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 DeepSeek: R1 0528
DeepSeek: R1 0528 wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.…
Model details →Side-by-side comparison
| Capability | AI21: Jamba Large 1.7 | DeepSeek: R1 0528 | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 256K | 164K | 🏆 AI21: Jamba Large 1.7 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $2.00 | $0.45 | 🏆 DeepSeek: R1 0528 |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $8.00 | $2.15 | 🏆 DeepSeek: R1 0528 |
| 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. | — | Yes | 🏆 DeepSeek: R1 0528 |
Frequently asked questions
Is AI21: Jamba Large 1.7 better than DeepSeek: R1 0528?
DeepSeek: R1 0528 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 DeepSeek: R1 0528?
Input: $2.00 vs $0.45 per 1M tokens. Output: $8.00 vs $2.15 per 1M tokens.
What context windows do AI21: Jamba Large 1.7 and DeepSeek: R1 0528 support?
AI21: Jamba Large 1.7 supports up to 256K tokens. DeepSeek: R1 0528 supports up to 164K tokens.
Do both AI21: Jamba Large 1.7 and DeepSeek: R1 0528 support tool calling?
AI21: Jamba Large 1.7: yes. DeepSeek: R1 0528: yes.