AI Strategy Tool

LLM Pricing Comparison

Compare price, context window and features of every major LLM side by side — Claude, GPT-4o, Gemini, Llama, Mistral, DeepSeek. Built-in calculator ranks models by your real workload cost. Free.

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Quick Answer

The LLM Pricing Comparison puts every major language model — Claude, GPT-4o, Gemini, Llama, Mistral, DeepSeek — in one sortable table showing input/output price, context window, vision and tool-use support. Set your token workload in the built-in calculator and it ranks models by what they'd actually cost you per call and per month. 100% client-side.

Cost calculator — set your workload

Input tokens / callOutput tokens / callCalls / month

Model	Input /1M	Output /1M	Context	Vision	Tools	Cost / call	/ month
Gemini 2.0 Flash Google · Cheapest big-context model	$0.1	$0.4	1M	✓	✓	$0.00052	$0.5200cheapest
GPT-4o mini OpenAI · Very cheap; good for simple tasks	$0.15	$0.6	128K	✓	✓	$0.00078	$0.7800
DeepSeek-V3 DeepSeek · Very low cost; open weights	$0.27	$1.1	128K	—	✓	$0.00142	$1.42
Llama 3.3 70B Meta/Groq · Open weights; cheap via Groq	$0.59	$0.79	128K	—	✓	$0.00181	$1.81
Claude Haiku 4.5 Anthropic · Cheapest Claude; great for high volume	$0.8	$4	200K	✓	✓	$0.00480	$4.80
Gemini 2.0 Pro Google · 2M context window	$1.25	$5	2M	✓	✓	$0.00650	$6.50
Mistral Large 2 Mistral · EU-hosted option	$2	$6	128K	—	✓	$0.00880	$8.80
GPT-4.1 OpenAI · 1M context window	$2	$8	1M	✓	✓	$0.0104	$10.40
GPT-4o OpenAI · Multimodal flagship	$2.5	$10	128K	✓	✓	$0.0130	$13.00
OpenAI o1-mini OpenAI · Cheaper reasoning	$3	$12	128K	—	—	$0.0156	$15.60
Claude Sonnet 4.6 Anthropic · Best all-round value	$3	$15	200K	✓	✓	$0.0180	$18.00
OpenAI o1 OpenAI · Deep reasoning model	$15	$60	200K	✓	✓	$0.0780	$78.00
Claude Opus 4.7 Anthropic · Top reasoning; prompt caching 90% off	$15	$75	200K	✓	✓	$0.0900	$90.00

💡 Prices are published list prices (USD per 1M tokens) and change often — verify against each provider's pricing page before budgeting. Anthropic prompt caching cuts cached input ~90%; Batch APIs cut cost ~50%. All calculation runs client-side.

Quick Facts

Tool Name: LLM Pricing Comparison
Category: AI Strategy Tool
Price: ✓ Free
Platform: Browser Based
Login Required: ✓ No
Last updated: 2026-05-20

How to Use LLM Pricing Comparison

Enter Your Input
Paste your text or fill in the required fields in the tool above.
Click Generate
Hit the generate or analyze button to start processing.
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How to pick the cheapest LLM for your use case

Don't compare list prices in isolation — compare them against your workload. A long-context summarizer (heavy input, light output) and a copy generator (light input, heavy output) will rank models differently. Enter your real token mix in the calculator above and let the table sort by true cost per call.

How to cut your LLM bill

Start with the cheap tier — Haiku, GPT-4o mini, Gemini Flash and DeepSeek handle most tasks at 10–20× lower cost than flagship models.
Use prompt caching — Anthropic charges ~10% for cached input tokens; cache any repeated system prompt.
Use the Batch API — ~50% off for work that doesn't need a real-time response.
Cap max output tokens — you pay for every output token; don't allow 4,000 when you need 400.

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Frequently Asked Questions

Everything you need to know about LLM Pricing Comparison

Which models does the comparison cover?

13 models across every major provider: Claude Opus 4.7, Sonnet 4.6 and Haiku 4.5 (Anthropic); GPT-4o, GPT-4o mini, GPT-4.1, o1 and o1-mini (OpenAI); Gemini 2.0 Flash and Pro (Google); Llama 3.3 70B (Meta, via Groq); Mistral Large 2; and DeepSeek-V3. Each row shows input/output price per million tokens, context window, vision and tool-use support.

How is 'cost per call' calculated?

Set your typical input tokens, output tokens and monthly call volume in the calculator. Cost per call = (input tokens ÷ 1,000,000 × input price) + (output tokens ÷ 1,000,000 × output price). The monthly column multiplies that by your call volume. The cheapest option for your specific workload is highlighted in green.

Why do input and output prices differ so much?

Output tokens are far more expensive to generate than input tokens are to process — often 4–5× the price. This means a model's 'cheapness' depends heavily on your input/output ratio. A summarization task (long input, short output) and a content-generation task (short input, long output) can rank models completely differently — which is why the calculator lets you set both.

Are these prices guaranteed accurate?

They're published list prices at the time of the last update, but LLM pricing changes frequently. Always verify against the provider's official pricing page before committing budget. Also note: real bills are often lower — Anthropic's prompt caching cuts cached input tokens by ~90%, and Batch APIs across providers cut cost ~50% for non-real-time work.

Is anything sent to a server?

No. The pricing data is bundled into the page and all calculations run in your browser. There's no API call, no tracking, and your workload numbers never leave your device.

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