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Model infoModelsSnapshot: 15 Oct 2026

Preferred Networks / PLaMo

PLaMo 2.0-31B Instructed

Instruction-tuned 31B model previously hosted by SAKURA, distinct from the inference-optimized Prime packaging.

Language models (LLMs)
historicalClosed weightsText generation
Official documentation (opens in a new tab)Reviewed 14 Oct 2026
4 of 17 specification fields collected
Context windowNot collectedAwaiting source review
Maximum outputNot collectedAwaiting source review
Input billingNot collectedSAKURA AI Engine (retired deployment)
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
Input modalities
TextSource for Input modalities (opens in a new tab)
Output modalities
TextSource for Output modalities (opens in a new tab)
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
Parameters
31BSource for Parameters (opens in a new tab)
Architecture
Not collected
Languages
JapaneseSource for Languages (opens in a new tab)

Documented focus, not a complete language inventory.

Context caching
Not collected

No model-specific public prompt-cache contract or cached-token discount was verified. Internal inference caches do not establish a customer-facing cache feature.

Access & pricing

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

SAKURA AI Engine (retired deployment)

Provider source (opens in a new tab)
API model ID
plamo-2.0-31b
Access
SAKURA ended this deployment on October 12, 2026. No public weight release or current replacement selector for the same checkpoint was verified.
Regions
Deployment and service contract determine access and processing location.

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.

SAKURA AI Engine (retired deployment)

plamo-2.0-31b
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

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

Named provider model offered through commercial services, private licensing or provider research, with no matching public checkpoint verified. Closed-weight classification is inferred for this specific derivative, not its public base or other PLaMo releases.

Classification evidence (opens in a new tab)

Lifecycle dates

SAKURA deployment ends12 Oct 2026Source (opens in a new tab)

Sources reviewed