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Model infoModelsSnapshot: 15 Oct 2026

Aleph Alpha / Luminous

Luminous Base Sparse

Research Luminous Base variant pruned from 13B to 2.6B retained parameters for Graphcore IPU hardware.

restrictedClosed weightsText generation
Official documentation (opens in a new tab)Reviewed 14 Oct 2026
7 of 21 specification fields collected
Context windowNot collectedAwaiting source review
Maximum outputNot collectedAwaiting source review
Input billingNot collectedAleph Alpha / Graphcore research
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 input tokens
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
Not collected

Announcement dates and SDK selector suffixes do not establish exact checkpoint release dates.

Parameters
2,600,000,000Source for Parameters (opens in a new tab)

Retained non-zero parameters after approximately 80% pruning; dense parent has 13B.

Languages
Not collected
Context caching
Not collected

SDK caches tokenizers and model metadata locally; this does not establish prompt-cache support or discounted cached input.

Usage metering
Not collected

No current official model-specific rate verified. Historical third-party dollar estimates are not treated as provider prices.

Endpoint availability
Published research demonstration; no native API selector verified.Source for Endpoint availability (opens in a new tab)
Architecture
Point-sparse Luminous Base, retrained after pruning; retained weights use compressed sparse row storage.Source for Architecture (opens in a new tab)
Deployment options
Demonstrated on Graphcore IPU-POD16 Classic; no current self-service deployment or callable selector verified.Source for Deployment options (opens in a new tab)
Training hardware
Provider reports 20% of dense inference FLOPs, 44% memory use and 38% lower energy requirements.Source for Training hardware (opens in a new tab)

Reported relative demonstration measurements, not universal production guarantees.

Access & pricing

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

Aleph Alpha / Graphcore research

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

No native selector verified.

Access
Public research description; no downloadable original weights or callable API verified.
Regions
No model-specific current processing region verified

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

Data & enterprise terms

Current retention and training-use commitments not established for this historical model record.

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.

Aleph Alpha / Graphcore research

Not verified

No provider-documented prompt cache verified for this exact model.

How it works
Not collected

Local SDK tokenizer/context-size memoization is not provider prompt caching.

Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected

No cached-input rate verified.

Limits & data boundaries
Not collected

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

Caching reviewed 14 Oct 2026

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

Provider documents this Luminous model as a hosted commercial model or research demonstration. No original Luminous weight release was found in reviewed official model/repository listings. This is a qualified review finding; public SDK code and other open-weight Aleph Alpha families do not release these weights.

Classification evidence (opens in a new tab)

Lifecycle dates

Sparse model article published17 Oct 2022Source (opens in a new tab)

Sources reviewed