Jamba Large 1.7

Pricing — 1 offering(s)

Showing the active price and any recorded history. Full pricing history is available via the paid API — see API docs.

Capability profile

Operator guidance

Choose Jamba Large 1.7 when long-context grounding accuracy and the ability to self-host are the priorities, and mid-tier pricing is acceptable. For the same architecture at a fraction of the cost with lower ceiling, use Jamba Mini 2. For frontier reasoning or coding, a general flagship (Claude, GPT-5.x, Gemini) will outperform it — Jamba's differentiation is the efficient long context and the open-weights option, not raw capability.

Use cases

• Grounded question answering and summarisation over long enterprise documents (contracts, filings, knowledge bases) where citations-to-context accuracy matters
• Deployments that need open weights they can host in their own VPC/on-prem for data-control reasons
• Long-context RAG where the 256K window plus tuned grounding reduces retrieval-chunking complexity

Limitations

• Not a frontier reasoning or coding model — mid-tier general capability
• Hybrid SSM-Transformer tooling/fine-tuning ecosystem is smaller than for standard Transformers
• AI21's own pricing page lists only a generic 'Jamba Large' rate; the versioned mapping (jamba-large -> jamba-large-1.7-2025-07) is from AI21's docs (see registry entry)
• Capability ratings are qualitative from AI21's materials and the HF model card; no independent leaderboard entry consulted for this doc

Citations

• AI21-Jamba-Large-1.7 model card (Hugging Face)
• Jamba foundation models (AI21 docs)
• Jamba — AI21 Labs (product page)
• AI21 pricing