Jamba2 Mini: context, capabilities and where to run it

Prices from official vendor price lists · October 2026

AI21 Labs does not publish a token price for Jamba2 Mini, so cost depends on where it is hosted. Recorded here for reasoning.

Capabilities
Text & chatReasoningTool calling
Context window
256K tokens
Price / mo
API only

Jamba2 Mini is an AI model from AI21 Labs. The vendor does not publish a public per-token price, so the cost cells are left empty rather than guessed.

It holds 256K tokens in a single conversation. Capabilities recorded in this rating: text & chat, reasoning, tool calling, low latency, multilingual. Access is through the API rather than a consumer subscription.

API priceNot publishedper 1M tokens, in / out
Context256K tokenstokens per conversation
VendorAI21 Labsall models from this vendor
TierUnpricedno public rate card

Compared with alternatives

Good and poor fit

Good fit
  • Multi-step analysis, planning and code review, where the first plausible answer is often wrong.
  • High-volume routing, classification and autocomplete.
Poor fit
  • Long multi-step reasoning, where a larger model finishes in fewer attempts.
  • Anything requiring image input — this model does not accept it.

Related filters

Text & chat234 models for text generation and chat
Reasoning175 models that think before answering
Tool calling172 models that call your functions
Low latency76 small, fast models for volume
MultilingualAll 245 models work beyond English
AI21 Labs2 models from this vendor
All 245 modelsThe full rating with filters and prices

Frequently asked questions

How much does Jamba2 Mini cost?

AI21 Labs does not publish a public per-token rate for this model, so the price cells here are empty rather than estimated.

What is the context window of Jamba2 Mini?

256K tokens in a single conversation.

What can Jamba2 Mini do?

In this rating it is recorded with: text & chat, reasoning, tool calling, low latency, multilingual, proprietary API.

Is Jamba2 Mini a good choice?

It depends on the job. See the good-fit and poor-fit lists above, and compare against the neighbouring models before committing.

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