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LLM API Token Cost Calculator: Claude, GPT, Gemini & DeepSeek Pricing (2026)

Compare daily and monthly inference costs across frontier and open-weight LLM APIs with input/output token sliders, system prompt caching discounts, and batch API savings.Documentation & FAQs ↓

2026 AI Chatbot & LLM API Token Cost Calculator — Interactive Console
Runs locally in your browser • Instant output
Daily Requests2,500
Prompt Cache Hit %40%
LLM ModelRates (In / Out 1M)Cost / 1K CallsDaily SpendMonthly (30-Day)
Gemini 2.5 Flash Lowest Cost$0.15 / $0.60$0.459$1.15
$34.42
GPT-4o mini $0.15 / $0.60$0.486$1.22
$36.45
DeepSeek R1 / V3 $0.27 / $1.10$0.837$2.09
$62.78
Claude 3.5 Haiku $0.80 / $4.00$2.722$6.80
$204.12
Gemini 2.5 Pro $1.25 / $10.00$6.073$15.18
$455.49
GPT-4o $2.50 / $10.00$8.100$20.25
$607.50
Claude 3.7 Sonnet $3.00 / $15.00$10.206$25.52
$765.45
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2026 LLM API Token Pricing, Context Caching & Word-to-Token Benchmark Table

2026 Verified Reference
Quick Answer & 2026 Technical Summary (llm api token cost calculator)Updated 2026 Standard

In English prose and source code, `1,000 tokens` equals approximately `750 words` (`1 token ≈ 0.75 words` or `4 characters`). In 2026, enabling Prompt Context Caching reduces repeated system prompt and RAG document input token costs by 50%–90%, while async Batch APIs cut both input and output costs by 50%.

Monthly API Cost ($) = ((Input_Tokens × Input_Rate) + (Cached_Tokens × Cache_Rate) + (Output_Tokens × Output_Rate)) / 1,000,000
Token Conversion Rule: 1M Tokens ≈ 750,000 English words (~1,500 pages)
Prompt Caching Discount: 50% to 90% off repeated prefix tokens
Batch Async API Discount: 50% off standard synchronous rates (24h SLA)
2026 Frontier / Flash Model TierInput Cost / 1M TokensCached Input / 1M TokensOutput Cost / 1M & Context Window
OpenAI GPT-4o (Multimodal Flagship)$2.50 / 1M$1.25 / 1M (50% Auto-Cache)$10.00 / 1M (128k Context Window)
OpenAI GPT-4o mini (High-Volume)$0.15 / 1M$0.075 / 1M (50% Auto-Cache)$0.60 / 1M (128k Context Window)
Anthropic Claude 3.7 Sonnet$3.00 / 1M$0.30 / 1M (90% Cache Read)$15.00 / 1M (200k Context + Thinking)
Google Gemini 2.5 Pro$1.25 / 1M (≤200k)$0.31 / 1M (Context Cache)$10.00 / 1M (Up to 2M Token Context)
Google Gemini 2.5 Flash$0.15 / 1M$0.0375 / 1M (75% Cache Save)$0.60 / 1M (1M Token Context Window)
DeepSeek V3 / R1 (Open-Weight API)$0.27 – $0.55 / 1M$0.07 – $0.14 / 1M (Disk Cache)$1.10 – $2.19 / 1M (64k–128k Context)
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Step-by-Step Workflow

4 Easy Steps
01Phase 1

Set Daily Request Volume

Adjust the Daily API Requests slider to match your expected traffic.

02Phase 2

Configure Average Input & Output Tokens

Enter average prompt input tokens (including RAG context) and completion output tokens.

03Phase 3

Set Prompt Cache Hit Rate (%)

Specify what percentage of input tokens come from cached system prompts.

04Phase 4

Compare Monthly Cost Table

Review the sorted comparison table from lowest cost to flagship frontier models.

Real-World Applications

AI SaaS Margin & Pricing Architecture

Forecast monthly API bills at 1,000, 10,000, or 100,000 daily user queries before launching.

Model Routing Optimization

Calculate how much you save by routing 80% of classification tasks to Flash/Mini models and 20% to Pro/Sonnet models.

Related Editorial Guide10 Best Artificial Intelligence Chatbots in 2026
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