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Model infoModelsSnapshot: 15 Oct 2026

Contextual AI / Contextual AI

Contextual Reranker v1 Instruct

Instruction-following reranker that orders documents by query relevance and then by optional ranking preferences.

availableClosed weightsReranking
Official documentation (opens in a new tab)Reviewed 15 Oct 2026
4 of 16 specification fields collected
Context windowNot collectedAwaiting source review
Maximum outputNot collectedAwaiting source review
Input billingNot collectedContextual AI API
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

Exact version-specific contract not established. Unknown does not mean unsupported.

Maximum input tokens
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Maximum output
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Parameters
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Release date
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Knowledge cutoff
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Reasoning
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Tool calling
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Structured output
SupportedSource for Structured output (opens in a new tab)

Typed ranking result, not arbitrary generated JSON Schema.

Streaming
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Batch processing
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Fine-tuning
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Context caching
Not collected

Exact version-specific contract not established. Unknown does not mean unsupported.

Output modalities
Relevance scores, Document indicesSource for Output modalities (opens in a new tab)
Generation controls
query, documents and model required; instruction, top_n and metadata optional. Metadata list must match document count. Scores normalized to 0–1 and truncated to eight decimal places.Source for Generation controls (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.

API model ID
ctxl-rerank-v1-instruct
Access
Versioned reranking API; present-day model selector documented, inference availability not tested.
Regions
Public API serving region not established. Enterprise VPC deployment is offered under separate terms.
API endpoint
POST https://api.contextual.ai/v1/rerankSource for API endpoint (opens in a new tab)

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

Data & enterprise terms

Service terms permit processing Customer Data to deliver and improve the service during and after the term. This is not a universal no-training or zero-retention commitment. Personal-data retention is purpose-dependent; enterprise/VPC agreements and task-result retention require separate review.

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.

Contextual AI API

ctxl-rerank-v1-instruct
Not verified

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

How it works
Not collected

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

Minimum reusable input
Not collected

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

Lifetime & refresh
Not collected

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

How to enable it
Not collected

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

Usage fields
Not collected

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

Billing rules
Not collected

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

Limits & data boundaries
Not collected

No exact model-specific prompt-cache mechanism, eligibility or discounted tariff established.

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

Caching reviewed 15 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-developed specialized model supplied through versioned service selectors under retained provider rights and extraction restrictions. Reviewed official public releases distinguish LMUnit and Reranker v2 weights; they do not release this named GLM or v1 reranker checkpoint. Underlying open base models do not establish publication of the specialized weights.

Classification evidence (opens in a new tab)

Lifecycle dates

Original instruction-following reranker publicly launched11 Mar 2025Source (opens in a new tab)

Sources reviewed