Credit Decoder · what is a credit worth?

What is an AI credit actually worth?

GitHub credits, Copilot Studio credits, Anthropic CCU, Cursor’s $-budget — decode any of them into real dollars and into actual model usage (tokens & messages).

Pricing verified: 2026-08-23 SSOT-sourced rates$0.01 = 1 credit, mostly
What this calculator does

Decode any vendor credit — GitHub AI Credits, Copilot Studio credits, Anthropic CCU, Cursor's $-budget — into real dollars and into actual model usage (tokens & messages).

Why use it
  • Most AI "credits" are just repriced tokens — usually $0.01 each. This shows the real value.
  • Credit rates are read live from the verified pricing catalog (no stale hardcodes)
  • Convert a credit balance into tokens and chat-messages on any model you pick
  • Pairs with Tier Showdown to size a bare "5×/20×" multiplier in dollars

New to this calculator? Start with the ⚡ Playground — a few sliders, instant ballpark. Then switch to the 🧮 Calculator for your exact number.

Two ways to use this: visualize in the Playground, then get your number in the Calculator.

▶Playground A quick, visual way to see which factors move your dollar value the most. Open the playground → ▤Calculator Enter your real workload for a precise dollar value you can apply to your own usage. Go to the calculator →
Credit Decoder Playground
Drag the sliders for an instant estimate.
What do these credits actually buy?

Turn a credit balance into real model usage. Drag the levers; the breakdown shows dollars and tokens too.

Messages those credits buy
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Change the input sliders below to see new estimates.

How we got this estimate
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💡Preview decodes GitHub AI Credits ($0.01 each) on Claude Sonnet 4.6. Credit count scales everything; input-share and tokens-per-message set how many messages that buys. Open the full tool to switch credit type or model.

GitHub credits, Copilot Studio credits, Anthropic CCU, Cursor’s $-budget — decode any of them into real dollars and into actual model usage (tokens & messages).

Credit Decoder Calculator

Enter your exact numbers for a precise result.
📊 Not sure of a value? Fields with a ▾ Typical pill offer broad industry ballparks (sourced typical ranges) so you can move forward now — your result gets more accurate as you replace them with your own measured numbers. Values marked * are rough estimates.
🎮 Interactive Guide & Calculator Playground →
🎛 Inputs
Hint: What the vendor's plan counts: credits, messages, or words. Pick what yours uses.
Hint: How many of those units your plan includes per month.
Hint: Which model to price against, to see what those units really cost.
Hint: Roughly how much is input vs the reply. 80 = mostly input. Leave as-is if unsure.
Hint: Length of a typical message. Default 1,500 is a few paragraphs; leave if unsure.

Results

Dollar value
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Equivalent tokens
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Equivalent messages
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at your tokens/message
How this decodes

    Go deeper

    Our playbooks on cutting this number.

    🧾
    Plan Overage Calculator
    Pay overage or upgrade?
    ⚔️
    Tier Showdown
    Compare $100/$200 tiers
    🧮
    Cost Calculator
    Baseline workload cost

    Need help using this calculator for your workloads?

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    📖 Data sources & methodology 150 text models · 9 embeddings · 40 vision · 55 audio · 8 vector DBs across 10 vendor pages · last verified 2026-08-23

    Methodology

    • All prices are USD per 1 million tokens, current as of 2026-08-23.
    • 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
    2026-08-23
    https://www.anthropic.com/pricing
    Daily snapshot since Sep 2023 · 657 days captured
    Anthropic Docs
    2026-08-23
    https://platform.claude.com/docs/en/about-claude/pricing
    Daily snapshot since Sep 2023 · 657 days captured
    OpenAI
    2026-08-23
    https://openai.com/api/pricing/
    Daily snapshot since Sep 2023 · 658 days captured
    Google AI
    2026-08-23
    https://ai.google.dev/gemini-api/docs/pricing
    Daily snapshot since Dec 2023 · 633 days captured
    Google Vertex
    2026-08-23
    https://cloud.google.com/vertex-ai/generative-ai/pricing
    Daily snapshot since Dec 2023 · 633 days captured
    DeepSeek
    2026-08-23
    https://api-docs.deepseek.com/quick_start/pricing
    Daily snapshot since May 2024 · 572 days captured
    xAI
    2026-08-23
    https://x.ai/api
    Daily snapshot since Nov 2024 · 490 days captured
    Mistral
    2026-08-23
    https://mistral.ai/pricing
    Daily snapshot since Dec 2023 · 631 days captured
    Cohere
    2026-08-23
    https://cohere.com/pricing
    Daily snapshot since Sep 2023 · 657 days captured
    Voyage AI
    2026-08-11
    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.
    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 →