Claude · Fast / Budget · 200K context window
$0.005000 per call at 2,000 input / 600 output tokens.
Per call
$0.005000
10K calls/mo
$50
Cache savings
90% off input
Batch savings
50% off all
Adjust token counts, volume, and discount toggles to model your invoice parsing spend. Prices verified daily against provider pricing pages.
Call Claude Haiku 4.5 with the Anthropic Python SDK:
from anthropic import Anthropic
client = Anthropic()
response = client.messages.create(
model="claude-haiku-4-5",
max_tokens=600,
messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.005000 per call at standard rates
# Input: $1.00/MTok
# Output: $5.00/MTokPer-call cost for all models scoring 50+ on invoice parsing benchmarks. Hover for details.
Cheapest viable option: GPT 5.6 Luna at $0.001120/call (78% less, 89/100 quality).
Invoices are short, highly repetitive documents processed in bulk: the ideal batch API workload. Per-document cost is low; total cost is set by volume and by whether you are paying full rate for a job that could have run asynchronously overnight at a discount. The extraction schema is constant, so it should never be paying full input rate either.
For Claude Haiku 4.5 specifically, that means output tokens cost 5.0x more than input, at $5.00 vs $1.00 per MTok. At this use case’s 2,000/600 token split, output accounts for 60% of the $0.005000 per-call cost.
| Direction | $/MTok | Tokens per call |
|---|---|---|
| Input | $1.00 | 2,000 |
| Output | $5.00 | 600 |
Caching drops input cost from $1.00 to $0.10/MTok. For repeated system prompts, that saves $0.001800 per call.
Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.
| Monthly volume | Cost per call | Standard monthly | Cached monthly | You save with caching |
|---|---|---|---|---|
| 10,000 calls | $0.005000 | $50 | $32 | $18 |
| 50,000 calls | $0.005000 | $250 | $160 | $90 |
| 100,000 calls | $0.005000 | $500 | $320 | $180 |
| 500,000 calls | $0.005000 | $2,500 | $1,600 | $900 |
| 1,000,000 calls | $0.005000 | $5,000 | $3,200 | $1,800 |
Claude Haiku 4.5 is a solid pick for invoice parsing
Scores 88/100 (rank #2 of 20). Good balance of quality and cost for invoice parsing.
Top-ranked: GPT 5.6 Terra (90/100) at $0.0112/call
Claude Haiku 4.5 scores by task type. Invoice Parsing highlighted.
| Task type | Confidence score | Rank out of 20 |
|---|---|---|
| Classification | 90/100 | #2 |
| Extraction(current page) | 88/100 | #2 |
| Q&A | 86/100 | #4 |
| Summarization | 82/100 | #5 |
| Code Generation | 72/100 | #6 |
| Code Review | 70/100 | #7 |
| Reasoning | 65/100 | #7 |
| Creative Writing | 60/100 | #7 |
Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.
13 models score 80+ on invoice parsing benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (78% less, 89/100 quality).
| Model | Provider | Input $/MTok | Output $/MTok | Quality | Per call | vs Claude |
|---|---|---|---|---|---|---|
| GPT 5.6 Luna | GPT | $0.20 | $1.20 | 89/100 | $0.001120 | 78% cheaper |
| Gemini 3.5 Flash-Lite | Gemini | $0.30 | $2.50 | 83/100 | $0.002100 | 58% cheaper |
| Gemini 3 Flash | Gemini | $0.50 | $3.00 | 86/100 | $0.002800 | 44% cheaper |
| Gemini 3.5 Flash | Gemini | $1.50 | $9.00 | 90/100 | $0.008400 | 68% more |
| Claude Sonnet 5 | Claude | $2.00 | $10.00 | 88/100 | $0.010000 | 100% more |
| GPT 5.6 Terra | GPT | $2.00 | $12.00 | 90/100 | $0.0112 | 124% more |
| Gemini 3.1 Pro | Gemini | $2.00 | $12.00 | 85/100 | $0.0112 | 124% more |
| GPT 5.4 | GPT | $2.50 | $15.00 | 89/100 | $0.0140 | 180% more |
| Claude Sonnet 4.6 | Claude | $3.00 | $15.00 | 86/100 | $0.0150 | 200% more |
| GPT 5.6 Sol | GPT | $4.00 | $20.00 | 88/100 | $0.0200 | 300% more |
| Claude Opus 4.8 | Claude | $5.00 | $25.00 | 82/100 | $0.0250 | 400% more |
| GPT 5.5 | GPT | $5.00 | $30.00 | 87/100 | $0.0280 | 460% more |
| Claude Fable 5 | Claude | $10.00 | $50.00 | 85/100 | $0.0500 | 900% more |
Provider
Claude
Tier
Fast / Budget
Context
200K tokens
Released
Oct 2025
| Model | Tier | Input $/MTok | Output $/MTok | Context |
|---|---|---|---|---|
| Claude Opus 4.8 | Flagship | $5.00 | $25.00 | 200K |
| Claude Sonnet 4.6 | Mid-tier | $3.00 | $15.00 | 200K |
| Claude Sonnet 5 | Mid-tier | $2.00 | $10.00 | 200K |
| Claude Opus 5 | Flagship | $5.00 | $25.00 | 1,000K |
| Claude Fable 5.1 | Flagship | $10.00 | $50.00 | 1,000K |
| Claude Fable 5 | Flagship | $10.00 | $50.00 | 1,000K |
You can compare Claude Haiku 4.5 head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.
See how Claude Haiku 4.5 costs change across different workload types.
Code Generation
$0.0220/call
Unit Test Generation
$0.0280/call
SQL Generation
$0.006500/call
API Generation
$0.0330/call
Code Refactoring
$0.0240/call
Code Review
$0.0150/call
PR Review
$0.0230/call
Security Review
$0.0185/call
Bug Detection
$0.0150/call
Document Summarization
$0.0150/call
PDF Summarization
$0.0225/call
Meeting Notes
$0.0180/call
Email Summarization
$0.005500/call
Chatbot
$0.007000/call
RAG Pipeline
$0.0135/call
Customer Support Bot
$0.008000/call
FAQ Bot
$0.005500/call
Data Extraction
$0.009000/call
JSON Extraction
$0.007000/call
Resume Parsing
$0.006500/call
Chain of Thought
$0.0280/call
Legal Analysis
$0.0300/call
Math Reasoning
$0.0165/call
Financial Analysis
$0.0280/call
Content Moderation
$0.001000/call
Sentiment Analysis
$0.001000/call
Categorization
$0.001550/call
Intent Detection
$0.000800/call
Copywriting
$0.0105/call
Blog Writing
$0.0410/call
Marketing Copy
$0.0158/call
Product Descriptions
$0.008000/call
A typical invoice parsing call using Claude Haiku 4.5 costs about $0.005000 per call. This estimate uses 2,000 input tokens and 600 output tokens at standard rates. Standard rates are $1.00 per million input tokens and $5.00 per million output tokens.
Claude Haiku 4.5 scores 88 out of 100 on invoice parsing benchmarks overall. It ranks #2 across all 20 models in our cross-provider registry. The highest-ranked model for this task is GPT 5.6 Terra from GPT. That model scores 90/100 on this task type. Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.
The most affordable model for invoice parsing above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 89/100. Switching from Claude Haiku 4.5 to GPT 5.6 Luna saves about 78% per API call.
Three strategies lower Claude Haiku 4.5 costs for this task type effectively. Prompt caching gives a 90% discount on input tokens when reusing system prompts. The batch API gives 50% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.005000 to about $0.000250 per call.
Claude has 6 other models alongside Claude Haiku 4.5 today: Claude Opus 4.8 at $5.00/$25.00 per million tokens (flagship), Claude Sonnet 4.6 at $3.00/$15.00 per million tokens (mid-tier), Claude Sonnet 5 at $2.00/$10.00 per million tokens (mid-tier), Claude Opus 5 at $5.00/$25.00 per million tokens (flagship), Claude Fable 5.1 at $10.00/$50.00 per million tokens (flagship), Claude Fable 5 at $10.00/$50.00 per million tokens (flagship). The right choice depends on whether your invoice parsing workload prioritizes quality, cost, or speed.
Claude Haiku 4.5 supports a context window of 200K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For invoice parsing, typical calls use 2,000 input and 600 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.
This calculator estimates costs based on published rates only. Connect your API usage to see where your money goes and which models drive your spend.