Skip to content
Model infoModelsSnapshot: 15 Oct 2026

Meta / Llama 4

Llama 4 Behemoth · unreleased teacher

Meta’s large multimodal mixture-of-experts teacher used during development of the released Llama 4 models.

restrictedClosed weightsGeneral purposeCoding
Official documentation (opens in a new tab)Reviewed 13 Oct 2026
8 of 18 specification fields collected
Context windowNot collectedAwaiting source review
Maximum outputNot collectedAwaiting source review
Input billingNot collectedMeta · research reference
Output billingNot collectedNo inferred price

Specifications

Provider-documented facts. “Not collected” means we have not verified that field yet, not that the feature is unsupported.

Context / input limit
Not collected
Maximum output
Not collected
Reasoning
Not collected
Tool calling
Not collected
Structured output
Not collected
Streaming
Not collected
Batch processing
Not collected
Fine-tuning
Not collected
Knowledge cutoff
Not collected
Release date
2025-04-05Source for Release date (opens in a new tab)

Research disclosure date, not general API or weight availability.

Parameters
288B active parameters; nearly 2T totalSource for Parameters (opens in a new tab)
Architecture
Multimodal mixture-of-experts teacher with 16 expertsSource for Architecture (opens in a new tab)
Languages
Multilingual; exact supported language list not established for this unreleased teacherSource for Languages (opens in a new tab)
Context caching
Not collected

No model-specific inference service or discounted prompt-cache contract is established for these research weights.

distillationRole
Teacher for Llama 4 Maverick co-distillation during pretrainingSource for distillationRole (opens in a new tab)
postTraining
Lightweight supervised fine-tuning followed by large-scale reinforcement learningSource for postTraining (opens in a new tab)

Access & pricing

Prices belong to an endpoint and billing tier. A provider listing does not guarantee access for every account or region.

Meta · research reference

Provider source (opens in a new tab)
API model ID
Not collected

Descriptive catalog identity, not a verified selectable API ID.

Access
Announced internal teacher. No public inference selector or original weight download verified in the reviewed official distribution.
Regions
Research deployment only; public availability and residency are not established

Endpoint pricing has not been collected. Check the provider for applicable rates.

Data & enterprise terms

The cited research release does not supply a current production processing/retention agreement. Research access or an expired demonstration is not a production API entitlement.

Read the service policy (opens in a new tab)

Caching

Caching can reuse earlier input processing. Availability, lifetime and billing depend on the endpoint. A cache hit still generates a new response.

01 / INITIAL INPUTProcess & retain

The system processes eligible input and retains reusable state.

02 / LATER REQUESTCheck available state

Reuse depends on matching input, session state and the cache policy.

03 / CACHE HITReuse & generate

Reusing state can reduce repeated work. Any charges follow the billing rules below.

Meta · research reference

Not verified

No published service cache policy for this research record.

How it works
Not collected

No published service cache policy for this research record.

Minimum reusable input
Not collected

No published service cache policy for this research record.

Lifetime & refresh
Not collected

No published service cache policy for this research record.

How to enable it
Not collected

No published service cache policy for this research record.

Usage fields
Not collected

No published service cache policy for this research record.

Billing rules
Not collected

No published service cache policy for this research record.

Limits & data boundaries
Not collected

No published service cache policy for this research record.

No verified cache rate for this endpoint. An empty rate is not a zero charge.

What the measurements say

No benchmark observations have been added for this model. We do not turn a vendor description into a performance score.

Latency and throughput depend on the host, request size, reasoning settings and load. There is no measured speed or global usage figure in this record.

The record behind the model

Why it is included

The official announcement explicitly distinguishes unreleased Behemoth from downloadable Scout and Maverick. The reviewed Llama 4 model card and Meta’s official distribution inventory list released siblings, not Behemoth weights. This record concerns the unpublished teacher as reviewed, not a permanently proprietary license claim about all Llama models.

Classification evidence (opens in a new tab)

Lifecycle dates

Teacher model previewed; weights not released5 Apr 2025Source (opens in a new tab)

Sources reviewed