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 Ox Alpha
Ox Alpha wins on 5 of 6 axes — pricing and capability skew in its favour for most workloads.
Ox Alpha is a reasoning model designed for coding, sustained agentic work, and production workloads. It is suited for long-horizon software engineering, complex reasoning, and workflows that combine text with...
Model details →Side-by-side comparison
| Capability | AI21: Jamba Large 1.7 | Ox Alpha | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 256K | 1.0M | 🏆 Ox Alpha |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $2.00 | $0.00 | 🏆 Ox Alpha |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $8.00 | $0.00 | 🏆 Ox Alpha |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | Yes | 🏆 Ox Alpha |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | Yes | 🏆 Ox Alpha |
Frequently asked questions
Is AI21: Jamba Large 1.7 better than Ox Alpha?
Ox Alpha wins on 5 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 Ox Alpha?
Input: $2.00 vs $0.00 per 1M tokens. Output: $8.00 vs $0.00 per 1M tokens.
What context windows do AI21: Jamba Large 1.7 and Ox Alpha support?
AI21: Jamba Large 1.7 supports up to 256K tokens. Ox Alpha supports up to 1.0M tokens.
Do both AI21: Jamba Large 1.7 and Ox Alpha support tool calling?
AI21: Jamba Large 1.7: yes. Ox Alpha: yes.