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Is there an AI for this?

Model

Jamba2 Mini

Recorded as suitable for chat, rag, long context.

Source
Model registry API
Verified
19 Sep 2026
Confidence
High

01What this is

Author
AI21 Labs
Family
Jamba 2
Task
text-generation
Hugging Face
ai21labs/AI21-Jamba2-Mini
OpenRouter
not listed
Also known as
Jamba2 Mini, jamba2-mini, ai21 jamba mini

02Registry facts

19 Sep 2026
LicenceFACT

apache-2.0

FreshRetrieved 19 Sep 2026
ParametersFACT

51.6B

FreshRetrieved 19 Sep 2026
Context lengthFACT

not returned by the registry

Evidence not verified
Downloads (30 days)FACT

629

FreshRetrieved 19 Sep 2026
LikesFACT

57

FreshRetrieved 19 Sep 2026
GatedFACT

no

FreshRetrieved 19 Sep 2026

Model

downloadsFACT

629

Verification may be outdatedRetrieved 19 Sep 2026
gatedFACT

false

Verification may be outdatedRetrieved 19 Sep 2026
likesFACT

57

Verification may be outdatedRetrieved 19 Sep 2026
model licenseFACT

apache-2.0

Verification may be outdatedRetrieved 19 Sep 2026
parameter countFACT

51570323328

Verification may be outdatedRetrieved 19 Sep 2026

Other

available on platform · awsFACT

aws

Evidence not verified — the quoted phrase was not found in the fetched document.

Evidence not verified
last modifiedFACT

2026-02-16T14:16:19.000Z

Verification may be outdatedRetrieved 19 Sep 2026
libraryFACT

transformers

AgeingRetrieved 19 Sep 2026

03VRAM by quantisation

ASSESSMENT

Peak VRAM for serving this model, computed by lib/deployment/hardware.ts from weights + KV cache + 15% runtime overhead. Inputs: 51.6B parameters, 8,192 tokens of context (assumed — none fetched yet), 4 concurrent requests (assumed).

Decimal GB (10⁹ bytes), matching how GPU memory is advertised.
QuantisationWeightsTotal
bf16bf16 is two bytes per weight, the same arithmetic as fp16.103.14 GB130.96 GB
int851.57 GB71.65 GB
int425.79 GB42 GB

What this estimate assumes

  • Weights: 51.6B parameters × 2 bytes per parameter (fp16) = 103.14 GB.
  • No model configuration was supplied, so the KV cache uses the size heuristic for this band: 0.328 MB per token, from Qwen2.5-72B-Instruct (80 × 8 × 128).
  • KV cache: 0.328 MB per token × 8,192 tokens of context × 4 concurrent requests = 10.74 GB, sized for every user holding a full context at once.
  • Overhead: 15% of weights plus KV cache for the runtime, activations and memory fragmentation = 17.08 GB.
  • GB means 10⁹ bytes, matching how GPU memory is advertised.
  • KV cache held at fp16 (2 bytes per element); quantising weights does not by itself quantise the cache.
  • Peak figure, not average: prefix caching and paged attention usually keep real usage lower, while speculative decoding, CUDA graphs and a second resident model push it higher.
  • "Concurrent" counts requests generated at the same instant, not people: 4 simultaneous requests is the worst case this estimate is built on — measure yours before buying.

04Hardware profiles

No hardware profile was sized for this answer.


05Hosted providers

No hosted provider has been fetched for this model. OpenRouter’s catalogue is read when our refresh next runs; until then this is empty rather than assumed.


06Deployment stacks

0 using it

No published deployment stack names this model yet.


07Evidence

7 verified
  1. 01–07
    Tier 4official repository / model cardHugging Face Hub

    Hugging Face model card data — ai21labs/AI21-Jamba2-Mini

    https://huggingface.co/api/models/ai21labs/AI21-Jamba2-Mini

    Verification may be outdatedRetrieved 19 Sep 2026sha256:1069395a2194

    7 records · · · · · ·

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From the field

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