. Llama 4 Scout offers 19.5M more tokens in context window than Jamba 1.5 Large. Llama 4 Scout is $9.62 cheaper per million tokens. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, Llama 4 Scout is the stronger choice for coding tasks.
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.
Meta
Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.
7 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
Llama 4 Scout
Meta
2025-04-05
Cost per million tokens (USD)
Jamba 1.5 Large
Llama 4 Scout
Context window and performance specifications
Average performance across 17 common benchmarks
Jamba 1.5 Large
Llama 4 Scout
Jamba 1.5 Large
2024-03-05
Available providers and their performance metrics
Jamba 1.5 Large
Bedrock
Llama 4 Scout
Jamba 1.5 Large
Llama 4 Scout
Jamba 1.5 Large
Llama 4 Scout
DeepInfra
Fireworks
Groq
Lambda
Novita
Together