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Embed V1 4B

Embed V1 4B is a cost-efficient model with standard context support, suited to semantic retrieval and enterprise search for enterprise teams.

Try Embed V1 4B with your team

Last reviewed: 2026-09-02

Embed V1 4B

Perplexity

Stable
Context Window
32,000
Input / 1M
$0.05
Output / 1M
$0.00

Watch Embed V1 4B in Remova

See how a team selects Embed V1 4B, passes policy checks, and routes the request safely through Remova.

Use Embed V1 4B Safely on Remova

Model demo

A 36-second overview showing how teams can select Embed V1 4B inside Remova, pass policy checks, apply it to real-world work, and use advanced AI with redaction, routing, budgets, and audit trails.

Video transcript

Embed V1 4B for enterprise AI. Remova routes model access, long-context analysis, and assistant workflows through governance controls. In the Remova interface, a user selects Embed V1 4B, passes sensitive data redaction, budget threshold, and role access checks, then runs the request safely. Teams can use Embed V1 4B for improve enterprise search, power semantic retrieval, deduplicate knowledge assets, route support requests, rank compliance evidence, measure content similarity. Use Embed V1 4B safely on Remova with redaction, routing, budgets, and audit trails built in. Sign up now.

What can you do with Embed V1 4B?

Practical ways teams can use Embed V1 4B inside governed AI workflows.

01

Improve enterprise search with Embed V1 4B

Rank documents, answers, and knowledge-base results so teams find the right information faster with Embed V1 4B.

02

Power semantic retrieval with Embed V1 4B

Match user questions to relevant policies, product docs, tickets, and internal references with Embed V1 4B.

03

Deduplicate knowledge assets with Embed V1 4B

Cluster related content, similar records, and overlapping documents for cleaner operations with Embed V1 4B.

04

Route support requests with Embed V1 4B

Classify incoming questions and connect them with the most relevant internal resources with Embed V1 4B.

05

Rank compliance evidence with Embed V1 4B

Surface the most relevant policies, logs, and documents during audits and reviews with Embed V1 4B.

06

Measure content similarity with Embed V1 4B

Compare records, tickets, snippets, and documents for matching or recommendation workflows with Embed V1 4B.

Why this model

Embed V1 4B is available in Remova as a standard context option with $0.05 per 1M tokens input pricing, $0.00 per 1M tokens output pricing, and text input to embeddings output support.

  • Embed V1 4B offers standard context capacity for enterprise prompts and documents.
  • Current Remova pricing band is cost-efficient: $0.05 per 1M tokens input and $0.00 per 1M tokens output.
  • Best-fit workloads include: Semantic retrieval, Enterprise search, Knowledge indexing.
  • Keep audit logs enabled for high-impact use cases.

At a glance

Model ID
perplexity/pplx-embed-v1-4b
Context Window
32,000 tokens
Modality
Text input to embeddings output
Input Modalities
Text
Output Modalities
Embeddings
Input Price
$0.05 per 1M tokens
Output Price
$0.00 per 1M tokens
Provider
Perplexity
Listing Date
2026-03-16

Strengths

  • Embed V1 4B is suited for semantic retrieval.
  • Supports standard context for multi-step prompts and larger working sets.
  • Pricing profile is cost-efficient, enabling predictable workload routing decisions.
  • Can be paired with policy guardrails for safer deployment at scale.

Tradeoffs

  • Operational drift can appear over time without recurring quality evaluations.
  • Standard context limits may require chunking or retrieval strategies for large documents.
  • Low-cost tiers can still underperform on high-consequence decisions without escalation paths.
  • Embedding and retrieval systems need benchmark sets to catch ranking drift and stale indexes.

Best for

  • Embed V1 4B for semantic retrieval, ranking, and enterprise search workflows.
  • Embed V1 4B for enterprise search across policies, product docs, and support knowledge bases.
  • Embed V1 4B for indexing internal knowledge assets into searchable vector workflows.
  • Embed V1 4B for surfacing compliance evidence and related records during audits.

Rollout checklist

  • Define where Embed V1 4B is default vs. fallback in your routing policy.
  • Enable role-based access and policy checks before opening access broadly.
  • Set spend guardrails by team and monitor weekly token consumption.
  • Start with approved teams, then expand in controlled waves.
  • Re-run quality and cost benchmarks monthly as newer releases appear.

Related models

Explore adjacent model profiles for routing and benchmarking decisions.

Free Resource

Where Should Your Team Start with AI?

Tell us your industry and team size. We'll tell you which AI use cases will save the most time with the least setup.

You get

A shortlist of AI use cases ranked by impact and effort for your situation.

Tuning notes

frequency_penalty

Tune repetition control for long responses in multi-step workflows.

max_tokens

Set completion limits to avoid unpredictable long-output spend.

presence_penalty

Use carefully when expanding idea diversity in exploration-heavy prompts.

temperature

Lower temperature for deterministic policy and compliance tasks.

Free Assessment

What Could Go Wrong?

5 questions about how your company uses AI today. We'll show you the risks most companies miss until it's too late.

You get

A risk breakdown with the 3 things you should fix first.

Book demo
Knowledge Hub

Embed V1 4B FAQs

Choose Embed V1 4B when the workload aligns with semantic retrieval, enterprise search, knowledge indexing and quality targets justify its pricing profile.
It depends on workload mix. Most organizations use routing policies so routine traffic stays on lower-cost tiers.
Validate quality on real internal prompts, token efficiency, latency, and policy compliance behavior.

Deploy This Model With Governance

Use policy controls, role-based access, and budget guardrails before enabling advanced model tiers at scale.

Try Embed V1 4B with your team