Governed Profile

Mistral: Mistral Embed 2312

Mistral: Mistral Embed 2312 is a cost-efficient model with standard context support, suited to semantic retrieval and enterprise search for enterprise teams.

Try Mistral: Mistral Embed 2312 with your team

Last reviewed: 2026-06-09

Mistral AI

Stable

Context Window

8,192

Input / 1M

$0.15

Output / 1M

$0.00

What can you do with Mistral: Mistral Embed 2312?

Practical ways teams can use Mistral: Mistral Embed 2312 inside governed AI workflows.

Improve enterprise search with Mistral: Mistral Embed 2312

Rank documents, answers, and knowledge-base results so teams find the right information faster with Mistral: Mistral Embed 2312.

Power semantic retrieval with Mistral: Mistral Embed 2312

Match user questions to relevant policies, product docs, tickets, and internal references with Mistral: Mistral Embed 2312.

Deduplicate knowledge assets with Mistral: Mistral Embed 2312

Cluster related content, similar records, and overlapping documents for cleaner operations with Mistral: Mistral Embed 2312.

Route support requests with Mistral: Mistral Embed 2312

Classify incoming questions and connect them with the most relevant internal resources with Mistral: Mistral Embed 2312.

Rank compliance evidence with Mistral: Mistral Embed 2312

Surface the most relevant policies, logs, and documents during audits and reviews with Mistral: Mistral Embed 2312.

Measure content similarity with Mistral: Mistral Embed 2312

Compare records, tickets, snippets, and documents for matching or recommendation workflows with Mistral: Mistral Embed 2312.

Why this model

Mistral: Mistral Embed 2312 is available in Remova as a standard context option with $0.15 per 1M tokens input pricing, $0.00 per 1M tokens output pricing, and text->embeddings modality support for enterprise AI operations.

Mistral: Mistral Embed 2312 offers standard context capacity for enterprise prompts and documents.
Current Remova pricing band is cost-efficient: $0.15 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: mistralai/mistral-embed-2312
Context Window: 8,192 tokens
Modality: text->embeddings
Input Modalities: text
Output Modalities: embeddings
Input Price: $0.15 per 1M tokens
Output Price: $0.00 per 1M tokens
Provider: Mistral AI
Listing Date: 2025-10-31

Strengths

Mistral: Mistral Embed 2312 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

Prompt standards are still needed to keep output quality consistent across teams.
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

Mistral: Mistral Embed 2312 for semantic retrieval, ranking, and enterprise search workflows.
Mistral: Mistral Embed 2312 for enterprise search across policies, product docs, and support knowledge bases.
Mistral: Mistral Embed 2312 for indexing internal knowledge assets into searchable vector workflows.
Mistral: Mistral Embed 2312 for surfacing compliance evidence and related records during audits.

Rollout checklist

Define where Mistral: Mistral Embed 2312 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.

response_format

Prefer structured output where responses feed internal systems.

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.

Knowledge Hub

Mistral: Mistral Embed 2312 FAQs

Choose Mistral: Mistral Embed 2312 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 Mistral: Mistral Embed 2312 with your team