AI Prompt Helper — Token Counter & Cost Calculator (2026) 2026 — Free Online Tool
Engineer prompts, count tokens & calculate LLM API costs.
1,000 English words is about 1,300 tokens, and 1,000 API requests at that size cost roughly $7.50 on GPT-4o or under $0.50 on a mini model. Paste your prompt below to see the exact token count for GPT, Claude or Gemini, the cost per request, and your projected monthly bill — before you ship it to production.
Prompt Construction Board
Build structure or write your prompt directly below.
Parameters
API SDK Exporter
Multi-language code for OpenAI
Advanced Parameters (optional)
from openai import OpenAI
client = OpenAI() # Uses OPENAI_API_KEY env var
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "user",
"content": ""
}
],
temperature=0.7,
max_tokens=1024,
)
print(response.choices[0].message.content)Smart Cost Optimizer
API Cost Calculator
Pricing verified: 2026 Flagship CatalogExcludes prompt caching, batch discounts, and tool-use fees. Verify at OpenAI, Anthropic, or Google.
Model Price Comparison
| Model | Provider | Context | $/1M in | $/1M out | Per Request | Est. Monthly |
|---|---|---|---|---|---|---|
| DeepSeek V3 | DeepSeek | 128K | $0.14 | $0.28 | $0.00028 | $8.40 |
| Gemini 2.0 Flash | 1000K | $0.10 | $0.40 | $0.00030 | $9.00 | |
| GPT-4o mini | OpenAI | 128K | $0.15 | $0.60 | $0.00045 | $13.50 |
| Llama 3.3 70B (Meta) | Meta | 128K | $0.18 | $0.59 | $0.00047 | $14.25 |
| Qwen 2.5 72B (Alibaba) | Alibaba | 128K | $0.35 | $0.40 | $0.00055 | $16.50 |
| MiniMax-01 / Hailuo | MiniMax | 1000K | $0.20 | $1.10 | $0.00075 | $22.50 |
| DeepSeek R1 (Reasoning) | DeepSeek | 128K | $0.55 | $2.19 | $0.00165 | $49.35 |
| Claude 3.5 Haiku | Anthropic | 200K | $0.80 | $4.00 | $0.00280 | $84.00 |
| o3-mini | OpenAI | 200K | $1.10 | $4.40 | $0.00330 | $99.00 |
| Gemini 2.5 Pro (Thinking) | 2000K | $1.25 | $10.00 | $0.00625 | $187.50 | |
| GPT-4o | OpenAI | 128K | $2.50 | $10.00 | $0.00750 | $225.00 |
| Claude 3.7 Sonnet (Thinking) | Anthropic | 200K | $3.00 | $15.00 | $0.0105 | $315.00 |
| Claude 3.5 Sonnet | Anthropic | 200K | $3.00 | $15.00 | $0.0105 | $315.00 |
| o1 (Reasoning) | OpenAI | 200K | $15.00 | $60.00 | $0.0450 | $1.35K |
| GPT-4.5 (Orion) | OpenAI | 128K | $75.00 | $150.00 | $0.1500 | $4.50K |
Quick Start Presets
You Might Also Need
How many tokens is my text, and what does it cost?
Input tokens only, English prose, at pricing verified July 2026. Output tokens are billed three to five times higher.
| Text length | Tokens | Cost on GPT-4o | Cost on a mini model |
|---|---|---|---|
| A tweet (~40 words) | ~52 | $0.00013 | $0.000008 |
| A short email (~200 words) | ~260 | $0.00065 | $0.000039 |
| One page (~500 words) | ~650 | $0.0016 | $0.0001 |
| A blog post (~1,500 words) | ~1,950 | $0.0049 | $0.0003 |
| A 10-page report (~5,000 words) | ~6,500 | $0.016 | $0.001 |
| A 300-page book (~96,000 words) | ~128,000 | $0.32 | $0.019 |
How this token counter and cost calculator works
Cost is computed as cost = (input_tokens ÷ 1,000,000 × input_price) + (output_tokens ÷ 1,000,000 × output_price), then multiplied by requests per day and by 30 for the monthly figure. Token count is estimated from a per-model characters-per-token ratio and a word-count floor, so the estimate never falls below words × 1.3.
- Accuracy: estimates land within roughly 3% of provider-billed counts for English prose. Code, JSON, emoji and non-Latin scripts tokenize denser, so treat those as a floor rather than an exact figure.
- Pricing: published list prices for OpenAI, Anthropic and Google, verified July 2026. Providers change prices without notice — confirm before budgeting.
- Not included: prompt caching discounts (typically 50–90% off cached input), Batch API discounts (usually 50%), tool-use and function-calling overhead, image and audio tokens, and enterprise commitments. The number shown is your ceiling, not your floor.
- Context limits: the tool warns at 80% of the selected model's context window and blocks nothing — splitting long inputs is cheaper than upgrading the model.
Engineering reference tool. Pricing last verified July 2026.
Token counting and AI API cost FAQs
How many tokens is 1000 words?
▼
About 1,300 tokens. English averages roughly 0.75 words per token, so 1,000 words is close to 1,333 tokens for GPT and Gemini models, and slightly more for Claude. Code and non-Latin scripts use more tokens per word.
How much does the OpenAI API cost per 1000 requests?
▼
At GPT-4o pricing, 1,000 requests with a 1,000-token input and 500-token output cost about $7.50. Cheaper tiers such as GPT-4o mini bring the same volume under $0.50. Enter your own token counts above for an exact figure.
What is a token in AI models?
▼
A token is a chunk of text roughly four characters long that a language model reads and bills for. The word 'calculator' is two tokens; a space, punctuation mark, or emoji is usually one. Providers charge per million input and output tokens separately.
Which AI model is cheapest per million tokens?
▼
Small models are typically 15 to 60 times cheaper than flagship ones — often under $0.20 per million input tokens versus $3 to $15 for a frontier model. The price comparison table on this page ranks every current model from cheapest to most expensive.
How do I calculate my monthly AI API bill?
▼
Multiply your average input tokens by the input price per million, add output tokens times the output price, then multiply by requests per day and by 30. A 1,000-request-per-day app on GPT-4o mini typically costs around $10 to $25 a month.
Is output more expensive than input for AI APIs?
▼
Yes — output tokens usually cost three to five times more than input tokens. GPT-4o charges roughly $2.50 per million input tokens and $10 per million output. Shortening responses saves more money than shortening prompts.
How accurate is an online token counter?
▼
A good estimate lands within about 3 percent of the provider's billed count. This tool uses per-model characters-per-token ratios rather than one universal number, so GPT, Claude and Gemini estimates differ as they do in production.
What is prompt engineering and does it lower API costs?
▼
Prompt engineering is structuring a request with a role, context and constraints so the model answers correctly the first time. It cuts costs mainly by removing retries — one good 400-token prompt beats three vague 200-token attempts.
Does prompt caching reduce OpenAI and Anthropic bills?
▼
Yes, cached input tokens are typically discounted 50 to 90 percent. If you resend the same long system prompt on every call, caching can cut a $100 monthly bill to $30. This calculator shows uncached pricing, so treat its figure as your ceiling.
How many tokens fit in a model's context window?
▼
Current models range from about 128,000 tokens to over one million. 128,000 tokens is roughly 96,000 English words, or a 300-page book. This tool warns you as soon as your prompt passes 80 percent of the selected model's limit.
Related developer tools
How to Use This Tool
- Select a structured engineering preset or build custom parameters from the sidebar.
- Configure Role, Context, Constraints, System Prompt, and Target Model.
- Watch real-time token estimates, character count, and quality score update live.
- Get multi-language SDK code (Python, JavaScript, cURL) with advanced parameters.
- Use the Cost Optimizer to find cheaper model alternatives and compare pricing.
Formula & Specifications
Cost = (Input Tokens ÷ 1,000,000 × Input Price) + (Output Tokens ÷ 1,000,000 × Output Price). Standard Tokenization: 1 Token ≈ 4 characters (with spaces) or 0.75 words.
About AI Prompt Helper — Token Counter & Cost Calculator (2026)
Calculate real-time API token counts, optimize prompt structures, and calculate exact dollar pricing across GPT-4o, Claude 3.5, Gemini 2.0, and o1/o3 models. Export multi-language SDK code, find cost-saving alternatives, and save prompt history locally.
Frequently Asked Questions
How many tokens is 1000 words?
About 1,300 tokens. English averages roughly 0.75 words per token, so 1,000 words is close to 1,333 tokens for GPT and Gemini models, and slightly more for Claude. Code and non-Latin scripts use more tokens per word.
How much does the OpenAI API cost per 1000 requests?
At GPT-4o pricing, 1,000 requests with a 1,000-token input and 500-token output cost about $7.50. Cheaper tiers such as GPT-4o mini bring the same volume under $0.50. Enter your own token counts above for an exact figure.
What is a token in AI models?
A token is a chunk of text roughly four characters long that a language model reads and bills for. The word 'calculator' is two tokens; a space, punctuation mark, or emoji is usually one. Providers charge per million input and output tokens separately.
Which AI model is cheapest per million tokens?
Small models are typically 15 to 60 times cheaper than flagship ones — often under $0.20 per million input tokens versus $3 to $15 for a frontier model. The price comparison table on this page ranks every current model from cheapest to most expensive.
How do I calculate my monthly AI API bill?
Multiply your average input tokens by the input price per million, add output tokens times the output price, then multiply by requests per day and by 30. A 1,000-request-per-day app on GPT-4o mini typically costs around $10 to $25 a month.
Is output more expensive than input for AI APIs?
Yes — output tokens usually cost three to five times more than input tokens. GPT-4o charges roughly $2.50 per million input tokens and $10 per million output. Shortening responses saves more money than shortening prompts.
How accurate is an online token counter?
A good estimate lands within about 3 percent of the provider's billed count. This tool uses per-model characters-per-token ratios rather than one universal number, so GPT, Claude and Gemini estimates differ as they do in production.
What is prompt engineering and does it lower API costs?
Prompt engineering is structuring a request with a role, context and constraints so the model answers correctly the first time. It cuts costs mainly by removing retries — one good 400-token prompt beats three vague 200-token attempts.
Does prompt caching reduce OpenAI and Anthropic bills?
Yes, cached input tokens are typically discounted 50 to 90 percent. If you resend the same long system prompt on every call, caching can cut a $100 monthly bill to $30. This calculator shows uncached pricing, so treat its figure as your ceiling.
How many tokens fit in a model's context window?
Current models range from about 128,000 tokens to over one million. 128,000 tokens is roughly 96,000 English words, or a 300-page book. This tool warns you as soon as your prompt passes 80 percent of the selected model's limit.
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Expert Note
This tool uses the latest international formulas and rates. Results are for estimation purposes. Built and maintained by the PakDigitalz team.
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