AI21 Labs: Jamba Large 1.7

Public pricingIntelligence 79/100Large memory도구 활용

AI21: Jamba Large 1.7은 일반 대화, 분석, 운영 환경에 맞춘 텍스트 모델입니다. 낮은 지연과 효율적 추론, 256K tokens의 컨텍스트, 균형형 비용 특성을 결합해 general chat, analysis, and production workloads에서 안정적인 작업을 돕습니다. 특히 지연, 비용, 처리량가 중요한 경우에 잘 맞으며, 안정적인 출력, 유연한 배포, 확장성을 중시하는 팀에 실용적입니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다.

Input

$2.00/1M

Output

$8.00/1M

Cached

$0.20/1M

Batch

$1.00/1M

Calculate your Jamba Large 1.7 bill.

Set your workload — see cost at your exact volume.

What would Jamba Large 1.7 cost you?

Adjust the workload to see your monthly bill.

Conversations per month50,000

1,00010,00050,000250,0001M10M

Input length

Output length

Repeated questions?

Replies can wait a few hours (batch discount)

Technical specifications

Jamba Large 1.7 at a glance.

Memory

256,000

tokens

Max reply

4,096

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

—

Released

Mar 2025

Training cutoff

Oct 2024

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

aa_intelligence_index
11

What it can do

Capabilities & limits.

Understands images
Deep step-by-step thinking
Uses tools / calls functions
Strict JSON output
Streams replies
Fine-tunable on your data

When to pick Jamba Large 1.7

Agentic workflows that call tools or APIs.
Long documents, full codebases, or extensive chat histories.

When to look elsewhere

Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Jamba Large 1.7 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Jamba Large 1.7 costs roughly $470 per month. Input is $2.00 /1M tokens and output is $8.00 /1M tokens.

Jamba Large 1.7 has a 256,000-token context window (large memory — an entire book or large codebase). That means you can fit about 48,000 words of input and history in a single call.

Beyond text generation, Jamba Large 1.7 supports calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.

Jamba Large 1.7 was released in March 2025, with training data cut off around October 2024.

Models in a similar class include Gemini 3.1 Pro Preview, Gemini 3.1 Pro Preview Custom Tools, GPT-4.1. The "Similar models" section below this FAQ links into each.

Still unsure?

Compare Jamba Large 1.7 against 100+ other models.

Open the full wizard — pick a use case, set your usage, and see side-by-side monthly costs in under a minute.

Open the comparison wizard

About

Insights

Streamline

Integration

Solutions

Healthcare AI

Use Cases

Industries