Jamba Large 1.7 is the latest model in the Jamba open family, offering improvements in grounding, instruction-following, and overall efficiency. Built on a hybrid SSM-Transformer architecture with a 256K context...
Model details →AI21: Jamba Large 1.7 vs inclusionAI: Ling-2.6-1T
inclusionAI: Ling-2.6-1T wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Ling-2.6-1T is an instant (instruct) model from inclusionAI and the company’s trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale. It uses a “fast...
Model details →Side-by-side comparison
| Capability | AI21: Jamba Large 1.7 | inclusionAI: Ling-2.6-1T | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 256K | 262K | 🏆 inclusionAI: Ling-2.6-1T |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $2.00 | $0.07 | 🏆 inclusionAI: Ling-2.6-1T |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $8.00 | $0.63 | 🏆 inclusionAI: Ling-2.6-1T |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is AI21: Jamba Large 1.7 better than inclusionAI: Ling-2.6-1T?
inclusionAI: Ling-2.6-1T wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between AI21: Jamba Large 1.7 and inclusionAI: Ling-2.6-1T?
Input: $2.00 vs $0.07 per 1M tokens. Output: $8.00 vs $0.63 per 1M tokens.
What context windows do AI21: Jamba Large 1.7 and inclusionAI: Ling-2.6-1T support?
AI21: Jamba Large 1.7 supports up to 256K tokens. inclusionAI: Ling-2.6-1T supports up to 262K tokens.
Do both AI21: Jamba Large 1.7 and inclusionAI: Ling-2.6-1T support tool calling?
AI21: Jamba Large 1.7: yes. inclusionAI: Ling-2.6-1T: yes.