tokevenGPT · Flagship · 1,000K context window
GPT 5.6 Sol pricing for unit test generation
$0.1650 per call at 3,000 input / 5,000 output tokens.
Per call
$0.1650
10K calls/mo
$1,650
Cache savings
90% off input
Batch savings
50% off all
Calculate your GPT 5.6 Sol costs
Adjust token counts, volume, and discount toggles to model your unit test generation spend. Pricing updated weekly.
Configure your usage
Estimated cost
Quick start
Call GPT 5.6 Sol with the OpenAI Python SDK:
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gpt-5.6-sol",
max_tokens=5000,
messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.1650 per call at standard rates
# Input: $5.00/MTok
# Output: $30.00/MTokHow GPT 5.6 Sol compares on cost
Per-call cost for all models scoring 50+ on unit test generation benchmarks. Hover for details.
Cheapest viable option: Claude Sonnet 5 at $0.0560/call (66% less, 93/100 quality).
Complete GPT 5.6 Sol pricing breakdown
Standard token rates
| Direction | $/MTok | Tokens per call |
|---|---|---|
| Input | $5.00 | 3,000 |
| Output | $30.00 | 5,000 |
Prompt caching: 90% off input tokens
Caching drops input cost from $5.00 to $0.50/MTok. For repeated system prompts, that saves $0.0135 per call.
Batch API: 50% off all tokens
Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.
Monthly cost projections
| Monthly volume | Cost per call | Standard monthly | Cached monthly | You save with caching |
|---|---|---|---|---|
| 10,000 calls | $0.1650 | $1,650 | $1,515 | $135 |
| 50,000 calls | $0.1650 | $8,250 | $7,575 | $675 |
| 100,000 calls | $0.1650 | $16,500 | $15,150 | $1,350 |
| 500,000 calls | $0.1650 | $82,500 | $75,750 | $6,750 |
| 1,000,000 calls | $0.1650 | $165,000 | $151,500 | $13,500 |
GPT 5.6 Sol quality benchmarks for unit test generation
Use GPT 5.6 Sol for unit test generation
Scores 94/100 (rank #1 of 14). Strong pick for production unit test generation workloads.
Top-ranked: Claude Fable 5 (96/100) at $0.2800/call
Performance across all task types
GPT 5.6 Sol scores by task type. Unit Test Generation highlighted.
| Task type | Confidence score | Rank out of 14 |
|---|---|---|
| Reasoning | 96/100 | #1 |
| Code Generation(current page) | 94/100 | #1 |
| Code Review | 92/100 | #2 |
| Creative Writing | 92/100 | #2 |
| Q&A | 91/100 | #1 |
| Summarization | 90/100 | #2 |
| Extraction | 88/100 | #3 |
| Classification | 86/100 | #3 |
Alternative models for unit test generation
8 models score 80+ on unit test generation benchmarks, sorted by input rate. Cheapest: Claude Sonnet 5 (66% less, 93/100 quality).
| Model | Provider | Input $/MTok | Output $/MTok | Quality | Per call | vs GPT |
|---|---|---|---|---|---|---|
| Claude Sonnet 5 | Claude | $2.00 | $10.00 | 93/100 | $0.0560 | 66% cheaper |
| Gemini 3.1 Pro | Gemini | $2.00 | $12.00 | 86/100 | $0.0660 | 60% cheaper |
| GPT 5.4 | GPT | $2.50 | $15.00 | 84/100 | $0.0825 | 50% cheaper |
| GPT 5.6 Terra | GPT | $2.50 | $15.00 | 86/100 | $0.0825 | 50% cheaper |
| Claude Sonnet 4.6 | Claude | $3.00 | $15.00 | 92/100 | $0.0840 | 49% cheaper |
| Claude Opus 4.8 | Claude | $5.00 | $25.00 | 95/100 | $0.1400 | 15% cheaper |
| GPT 5.5 | GPT | $5.00 | $30.00 | 91/100 | $0.1650 | same cost |
| Claude Fable 5 | Claude | $10.00 | $50.00 | 96/100 | $0.2800 | 70% more |
About GPT 5.6 Sol
Provider
GPT
Tier
Flagship
Context
1,000K tokens
Released
Jul 2026
Other models from GPT
| Model | Tier | Input $/MTok | Output $/MTok | Context |
|---|---|---|---|---|
| GPT 5.5 | Flagship | $5.00 | $30.00 | 128K |
| GPT 5.4 | Mid-tier | $2.50 | $15.00 | 128K |
| GPT 5.6 Terra | Mid-tier | $2.50 | $15.00 | 1,000K |
| GPT 5.6 Luna | Fast / Budget | $1.00 | $6.00 | 1,000K |
You can compare GPT 5.6 Sol 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.
GPT 5.6 Sol pricing for other use cases
See how GPT 5.6 Sol costs change across different workload types.
Code Generation
$0.1300/call
SQL Generation
$0.0375/call
API Generation
$0.1950/call
Code Refactoring
$0.1400/call
Code Review
$0.0850/call
PR Review
$0.1300/call
Security Review
$0.1050/call
Bug Detection
$0.0850/call
Document Summarization
$0.0800/call
PDF Summarization
$0.1200/call
Meeting Notes
$0.1000/call
Email Summarization
$0.0300/call
Chatbot
$0.0400/call
RAG Pipeline
$0.0750/call
Customer Support Bot
$0.0450/call
FAQ Bot
$0.0315/call
Data Extraction
$0.0500/call
JSON Extraction
$0.0390/call
Invoice Parsing
$0.0280/call
Resume Parsing
$0.0365/call
Chain of Thought
$0.1650/call
Legal Analysis
$0.1700/call
Math Reasoning
$0.0975/call
Financial Analysis
$0.1600/call
Content Moderation
$0.005500/call
Sentiment Analysis
$0.005500/call
Categorization
$0.008500/call
Intent Detection
$0.004500/call
Copywriting
$0.0625/call
Blog Writing
$0.2450/call
Marketing Copy
$0.0940/call
Product Descriptions
$0.0475/call
Related pages
Frequently asked questions
How much does GPT 5.6 Sol cost for unit test generation per API call?
$0.1650 per call at 3,000 input / 5,000 output tokens.
Is GPT 5.6 Sol the best model for unit test generation?
Scores 94/100, rank #1 of 14 models. Top-ranked: Claude Fable 5 at 96/100.
What is the cheapest model for unit test generation with good quality?
Claude Sonnet 5 scores 93/100 quality at $2.00/$10.00 per MTok. That is 66% less than GPT 5.6 Sol per call.
How can I reduce my GPT 5.6 Sol costs for unit test generation?
Three strategies: prompt caching (90% off input), batch API (50% off all tokens), prompt optimization. Combined: $0.1650 drops to about $0.008250 per call.
How does GPT 5.6 Sol pricing compare to other GPT models?
GPT also offers: GPT 5.5 at $5.00/$30.00, GPT 5.4 at $2.50/$15.00, GPT 5.6 Terra at $2.50/$15.00, GPT 5.6 Luna at $1.00/$6.00.
What context window does GPT 5.6 Sol support?
1,000K tokens total. Typical unit test generation calls use 3,000 plus 5,000 tokens, well within limits.
Track what you spend on AI
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.