Budget Planner

Plan your AI budget across every use case

Add your use cases, set a monthly ceiling, see allocation + alerts. Share the URL with your team.

Pricing verified: 2026-06-05 Up to 6 use cases · Shareable via URL
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AI Budget Planner full size
What this calculator does

Set a monthly AI spend budget and see which features/workloads fit under it.

Why use it
  • Helps prioritize AI roadmap against Finance constraints
  • Shows which features push you over budget before you build them
📊 Calculator at a glance
🎛 CALCULATOR
🧩 Your use casesEach AI-powered feature/workflow to budget, with its own model + volume.How to choose: Add one row per workflow; load a preset to start, then edit per-row model, tokens, and requests.Read the full guide →

Add each AI-powered feature/workflow. We calculate monthly cost for each.

Load a preset starting pointA template portfolio (startup, enterprise, agent-heavy) that pre-fills typical use cases.How to choose: Pick the closest profile then adjust rows to your actual apps.Read the full guide →
📈 RESULTS
📋 Example Workload - change any field to see your actual cost
Monthly budget ceilingThe monthly spend cap to compare your portfolio against.How to choose: Enter your approved monthly AI budget; alerts flag when projected spend exceeds it.Read the full guide →
$
Projected monthly spend
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Remaining / over
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Cost allocation by use case

Where your AI budget goes.

💡 Recommendations
    Detail one use case → Get a FinOps retainer →
    🎯 Use this result to
    📅 Schedule a call to apply this to your workload

    Go deeper

    Our playbooks on cutting this number.

    🧮
    AI Unit Economics
    The math behind this tool
    📊
    Margin Calculator
    Feature-level profitability
    💾
    Prompt Cache ROI
    Free up budget room
    🔁
    Agent Loop Guardrails
    Cap the runaway scenarios

    The calculator's an estimate. Want the real number?

    A 5-day Quickscan ($1,500) reviews your actual usage across every pillar — financial, reliability, governance, privacy, MLOps, observability — and returns a concrete savings plan.

    Book a Quickscan →
    📖 Data sources & methodology 161 text models · 9 embeddings · 24 vision · 41 audio · 8 vector DBs across 10 vendor pages · last verified 2026-06-05

    Methodology

    • All prices are USD per 1 million tokens, current as of 2026-06-05.
    • Vendor-published values have no mark. Inferred/extrapolated values are marked with * and listed below.
    • Batch API discounts are 50% off standard rates across providers that offer Batch mode.
    • Prompt caching discounts vary by provider (typically 80-90% off cached input tokens).
    • Regional data-residency surcharges (Anthropic 1.1x, OpenAI 1.1x, Google regional tiers) are NOT included in base rates.
    • Long-context pricing tiers apply when input exceeds model threshold.
    • Embedding prices are input-only (no output tokens generated).

    Primary sources

    Last-verified date is the most recent successful daily snapshot (aicost_pricing_snapshots) or, when no snapshot exists yet, the latest successful crawler run (aicost_crawler_runs). 10 of 10 vendors are currently verified. Aggregator services (TokenCost, AI Pricing Guru, etc.) are not listed.

    Anthropic
    2026-06-05
    https://www.anthropic.com/pricing
    Daily snapshot since Sep 2023 · 578 days captured
    Anthropic Docs
    2026-06-05
    https://platform.claude.com/docs/en/about-claude/pricing
    Daily snapshot since Sep 2023 · 578 days captured
    OpenAI
    2026-06-05
    https://openai.com/api/pricing/
    Daily snapshot since Sep 2023 · 579 days captured
    Google AI
    2026-06-05
    https://ai.google.dev/gemini-api/docs/pricing
    Daily snapshot since Dec 2023 · 554 days captured
    Google Vertex
    2026-06-05
    https://cloud.google.com/vertex-ai/generative-ai/pricing
    Daily snapshot since Dec 2023 · 554 days captured
    DeepSeek
    2026-06-05
    https://api-docs.deepseek.com/quick_start/pricing
    Daily snapshot since May 2024 · 493 days captured
    xAI
    2026-06-05
    https://x.ai/api
    Daily snapshot since Nov 2024 · 411 days captured
    Mistral
    2026-06-05
    https://mistral.ai/pricing
    Daily snapshot since Dec 2023 · 552 days captured
    Cohere
    2026-06-05
    https://cohere.com/pricing
    Daily snapshot since Sep 2023 · 578 days captured
    Voyage AI
    2026-06-05
    https://docs.voyageai.com/docs/pricing

    Inferred values (marked with * in calculator tables)

    Derived from industry conventions, not directly published by the vendor. Typical conventions: cached input = 10% of base (90% off), Batch API = 50% of base (50% off).

    Vendor / Model Field Why it’s inferred
    Anthropic — Claude Sonnet 4.6 cachedInput Derived at 10% of input rate — Anthropic publishes 90% cache-hit discount on this tier.
    Anthropic — Claude Sonnet 4.5 cachedInput Derived at 10% of input rate; same 90% cache-hit convention as Sonnet 4.6.
    Anthropic — Claude Sonnet 4.5 batchInput Derived at 50% of standard input — Anthropic documents uniform 50% Batch discount.
    Anthropic — Claude Sonnet 4.5 batchOutput Derived at 50% of standard output — Anthropic documents uniform 50% Batch discount.
    Anthropic — Claude Haiku 4.5 cachedInput Derived at 10% of input rate — Anthropic 90% cache-hit discount convention.
    OpenAI — GPT-5.4 Mini cachedInput Derived at 10% of input — OpenAI documents automatic 90% discount on cache hits across GPT-5.x tier.
    OpenAI — GPT-5.4 Nano cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
    OpenAI — GPT-5.4 Nano batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
    OpenAI — GPT-5.4 Nano batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
    OpenAI — GPT-5.4 Pro cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
    OpenAI — GPT-5.4 Pro batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
    OpenAI — GPT-5.4 Pro batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
    OpenAI — GPT-5.2 cachedInput Derived at 10% of input; no residency uplift.
    OpenAI — GPT-5.2 batchInput Derived at 50% of input.
    OpenAI — GPT-5.2 batchOutput Derived at 50% of output.
    OpenAI — GPT-5 cachedInput Derived at 10% of input.
    OpenAI — GPT-5 batchInput Derived at 50% of input.
    OpenAI — GPT-5 batchOutput Derived at 50% of output.
    OpenAI — GPT-5.5 Pro cachedInput Derived at 10% of input — OpenAI does not publish a cached rate for *-pro models; using the family convention.
    OpenAI — GPT-5.5 Pro batchInput Derived at 50% of input.
    OpenAI — GPT-5.5 Pro batchOutput Derived at 50% of output.
    OpenAI — GPT-5.2 Pro cachedInput Derived at 10% of input — pro-tier convention.
    OpenAI — GPT-5.2 Pro batchInput Derived at 50% of input.
    OpenAI — GPT-5.2 Pro batchOutput Derived at 50% of output.
    OpenAI — GPT-5.1 batchInput Derived at 50% of input.
    OpenAI — GPT-5.1 batchOutput Derived at 50% of output.
    OpenAI — GPT-5 Pro batchInput Derived at 50% of input.
    OpenAI — GPT-5 Pro batchOutput Derived at 50% of output.
    OpenAI — GPT-5 Nano cachedInput Derived at 10% of input.
    OpenAI — GPT-5 Nano batchInput Derived at 50% of input.
    OpenAI — GPT-5 Nano batchOutput Derived at 50% of output.
    Google — Gemini 3 Flash cachedInput Derived at 10% of input — Google caching discount convention ~90%.
    Google — Gemini 3.1 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
    Google — Gemini 3.1 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
    Google — Gemini 3.1 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
    Google — Gemini 2.5 Pro cachedInput Derived at 10% of input.
    Google — Gemini 2.5 Flash cachedInput Derived at 10% of input.
    Google — Gemini 2.5 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
    Google — Gemini 2.5 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
    Google — Gemini 2.5 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
    Google — Gemini 2.0 Flash cachedInput Derived at 25% of input per Google 2.0 family caching rates.
    Google — Gemini 2.0 Flash batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
    Google — Gemini 2.0 Flash batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
    Google — Gemini 2.0 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
    Google — Gemini 2.0 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
    Google — Gemini 2.0 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
    xAI — Grok 4 (legacy) cachedInput Extrapolated at 25% of base.

    Pricing is cross-verified against the LiteLLM community registry when available. Daily snapshots are kept in aicost_pricing_snapshots; every change is logged to aicost_price_changelog with old & new values for full audit trail. Read the full methodology →