Usage-based pricing

Pricing based on actual usage.

No required monthly platform subscription, LLMLab charges for tokens and system activity that are actually used.

Costs follow workflow execution, model usage, codebase parsing, retrieval, storage, hosted surfaces, and optional GPU activity. LLMLab's own support-agent setup used less than $0.10 in platform usage.

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No required Monthly fee

Start building before another platform subscription becomes the project.

Usage signal Spend follows work

Execution and model activity rise only when the system is active.

01 Use the platform

Build workflows, assistants, support agents, and knowledge systems.

02 Run workflows

Pay for execution, model activity, parsing, retrieval, and storage.

03 Scale with demand

Costs rise with real customer questions and system activity.

04 Control spend

Use lower-cost paths, answer memory, and budget guardrails.

No mandatory monthly fee

$5 free credit

Start without a required platform subscription. No setup, no credit card, and free usage credit for early testing.

Secure Payments LLMLab uses Stripe to manage secure payments, subscriptions, invoices, and usage credits.

Adaptive model spend Use lower-cost paths by default and escalate only when a model asks or validation fails

Answer memory Saved answers can resolve known questions before a workflow spends tokens on a fresh response.

Budget controls Monthly caps and usage visibility help keep workflow spend predictable

Current rate card* 2026-05-18

USD pricing Usage-based No monthly minimum

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Service	Price	Billing unit	Notes
Platform activity
Workflow run	`$0.003`	per run	Structured workflow execution overhead
Preset generation	`$0.001`	per preset	Template and preset generation overhead
Codebase parsing	`$0.01`	per 100K lines parsed	Source parsing for codebase ingestion
Hosted API tokens
`openai:gpt-5.4`	`$4.225` input / `$25.35` output	per 1M tokens	OpenAI flagship hosted path†
`openai:gpt-5.4-mini`	`$1.2675` input / `$7.605` output	per 1M tokens	Lower-cost OpenAI hosted path†
`anthropic:claude-sonnet-4-0`	`$5.07` input / `$25.35` output	per 1M tokens	Anthropic Sonnet hosted path†
`anthropic:claude-opus-4-1`	`$25.35` input / `$126.75` output	per 1M tokens	Anthropic highest-cost hosted path†
`google:gemini-2.5-pro`	`$4.225` input / `$25.35` output	per 1M tokens	Google hosted pro path†
`google:gemini-2.5-flash`	`$0.507` input / `$4.225` output	per 1M tokens	Faster lower-cost Google hosted path†
`google:gemini-2.5-flash-lite`	`$0.169` input / `$0.676` output	per 1M tokens	Lowest-cost Google flash hosted path†
`deepseek:deepseek-chat`	`$0.4563` input / `$1.859` output	per 1M tokens	DeepSeek chat hosted path†
`deepseek:deepseek-reasoner`	`$0.9295` input / `$3.7011` output	per 1M tokens	DeepSeek reasoning hosted path†
`xai:grok-4`	`$5.07` input / `$25.35` output	per 1M tokens	xAI Grok hosted path†
`mistral:mistral-medium-2508`	`$0.676` input / `$3.38` output	per 1M tokens	Mistral medium hosted path†
`mistral:mistral-small-2603`	`$0.2535` input / `$1.014` output	per 1M tokens	Mistral small hosted path†
Embeddings and reranking†
`sentence-transformers/all-minilm-l6-v2`	`$1.00`	per 1M tokens	Hosted dense embedding model
`intfloat/multilingual-e5-small`	`$1.00`	per 1M tokens	Hosted multilingual embedding model
`qdrant/bm25`	`$0.40`	per 1M tokens	Hosted sparse lexical embedding
`voyage:rerank-2.5` / `voyage:voyage-rerank-2.5`	`$0.10`	per 1K documents	Hosted reranker usage
GPU compute‡
Budget GPU tier	`$0.60`	per GPU-hour	RTX 3070 Ti / RTX 3080(Ti) / T4
Mid GPU tier	`$1.20`	per GPU-hour	RTX 3090(Ti) / L4 / A10
High GPU tier	`$4.00`	per GPU-hour	RTX 4090 / A100 40GB / A40 / L40
Ultra GPU tier	`$10.00`	per GPU-hour	A100 80GB / H100 / H200 class
Storage
Vector storage	`$0.60`	per GiB-month	Persistent vector index footprint
Hosted model storage	`$0.60`	per GiB-month	Persistent hosted model storage

* Amounts are rounded up to the next whole $0.01 increment across charge groups.

† User-provided tokens are not billed by LLMLab. Provider rates are charged separately by the provider.

‡ One of these GPU options will be selected depending on availability and current cloud pricing.

Cost controls

Usage-based does not mean uncontrolled.

A public support integration needs pricing controls, abuse protection, and visibility. LLMLab is designed to keep spend tied to real support value.

Traffic signal Abuse monitoring

Monitor suspicious traffic patterns and spam-like usage against a public integration or organization surface.

Traffic monitoring Abuse detection

Protective action Automated lockout

Support for protective behavior when traffic appears to abuse an exposed integration, assistant, or organization surface.

IP lockouts Org protection

What you are paying for

Usage across the actual system surface.

LLMLab pricing is designed around actual platform activity: workflow runs, model-backed responses, context ingestion, codebase parsing, retrieval, answer memory, web integration interactions, hosted model paths, and optional model infrastructure.

Tokens Model-backed responses and validation

Workflow runs Structured workflow execution

Parsing GitHub and codebase context extraction

Retrieval Knowledge search, embeddings, and reranking

Storage and GPU Vector storage, hosted models, and optional GPU worker activity

Get started

See how far $5 can go with a usage based plan

Use the free credit to build workflows, support agents, assistants, and operational AI systems. See just how far $5 can go before having to get the credit card.

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