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Model infoModelsSnapshot: 15 Oct 2026

ELYZA / ELYZA LLM

Llama-3-ELYZA-JP-70B

Japanese instruction model derived from Meta-Llama-3-70B-Instruct; the smaller 8B sibling was released publicly.

historicalClosed weightsText generation
Official documentation (opens in a new tab)Reviewed 14 Oct 2026
6 of 19 specification fields collected
Context windowNot collectedAwaiting source review
Maximum outputNot collectedAwaiting source review
Input billingNot collectedELYZA enterprise (earlier generation)
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
Architecture
Not collected
Languages
JapaneseSource for Languages (opens in a new tab)

Documented focus, not an exhaustive supported-language list.

Context caching
Not collected

No public prompt-caching contract, lifetime or cached-input rate verified. Speculative decoding is not a published cache discount.

Published price
Not collected

No numeric production price verified for this exact model. Historical free demos do not establish free production inference.

Base model
Meta-Llama-3-70B-InstructSource for Base model (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.

ELYZA enterprise (earlier generation)

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

Published model label is not a verified API request selector.

Access
Announced for enterprise API and joint-development projects; current access to this exact revision requires confirmation.
Regions
Deployment-specific; no universal processing-region guarantee verified.

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

Data & enterprise terms

Retention, training use, regional processing and enterprise terms have not been summarized for this endpoint.

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.

ELYZA enterprise (earlier generation)

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

Japanese MT-Bench

ELYZA · vendor-reported
9.08score / 10

September 2024 provider presentation, slide 16. Earlier 70B dialogue/task scores are reused from its launch; not an independent evaluation or a universal model ranking.

Evaluation source (opens in a new tab)

ELYZA Tasks 100

ELYZA · vendor-reported
4.07score / 5

September 2024 provider presentation, slide 16. Earlier 70B dialogue/task scores are reused from its launch; not an independent evaluation or a universal model ranking.

Evaluation source (opens in a new tab)

Nejumi-v3 GLP average

ELYZA · vendor-reported
0.6693aggregate score

September 2024 provider presentation, slide 16. Earlier 70B dialogue/task scores are reused from its launch; not an independent evaluation or a universal model ranking.

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

ELYZA explicitly distinguishes the generally published 8B weights from the 70B model offered through a demo, enterprise APIs and joint development. No matching public 70B checkpoint was verified; the open upstream model does not establish public weights for this derivative.

Classification evidence (opens in a new tab)

Lifecycle dates

Model and demo announced26 Jun 2024Source (opens in a new tab)
Demo replaced by Llama 3.1 generation25 Oct 2024Source (opens in a new tab)

Sources reviewed