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 window, it delivers more acc…
Model details →AI21: Jamba Large 1.7 vs omni-research/Tarsier2-Recap-7b
AI21: Jamba Large 1.7 wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
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Model details →Side-by-side comparison
| Capability | AI21: Jamba Large 1.7 | omni-research/Tarsier2-Recap-7b | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 256K | Unknown | 🏆 AI21: Jamba Large 1.7 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $2.00 | Custom | 🏆 AI21: Jamba Large 1.7 |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $8.00 | Custom | 🏆 AI21: Jamba Large 1.7 |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | — | 🏆 AI21: Jamba Large 1.7 |
| 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 omni-research/Tarsier2-Recap-7b?
AI21: Jamba Large 1.7 wins on 4 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 omni-research/Tarsier2-Recap-7b?
Input: $2.00 vs Custom per 1M tokens. Output: $8.00 vs Custom per 1M tokens.
What context windows do AI21: Jamba Large 1.7 and omni-research/Tarsier2-Recap-7b support?
AI21: Jamba Large 1.7 supports up to 256K tokens. omni-research/Tarsier2-Recap-7b supports up to Unknown tokens.
Do both AI21: Jamba Large 1.7 and omni-research/Tarsier2-Recap-7b support tool calling?
AI21: Jamba Large 1.7: yes. omni-research/Tarsier2-Recap-7b: not advertised.