LLM Reference

Jamba Large 1.7

Released
2026-02-01
Last refreshed
2026-05-22
Status
Researched 105d ago
Open sourceCommercial use: permittedRAGAgentsLong contextClassificationJSON / Tool use

Jamba Large 1.7 is worth evaluating for rag, agents, and long context when its provider route and context window match the workload.

Use it for

  • Teams evaluating rag, agents, and long context
  • Workloads that can use a 256k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Vision or document-understanding workloads
Specifications
Family
Jamba 1.7
Released
2026-02-01
Context
256k
Parameters
398B (94B active)
Architecture
Decoder Only
Knowledge cutoff
2024-08
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Weights
Available
Code
Unknown
Training
Pretrained
Created by

Developing AI for natural language understanding.

Tel Aviv, Israel
Founded 2017
Website
Pricing
Output / 1M
$8.00
Input / 1M
$2.00

Cheapest of 1 route · AI21 Studio

About

Jamba Large 1.7 is AI21 Labs' latest hybrid Mamba-Transformer model offering improvements in grounding, instruction following, and structured output generation at 256K context.

Top use-case fit: coding, agents, and build tasks

RAG

Included by capability and metadata signals in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
AI21 Studio$2.00$8.00
Serverless

Capabilities

JSON / Tool useStructured Outputs

Benchmark peer barsfor Classification

Benchmark scores(2)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
Google-Proof Q&A39.0GPQA Diamond (accuracy)Observed 2026-06-07Source
MMLU PRO57.7Widely reported third-party evaluation (accuracy)Observed 2026-06-07Source

Migration checks

No linked migration route is available for this model yet.