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Model infoModelsSnapshot: 15 Oct 2026

Aleph Alpha / Luminous

Luminous Supreme

Luminous Supreme is a 70B-parameter multilingual Luminous model evaluated in Aleph Alpha’s 2023 report.

historicalClosed weightsText generation
Official documentation (opens in a new tab)Reviewed 14 Oct 2026
7 of 20 specification fields collected
Context windowNot collectedAwaiting source review
Maximum outputNot collectedAwaiting source review
Input billingNot collectedAleph Alpha API (historical documentation)
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.

Languages
English, German, French, Italian, SpanishSource for Languages (opens in a new tab)
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
Historically documented model or representation. Current account-specific availability not verified.Source for Endpoint availability (opens in a new tab)
Architecture
Decoder-only autoregressive transformer with rotary positional embeddings.Source for Architecture (opens in a new tab)
Published training data
Curated multilingual corpus; report gives approximately 400B tokens for Base and 588B for Supreme, without an exact Extended figure.Source for Published training data (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.

Aleph Alpha API (historical documentation)

Provider source (opens in a new tab)
API model ID
luminous-supreme

Documented selector; present availability and alias resolution not verified.

Access
Historically documented completion API/model selector. Current deployment and account entitlement require separate verification.
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 API (historical documentation)

luminous-supreme
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

arc_challenge (CR) (acc)

Aleph Alpha · provider-reported
44.2%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

arc_easy (CR) (acc)

Aleph Alpha · provider-reported
76.9%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

boolq (RC) (acc)

Aleph Alpha · provider-reported
74.3%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

copa (CR) (acc)

Aleph Alpha · provider-reported
90%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

hellaswag (CR) (acc)

Aleph Alpha · provider-reported
59.2%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

lambada (RC) (acc)

Aleph Alpha · provider-reported
74%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

multirc (RC) (acc)

Aleph Alpha · provider-reported
1.9%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

openbookqa (CR) (acc)

Aleph Alpha · provider-reported
33%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

piqa (CR) (acc)

Aleph Alpha · provider-reported
79.9%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

race (RC) (acc)

Aleph Alpha · provider-reported
40.8%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

rte (NLI) (acc)

Aleph Alpha · provider-reported
64.3%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

triviaqa (QA) (exact)

Aleph Alpha · provider-reported
37.7%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Exact-match generative accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

webqs (QA) (exact)

Aleph Alpha · provider-reported
7.8%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Exact-match generative accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

wic (CL) (acc)

Aleph Alpha · provider-reported
43.3%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

winogrande (CR) (acc)

Aleph Alpha · provider-reported
70%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

wsc (CR) (acc)

Aleph Alpha · provider-reported
57.7%

February 2023 report, 16-task core table, zero-shot text completion with EleutherAI lm-eval. Likelihood-based option accuracy. Higher is better. Published by provider; not an independent reproduction or comparison against current models.

Evaluation source (opens in a new tab)

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

Published benchmark report20 Feb 2023Source (opens in a new tab)

Sources reviewed