Skip to main content
💡 Save ~17% with yearly billing — 2 months free on Pro & Team💡 Save ~17% with yearly billing — 2 months free on Pro & Team💡 Save ~17% with yearly billing — 2 months free on Pro & Team
TokenAtlas

AI spend management

Understand every dollar before you spend it on AI.

TokenAtlas is the AI cost modelling layer for teams building with LLMs. See exactly where projected token spend goes, test assumptions before you commit, and pick the right model for every workload.

  • Modelled cost per model, feature, environment and team
  • Scenario planning before you commit to a workload
  • Side-by-side cost simulation across GPT, Claude, Gemini and more
  • Forecast 12 months of cost on realistic growth curves
Try TokenAtlas free Open the calculator

Why AI spend management needs its own tool

Cloud FinOps dashboards weren't built for token economics. AI costs move with prompt length, model tier, cache hits, and reasoning mode — not CPU hours. TokenAtlas gives you a model-aware cost layer so engineering and finance work from the same numbers.

GPT spend management, before the first API call

OpenAI is the biggest line item on most AI bills. TokenAtlas prices every GPT-4o, GPT-4.1, mini and o1 workload by feature, environment and customer, and shows the exact prompt/output split driving cost so you can shrink it without breaking the product.

What you can do

Attribute modelled cost to a feature, customer, or environment. Compare scenarios against your forecast. Run what-if simulations before you swap a model in production. Export clean reports your CFO will actually accept.

What TokenAtlas does not do

TokenAtlas does not connect to provider accounts, ingest live usage, collect API keys, or read billing APIs. Every number comes from the volumes, prompt sizes and assumptions you enter, priced against our maintained pricing catalog.

Who it's for

Engineering leads who need a defensible AI budget. CTOs who want to know what AI costs before the next funding conversation. FinOps teams that have outgrown spreadsheets.

Frequently asked questions

What is AI spend management?
AI spend management is the practice of planning, allocating, and optimizing what your team pays for LLM APIs and AI infrastructure. TokenAtlas covers the modelling side: cost visibility for the workloads you describe, model selection, and budget planning in one workflow.
What is GPT spend management?
GPT spend management is the OpenAI-specific slice: understanding what every GPT-4o, GPT-4.1, GPT-4o mini and GPT-3.5 call costs, attributing that modelled cost to features and customers, and moving low-stakes traffic down to cheaper tiers. TokenAtlas can price and model OpenAI workloads per SKU and environment from the volumes and assumptions you provide.
How do I plan OpenAI API spend across a team?
Describe your OpenAI workloads in TokenAtlas by team, project or feature. You'll get per-feature modelled cost attribution, scenario comparisons, and budget thresholds you set yourself — so you can see an overrun coming before you commit to the workload.
How is AI spend management different from FinOps?
FinOps is the broader cloud financial-operations discipline. AI spend management is the AI-native slice: token-level cost modelling, model-mix optimization, and prompt-efficiency reviews — things traditional cloud FinOps tools weren't built for.
Which providers does TokenAtlas price for spend management?
Every provider in our maintained pricing catalog today: OpenAI, Anthropic, Google, Mistral, Groq and DeepSeek. New SKUs are added as they ship. Pricing catalog and side-by-side comparison live on the LLM comparison hub.
Can I forecast next quarter's AI bill?
Yes. TokenAtlas projects the next 3, 6 and 12 months of cost based on the usage curve you define — with adjustable growth assumptions and a swap-in-cheaper-model scenario for finance conversations.

Continue exploring