Project AURIONAI Use-Cases Research & Innovation
LLM

Jamba 1.5 Mini

Jamba 1.5 Mini is an AI21 hybrid SSM-Transformer mixture-of-experts model with a 256K context window, 12B active of 52B total parameters.

AI21 Labs
Levelmodel
ClassLLM
Parameters52B
Context256,000
Released22 Aug 2024
Opennessopen weights restricted
Runs onmulti-GPU node, single datacentre GPU
Statusnot in the notes

Benchmark Results

vendor-reported
ARC-cknowledge and reasoning
vendor-reported
85.7
050100

Score in %. Higher is better.

Arena-Hardhuman preference arena
vendor-reported
46.1
02550

Score in score. Higher is better.

BFCLagents and tool use
vendor-reported
80.6
050100

Score in %. Higher is better.

GPQAknowledge and reasoning
vendor-reported
32.3
050100

Score in %. Higher is better.

GSM8Kmath
vendor-reported
75.8
050100

Score in %. Higher is better.

MMLUknowledge and reasoning
CoTvendor-reported
69.7
050100

Score in %. Higher is better.

MMLU-Proknowledge and reasoning
CoTvendor-reported
42.5
050100

Score in %. Higher is better.

Where this comes from
Every score names who ran it: vendor-reported, maintainer-run or independent. A rank is shown with the population it was ranked in (gap rule 3).

R&D Topics

Runtimes

Identity

Developer
AI21 Labs
Family
not in the notes
Released
22 Aug 2024 sourcesannouncement page
Weights published
19 Aug 2024
Record checked
11 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
hybrid Hybrid SSM-Transformer (joint attention and Mamba) with mixture of experts
Total parameters
52B sources
Active parameters
12B
Checkpoint parameters
–
Context length
256,000 tokens
Input
text
Output
text
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
open weights restricted
Licence
Jamba Open Model License Agreement sources
Access routes
API, cloud marketplace, open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
multi-GPU node, single datacentre GPU
Footprint
BF16 needs at least 2 x 80GB GPUs; ExpertsInt8 in vLLM fits a single 80GB GPU with prompts up to about 100K tokens; blog says up to 140K tokens on a single GPU
Runtimes
vLLM, SGLang, llama.cpp, Ollama
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
English, Spanish, French, Portuguese, Italian, Dutch, German, Arabic, Hebrew
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Lineage

The notes record no lineage for this model.

Industry Use Cases

No industry use case links this model.

Sources

  1. ai21.com/blog/announcing-jamba-model-family https://www.ai21.com/blog/announcing-jamba-model-family
  2. huggingface.co/ai21labs/AI21-Jamba-Mini-1.5 https://huggingface.co/ai21labs/AI21-Jamba-Mini-1.5
  3. huggingface.co/api/models/ai21labs/AI21-Jamba-1.5-Mini https://huggingface.co/api/models/ai21labs/AI21-Jamba-1.5-Mini

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Jamba 1.5 Mini", https://aurion.semai.id/models/ai21-labs-jamba-1-5-mini/, records of October 2026.