Claude · Mid-tier · 200K context window
$0.0140 per call at 3,000 input / 800 output tokens.
Per call
$0.0140
10K calls/mo
$140
Cache savings
90% off input
Batch savings
50% off all
Adjust token counts, volume, and discount toggles to model your json extraction spend. Prices verified daily against provider pricing pages.
Call Claude Sonnet 5 with the Anthropic Python SDK:
from anthropic import Anthropic
client = Anthropic()
response = client.messages.create(
model="claude-sonnet-5",
max_tokens=800,
messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0140 per call at standard rates
# Input: $2.00/MTok
# Output: $10.00/MTokPer-call cost for all models scoring 50+ on json extraction benchmarks. Hover for details.
Cheapest viable option: GPT 5.6 Luna at $0.001560/call (89% less, 89/100 quality).
Structured JSON output is compact and predictable, so cost is set almost entirely by how much source text you send. The schema itself is identical on every call and belongs in the cached prefix. This is also a task where a smaller model often matches a larger one: the output space is constrained by the schema, which limits how wrong a cheaper model can go.
For Claude Sonnet 5 specifically, that means output tokens cost 5.0x more than input, at $10.00 vs $2.00 per MTok. At this use case’s 3,000/800 token split, output accounts for 57% of the $0.0140 per-call cost.
| Direction | $/MTok | Tokens per call |
|---|---|---|
| Input | $2.00 | 3,000 |
| Output | $10.00 | 800 |
Caching drops input cost from $2.00 to $0.20/MTok. For repeated system prompts, that saves $0.005400 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 | $0.0140 | $140 | $86 | $54 |
| 50,000 calls | $0.0140 | $700 | $430 | $270 |
| 100,000 calls | $0.0140 | $1,400 | $860 | $540 |
| 500,000 calls | $0.0140 | $7,000 | $4,300 | $2,700 |
| 1,000,000 calls | $0.0140 | $14,000 | $8,600 | $5,400 |
Claude Sonnet 5 is a solid pick for json extraction
Scores 88/100 (rank #2 of 20). Good balance of quality and cost for json extraction.
Top-ranked: GPT 5.6 Terra (90/100) at $0.0156/call
Claude Sonnet 5 scores by task type. JSON Extraction highlighted.
| Task type | Confidence score | Rank out of 20 |
|---|---|---|
| Code Review | 96/100 | #1 |
| Code Generation | 93/100 | #2 |
| Summarization | 91/100 | #1 |
| Reasoning | 90/100 | #2 |
| Q&A | 89/100 | #2 |
| Extraction(current page) | 88/100 | #2 |
| Creative Writing | 87/100 | #3 |
| Classification | 86/100 | #3 |
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 json extraction benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (89% 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 | $0.001560 | 89% cheaper |
| Gemini 3.5 Flash-Lite | Gemini | $0.30 | $2.50 | 83/100 | $0.002900 | 79% cheaper |
| Gemini 3 Flash | Gemini | $0.50 | $3.00 | 86/100 | $0.003900 | 72% cheaper |
| Claude Haiku 4.5 | Claude | $1.00 | $5.00 | 88/100 | $0.007000 | 50% cheaper |
| Gemini 3.5 Flash | Gemini | $1.50 | $9.00 | 90/100 | $0.0117 | 16% cheaper |
| GPT 5.6 Terra | GPT | $2.00 | $12.00 | 90/100 | $0.0156 | 11% more |
| Gemini 3.1 Pro | Gemini | $2.00 | $12.00 | 85/100 | $0.0156 | 11% more |
| GPT 5.4 | GPT | $2.50 | $15.00 | 89/100 | $0.0195 | 39% more |
| Claude Sonnet 4.6 | Claude | $3.00 | $15.00 | 86/100 | $0.0210 | 50% more |
| GPT 5.6 Sol | GPT | $4.00 | $20.00 | 88/100 | $0.0280 | 100% more |
| Claude Opus 4.8 | Claude | $5.00 | $25.00 | 82/100 | $0.0350 | 150% more |
| GPT 5.5 | GPT | $5.00 | $30.00 | 87/100 | $0.0390 | 179% more |
| Claude Fable 5 | Claude | $10.00 | $50.00 | 85/100 | $0.0700 | 400% more |
Provider
Claude
Tier
Mid-tier
Context
200K tokens
Released
Jun 2026
Launched at $2/$10 as introductory pricing through Aug 31, 2026. Anthropic cancelled the scheduled increase to $3/$15, so this is now the standard price.
| 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 Haiku 4.5 | Fast / Budget | $1.00 | $5.00 | 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 Sonnet 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 Sonnet 5 costs change across different workload types.
Code Generation
$0.0440/call
Unit Test Generation
$0.0560/call
SQL Generation
$0.0130/call
API Generation
$0.0660/call
Code Refactoring
$0.0480/call
Code Review
$0.0300/call
PR Review
$0.0460/call
Security Review
$0.0370/call
Bug Detection
$0.0300/call
Document Summarization
$0.0300/call
PDF Summarization
$0.0450/call
Meeting Notes
$0.0360/call
Email Summarization
$0.0110/call
Chatbot
$0.0140/call
RAG Pipeline
$0.0270/call
Customer Support Bot
$0.0160/call
FAQ Bot
$0.0110/call
Data Extraction
$0.0180/call
Invoice Parsing
$0.010000/call
Resume Parsing
$0.0130/call
Chain of Thought
$0.0560/call
Legal Analysis
$0.0600/call
Math Reasoning
$0.0330/call
Financial Analysis
$0.0560/call
Content Moderation
$0.002000/call
Sentiment Analysis
$0.002000/call
Categorization
$0.003100/call
Intent Detection
$0.001600/call
Copywriting
$0.0210/call
Blog Writing
$0.0820/call
Marketing Copy
$0.0316/call
Product Descriptions
$0.0160/call
A typical json extraction call using Claude Sonnet 5 costs about $0.0140 per call. This estimate uses 3,000 input tokens and 800 output tokens at standard rates. Standard rates are $2.00 per million input tokens and $10.00 per million output tokens.
Claude Sonnet 5 scores 88 out of 100 on json extraction 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 json extraction 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 Sonnet 5 to GPT 5.6 Luna saves about 89% per API call.
Three strategies lower Claude Sonnet 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 $0.0140 to about $0.000700 per call.
Claude has 6 other models alongside Claude Sonnet 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 Haiku 4.5 at $1.00/$5.00 per million tokens (fast / budget), 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 json extraction workload prioritizes quality, cost, or speed.
Claude Sonnet 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 json extraction, typical calls use 3,000 input and 800 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.