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GPT-3.5 Turbo (batch)

GPT-3.5 Turbo (batch) is a balanced model with standard context support, suited to model training and dataset workflows for enterprise teams.

Try GPT-3.5 Turbo (batch) with your team

Last reviewed: 2026-09-02

GPT-3.5 Turbo (batch)

OpenAI

Stable
Context Window
16,385
Input / 1M
$0.38
Output / 1M
$1.13

What can you do with GPT-3.5 Turbo (batch)?

Practical ways teams can use GPT-3.5 Turbo (batch) inside governed AI workflows.

01

Train LoRA adapters with GPT-3.5 Turbo (batch)

Create style, product, person, or subject adapters from approved training datasets with GPT-3.5 Turbo (batch).

02

Prepare training data with GPT-3.5 Turbo (batch)

Package images, captions, examples, and labels for repeatable model-training runs with GPT-3.5 Turbo (batch).

03

Validate training outputs with GPT-3.5 Turbo (batch)

Review sample generations, quality drift, and unsafe memorization before production use with GPT-3.5 Turbo (batch).

04

Govern dataset access with GPT-3.5 Turbo (batch)

Restrict sensitive training data with access controls, retention rules, and audit logs with GPT-3.5 Turbo (batch).

05

Manage model variants with GPT-3.5 Turbo (batch)

Track trained adapters, versions, prompts, and approval status across creative workflows with GPT-3.5 Turbo (batch).

06

Estimate training cost with GPT-3.5 Turbo (batch)

Compare dataset size, run count, and model usage before scaling training jobs with GPT-3.5 Turbo (batch).

Why this model

GPT-3.5 Turbo (batch) is available in Remova as a standard context option with $0.38 per 1M tokens input pricing, $1.13 per 1M tokens output pricing, and text input to text output support.

  • GPT-3.5 Turbo (batch) offers standard context capacity for enterprise prompts and documents.
  • Current Remova pricing band is balanced: $0.38 per 1M tokens input and $1.13 per 1M tokens output.
  • Best-fit workloads include: Model training, Dataset workflows, Style adaptation.
  • Use policy checks and output review on sensitive workflows.

At a glance

Model ID
openai/gpt-3.5-turbo:batch
Context Window
16,385 tokens
Modality
Text input to text output
Input Modalities
Text
Output Modalities
Text
Input Price
$0.38 per 1M tokens
Output Price
$1.13 per 1M tokens
Provider
OpenAI
Listing Date
2023-05-28

Strengths

  • GPT-3.5 Turbo (batch) is suited for model training.
  • Supports standard context for multi-step prompts and larger working sets.
  • Pricing profile is balanced, enabling predictable workload routing decisions.
  • Can be paired with policy guardrails for safer deployment at scale.

Tradeoffs

  • Governance controls are still required for regulated or sensitive workflows.
  • Standard context limits may require chunking or retrieval strategies for large documents.
  • Balanced-price tiers still need policy-based routing to protect monthly budgets.
  • Model training workflows need dataset consent, version control, and output review before reuse.

Best for

  • GPT-3.5 Turbo (batch) for training governed model variants from approved datasets.
  • GPT-3.5 Turbo (batch) for preparing, reviewing, and controlling training datasets.
  • GPT-3.5 Turbo (batch) for style, subject, or brand adaptation with versioned approvals.
  • GPT-3.5 Turbo (batch) for validating trained outputs before production reuse.

Rollout checklist

  • Define where GPT-3.5 Turbo (batch) 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.
  • Watch quality and spend weekly during early deployment.
  • Re-run quality and cost benchmarks monthly as newer releases appear.

Related models

Explore adjacent model profiles for routing and benchmarking decisions.

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Tuning notes

frequency_penalty

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

logit_bias

Use this parameter only with tested defaults in production workflows.

logprobs

Use this parameter only with tested defaults in production workflows.

max_tokens

Set completion limits to avoid unpredictable long-output spend.

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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.

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GPT-3.5 Turbo (batch) FAQs

Choose GPT-3.5 Turbo (batch) when the workload aligns with model training, dataset workflows, style adaptation 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 GPT-3.5 Turbo (batch) with your team