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OpenAI: GPT-5.6 Luna Coding Benchmark

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series. It is suited for high-volume, latency-sensitive tasks such as chat, classification, and lightweight agentic workflows, providing capable reasoning for...

Context1,050,000tokens
Max Output128,000tokens
Inputmodalities
Price$0.20/1M input

Try OpenAI: GPT-5.6 Luna in Kilo Code

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Coding Performance

Coding benchmarks and performance metrics for development tasks

OpenClaw Benchmarks

PinchBench measures how OpenAI: GPT-5.6 Luna performs on real OpenClaw agent tasks: multi-step execution, tool use, recovery, latency, and cost.

Average score

88.7%

#8 of 50 official models

Average time

170m 28s

5 runs · per OpenClaw task

Average cost

$17.141

Per benchmark run

Category breakdown

Best verified PinchBench v2 run by OpenClaw task family.

Memory100.0% · 2/2 cleared
Log Analysis97.4% · 14/30 cleared
Analysis95.4% · 5/12 cleared
Csv Analysis92.8% · 3/26 cleared

Top task results

Highest-scoring benchmark tasks from the same submission.

Analysis
Access Control Log Anomaly Detection
100.0%
Productivity
Calendar Event Creation
100.0%
Skills
Create Project Structure
100.0%
Coding
Dockerfile Optimization
100.0%
Research
Executive Lookup
100.0%
Analysis
Financial Ratio Calculation
100.0%

Autonomous task execution

OpenAI: GPT-5.6 Luna shows strong average success across OpenClaw-style benchmark runs, useful for recurring research, browser, and file-based automations.

Tool use and recovery

PinchBench tasks stress multi-step planning, tool calls, and judge-verified completion rather than single prompt coding snippets.

Agent workflow fit

Its deliberate average runtime and premium run cost help set expectations for long-running agents and production workflows.

Agentic benchmarks from the PinchBench Leaderboard

Real-World Usage

Real-world usage statistics from the Kilo Code community

No usage data available for this model yet.

No ranking data available for this model yet.

Real-world metrics from the Kilo Code Leaderboard

Pricing

Cost per 1 million tokens

Input Tokens
$0.20
per 1M tokens
Output Tokens
$1.20
per 1M tokens

Example Cost

Analyzing a 10,000 line codebase (≈40k input tokens, 10k output tokens) costs approximately $0.0200

Coding Capabilities

Features and parameters relevant to coding tasks

Coding Features

Function Calling
Can call external functions/APIs
Tool Choice
Control over function selection
Structured Outputs
JSON schema validation
Reasoning Tokens
Extended thinking for complex problems

Pricing details from OpenRouter

Technical Details

Architecture and implementation specifications

Specifications
Model ID
openai/gpt-5.6-luna
Created
July 9, 2026
Tokenizer
GPT
Input Modalities
FileImageText
Context Window
1,050,000 tokens
Max Completion Tokens
128,000 tokens
Input Price
$0.20 per 1M tokens
Output Price
$1.20 per 1M tokens
Cache Read Price
$0.02 per 1M tokens
Cache Write Price
$0.25 per 1M tokens
Content Moderation
Enabled

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