LLM API Pricing Comparison: TokenTab vs Checking Each Provider's Pricing Page

Updated 2026-10-25. Checked against official provider docs and pricing pages on 2026-10-25.

To compare LLM API prices, you have two options. You can open every provider's pricing page and build a spreadsheet, or you can use a comparison tool that has already collected the numbers. This page compares those two approaches honestly, including where you should skip TokenTab and go straight to the source.

The short answer

• For a quick, side-by-side estimate of what an agent or workload costs on different models, a comparison calculator is faster.
• For the final number on your bill, especially anything involving caching, batch, long context, regional pricing, or enterprise discounts, the provider's official pricing page is the authority. Always.

For a ranked shortlist built from these prices, see the cheapest LLM for AI agents in 2026.

What comparing by hand involves

TokenTab tracks 32 models from 9 providers: OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, Meta, Moonshot (Kimi), and MiniMax. Comparing them by hand means:

1. Opening nine pricing pages, each laid out differently.
2. Normalizing units. Most pages quote per 1M tokens, but tiers and footnotes vary.
3. Finding the conditions that change the price: long-context thresholds (for example, OpenAI's GPT-6 models above 272K input tokens, Grok 4.7 above 200K, and Claude Haiku 5.5 above 100K), peak vs off-peak pricing (DeepSeek, whose off-peak rates are half the peak rate), and promo end dates (Google's Gemini 4 Argon promo price runs through Nov 30, 2026).
4. Doing the math for your workload, because a lower input price can still lose if the model writes more output.

None of that is hard. It's just slow, and it has to be redone every time a price changes.

What TokenTab does

TokenTab is a free calculator. It has no sign-up and isn't affiliated with any provider. Here is what's on the site today:

• AI agent cost calculator: enter tool calls per task, input and output tokens per call, and tasks per day. It shows cost per task, per day, and per month for 32 models.
• Compare all models table: the same workload priced across every model at once.
• Copy share link: the link saves your inputs in the URL, so a teammate opens exactly the same scenario.
• Prompt caching savings calculator: cached vs uncached input cost, using each provider's official cached-input price.
• Subscription vs API tool: when a Claude or Codex plan beats paying per token.
• Head-to-head model comparison pages, per-model pricing pages, and a coding-agent cost-per-task benchmark page.
• Source links: each provider's official pricing page is linked so you can check any number.

How accurate are the prices?

All prices come from one file, models.json, which shows its last-updated date (currently 2026-10-25). models.json is checked by hand against the official pricing pages every day around 9 AM AKDT and updated when a price changes. There is no automatic syncing.

That means two things. A price change can appear on a provider's page before it reaches TokenTab. And every number traces back to a page a person actually read. If a number looks off, the linked source wins.

Side-by-side

Where TokenTab falls short (honest cons)

• List prices only. The main calculator uses standard-tier, short-context prices. Batch discounts, long-context surcharges, priority tiers, regional pricing, and image, audio, or tool fees aren't in the headline number. Some are mentioned in model notes, but they aren't calculated.
• Not real-time. By-hand checks are deliberate, but there is a window when a provider has changed a price and TokenTab hasn't yet.
• Coverage is curated. 32 models isn't every model. Older, regional, fine-tuned, and open-weights-on-your-own-GPU options are mostly not listed. For the self-hosting side, see self-hosting vs API break-even.
• Your token counts are your guess. The calculator is only as good as the tokens-per-call numbers you enter. Measure them from your logs if you can.
• No negotiated pricing. If you have a committed-spend deal, your real rate differs.

Where checking by hand falls short

• Slow to compare across providers. Nine layouts and nine sets of footnotes.
• Easy to compare the wrong thing. Input price alone misleads for agents. Output and reasoning tokens often dominate.
• No workload view. A pricing page tells you $ per 1M tokens, not what your agent costs a month.

Recommended workflow

1. Shortlist with a comparison calculator: run your real workload across all models and sort by monthly cost.
2. Verify the two or three finalists on their official pricing pages, with special attention to long context, caching, batch, and promo end dates.
3. Measure a pilot, then rerun the numbers with your real token counts.
4. Set spend limits at the provider before going to production.

Sources

Retrieved 2026-10-25.

• TokenTab: calculator, prompt caching calculator, subscription vs API, coding agent cost per task
• TokenTab models.json (lastUpdated 2026-10-25), including the long-context, promo, and peak notes cited above
• OpenAI: https://developers.openai.com/api/docs/pricing
• Anthropic: https://platform.claude.com/docs/en/about-claude/pricing
• Google: https://ai.google.dev/gemini-api/docs/pricing
• xAI: https://docs.x.ai/developers/pricing
• DeepSeek: https://api-docs.deepseek.com/quick_start/pricing
• Mistral: https://docs.mistral.ai/inference/pricing
• Meta: https://dev.meta.ai/docs/pricing-rate-limits
• Moonshot: https://platform.kimi.ai/docs/pricing/chat
• MiniMax: https://platform.minimax.io/docs/pricing/overview