Head-to-head comparison

GPT-6 Luna vs. GPT-5.6 Sol

Compare published benchmark results from matching versions and cohorts, API pricing, and technical specifications. Any documented test setup differences remain visible.

shared result series: 21
distinct benchmarks: 21
latest retrieval: 2026-09-29

First modelSecond model

Specifications

General specifications

Release date, availability, context window, architecture, and published parameter counts at a glance. Undisclosed details remain marked as unavailable.

Specifications for GPT-6 Luna and GPT-5.6 Sol
Attribute	GPT-6 Luna	GPT-5.6 Sol
Provider	OpenAI	OpenAI
Released	Sep 22, 2026	Jul 9, 2026
Availability	Active	Active
Model type	Proprietary	Proprietary
Parameters	Not published	Not published
Architecture	Not published	Not published
Context window	1,050,000 tokens	1,050,000 tokens
Knowledge cutoff	May 18, 2026	February 16, 2026
Technical sources	Model, Context	Model, Context, Knowledge cutoff

Pricing

API pricing compared

The table compares official standard API rates per 1M tokens, including published cache pricing. Batch, fast, priority, regional surcharges, tool calls, and cloud platform pricing are excluded.

API pricing for GPT-6 Luna and GPT-5.6 Sol
Price type	GPT-6 Luna	GPT-5.6 Sol
API input	$0.1 ≤272K / $0.2 >272K	$4 ≤272K / $8 >272K
API output	$0.5 ≤272K / $0.75 >272K	$20 ≤272K / $30 >272K
Cache read	$0.01 ≤272K / $0.02 >272K	$0.4 ≤272K / $0.8 >272K
Cache write (5 min.)	$0.13 ≤272K / $0.25 >272K	$5 ≤272K / $10 >272K
Cache write (1 hr.)	Not listed	Not listed
Price verified	09/22/2026 Source	09/22/2026 Source

GPT-6 LunaGPT-5.6 Sol

API inputUSD per 1M tokens, base tier

GPT-6 Luna$0.1

GPT-5.6 Sol$4

API outputUSD per 1M tokens, base tier

GPT-6 Luna$0.5

GPT-5.6 Sol$20

Cache readUSD per 1M tokens, base tier

GPT-6 Luna$0.01

GPT-5.6 Sol$0.4

Key to the marks:better valuebetter, but not conclusivetie

Pricing by provider

Direct developer pricing and provider endpoint tariffs routed through OpenRouter are listed separately. Prices are in USD per 1M tokens. Context-dependent direct tiers plus regional, Flex, Priority, and other OpenRouter tariffs remain individually identifiable.

Provider pricing for GPT-6 Luna and GPT-5.6 Sol
Model	Provider	Purchase route and tariff	Input per 1M tokens	Output per 1M tokens	Source
GPT-6 Luna	OpenAI	Direct from developerUp to 272,000 context tokens	$0.1	$0.5	Source09/22/2026
	OpenAI	Direct from developerAbove 272,000 context tokens	$0.2	$0.75	Source09/22/2026
	Amazon Bedrock	Via OpenRouteramazon-bedrock/us-east-1	$0.11	$0.55	Source10/07/2026
	Azure	Via OpenRouterazure	$0.1	$0.5	Source10/07/2026
	Azure	Via OpenRouterazure/eu	$0.11	$0.55	Source10/07/2026
	Azure	Via OpenRouterazure/us	$0.11	$0.55	Source10/07/2026
	OpenAI	Via OpenRouteropenai	$0.1	$0.5	Source10/07/2026
	OpenAI	Via OpenRouteropenai/fast	$0.2	$1	Source10/07/2026
	OpenAI	Via OpenRouteropenai/flex	Lowest listed price: $0.05	Lowest listed price: $0.25	Source10/07/2026
GPT-5.6 Sol	OpenAI	Direct from developerUp to 272,000 context tokens	$4	$20	Source09/22/2026
	OpenAI	Direct from developerAbove 272,000 context tokens	$8	$30	Source09/22/2026
	Amazon Bedrock	Via OpenRouteramazon-bedrock/us-east-1	$4.4	$22	Source10/07/2026
	Azure	Via OpenRouterazure	$4	$20	Source10/07/2026
	Azure	Via OpenRouterazure/eu	$4.4	$22	Source10/07/2026
	Azure	Via OpenRouterazure/us	$4.4	$22	Source10/07/2026
	OpenAI	Via OpenRouteropenai	$2	$10	Source10/07/2026
	OpenAI	Via OpenRouteropenai/fast	$4	$20	Source10/07/2026
	OpenAI	Via OpenRouteropenai/flex	Lowest listed price: $1	Lowest listed price: $5	Source10/07/2026

Performance

Shared benchmarks

Only published results with the same benchmark version, task, metric, and comparison cohort are paired. Different reasoning levels, agents, harnesses, or output limits appear directly in the table.

Capability profile from matched benchmarks

Each axis averages directly matched benchmark families. A value of 100 means the stronger value within this pair, not a universal quality score.

GPT-6 Luna

GPT-5.6 Sol

Coding: 61.8 / 99.7 (5 benchmark families)

Mathematics: 77.1 / 100 (1 benchmark family)

Finance: 91.4 / 100 (3 benchmark families)

Legal: 81.5 / 92.9 (2 benchmark families)

Agentic tasks: 85.2 / 100 (1 benchmark family)

Productivity: 86.7 / 100 (1 benchmark family)

Cybersecurity: 99.9 / 100 (1 benchmark family)

Health: 99.1 / 99.2 (2 benchmark families)

21 matched rows from 20 benchmark families were considered. The radar shows 8 of 11 comparable categories.

GPT-6 LunaGPT-5.6 Sol

BioMysteryBenchOverall. Higher is better. No documented setup difference

GPT-6 Luna61.481 %

GPT-5.6 Sol71.111 %

Code MigrationOverall. Higher is better. No documented setup difference

GPT-6 Luna42.554 %

GPT-5.6 Sol52.916 %

CyberBench v1.1Overall. Higher is better. No documented setup difference

GPT-6 Luna76.25 %

GPT-5.6 Sol76.31 %

EMBOverall. Higher is better. No documented setup difference

GPT-6 Luna68.515 %

GPT-5.6 Sol72.339 %

Finance Agent (v2)Overall. Higher is better. No documented setup difference

GPT-6 Luna49.873 %

GPT-5.6 Sol53.756 %

Harvey's Legal Agent BenchmarkOverall · Task fully resolved. Higher is better. No documented setup difference

GPT-6 Luna2.917 %

GPT-5.6 Sol2.5 %

IOIOverall. Higher is better. No documented setup difference

GPT-6 Luna55.556 %

GPT-5.6 Sol91.167 %

Legal Research BenchOverall · All-pass. Higher is better. No documented setup difference

GPT-6 Luna30.288 %

GPT-5.6 Sol48.077 %

MedCodeOverall. Higher is better. No documented setup difference

GPT-6 Luna44.685 %

GPT-5.6 Sol43.974 %

MedScribeOverall. Higher is better. No documented setup difference

GPT-6 Luna83.71 %

GPT-5.6 Sol85.233 %

MysteryMechanismOverall. Higher is better. No documented setup difference

GPT-6 Luna19.369 %

GPT-5.6 Sol33.333 %

ProgramBenchOverall. Higher is better. No documented setup difference

GPT-6 Luna0.5 %

GPT-5.6 Sol1.5 %

Key to the marks:better valuebetter, but not conclusivetie

Benchmark scores for GPT-6 Luna and GPT-5.6 Sol
Benchmark and task	GPT-6 Luna	GPT-5.6 Sol	Source
BioMysteryBenchOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is betterSettings: Harness: Terminus 2	61.481 %	Winner71.111 %	Vals AI Source details Data as of: 09/27/2026
Code MigrationOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	42.554 %	Winner52.916 %	Vals AI Source details Data as of: 09/27/2026
CyberBench v1.1Overall Test details No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is better	76.25 %	Winner76.31 %	Vals AI Source details Data as of: 09/27/2026
EMBOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	68.515 %	Winner72.339 %	Vals AI Source details Data as of: 09/27/2026
Finance Agent (v2)Overall Test details No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better	49.873 %	Winner53.756 %	Vals AI Source details Data as of: 09/27/2026
Harvey's Legal Agent BenchmarkOverall · Task fully resolved Test details No documented difference in the test setupVersion: 1Metric: task resolution rateScoring: Higher is better	Winner2.917 %	2.5 %	Vals AI Source details Data as of: 09/27/2026
IOIOverall Test details No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better	55.556 %	Winner91.167 %	Vals AI Source details Data as of: 09/27/2026
Legal Research BenchOverall · All-pass Test details No documented difference in the test setupVersion: 1Metric: all-pass rateScoring: Higher is better	30.288 %	Winner48.077 %	Vals AI Source details Data as of: 09/27/2026
MedCodeOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	Winner44.685 %	43.974 %	Vals AI Source details Data as of: 09/26/2026
MedScribeOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	83.71 %	Winner85.233 %	Vals AI Source details Data as of: 09/26/2026
MysteryMechanismOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	19.369 %	Winner33.333 %	Vals AI Source details Data as of: 09/27/2026
ProgramBenchOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	0.5 %	Winner1.5 %	Vals AI Source details Data as of: 09/27/2026
ProofBenchOverall Test details No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is better	64 %	Winner83 %	Vals AI Source details Data as of: 09/28/2026
Public Benefits Bench v1.1Overall Test details No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is better	57.645 %	Winner66.509 %	Vals AI Source details Data as of: 09/27/2026
SAGEOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	48.091 %	Winner52.563 %	Vals AI Source details Data as of: 09/26/2026
Tax Agent BenchOverall Test details No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better	58.864 %	Winner67.955 %	Vals AI Source details Data as of: 09/27/2026
Terminal-Bench 2.1Overall Test details No documented difference in the test setupVersion: 2.1Metric: accuracyScoring: Higher is better	73.034 %	Winner85.768 %	Vals AI Source details Data as of: 09/27/2026
Terminal-Bench 4.0Overall Test details No documented difference in the test setupVersion: 4.0Metric: accuracyScoring: Higher is better	9.596 %	Winner27.778 %	Vals AI Source details Data as of: 09/27/2026
Terminal-Bench ScienceOverall Test details No documented difference in the test setupVersion: 0.1Metric: accuracyScoring: Higher is better	10 %	Winner12.857 %	Vals AI Source details Data as of: 09/27/2026
Vals IndexOverall Test details No documented difference in the test setupVersion: 2Metric: weighted index scoreScoring: Higher is better	58.45 %	Winner63.709 %	Vals AI Source details Data as of: 09/27/2026
Vibe Code Bench v1.1Overall Test details No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is betterSettings: Harness: OpenHands	Winner81.649 %	80.495 %	Vals AI Source details Data as of: 09/27/2026
Key to the marks:better valuebetter, but not conclusivetie

Our model tests

Our tests

Compare how the models respond to the same prompt. Each test shows the latest attempt, with no subsequent fixes to the generated code. Earlier runs remain available in the test details. These results do not contribute to an overall score.

Pelican on a bicycle

A community classic for free-form SVG drawing.

GPT-6 Luna

Reasoning (requested): high

Current attempt

Run date: 1 Oct 2026
API provider: openrouter
Requested API model: openai/gpt-6-luna
API model reported in response: openai/gpt-6-luna
Reasoning setting: high
Pinned endpoint: OpenAI | openai/gpt-6-luna-20260922
Temperature: Provider default
Token limit including reasoning: 8,192 tokens
Test protocol: community-visual-tests-v1
Technical checks: Passed, not a quality rating
Response time: 46.7 s

Visually reviewed. This individual test does not establish overall model quality.

GPT-5.6 Sol

Reasoning (requested): high

Current attempt

Run date: 1 Oct 2026
API provider: openrouter
Requested API model: openai/gpt-5.6-sol
API model reported in response: openai/gpt-5.6-sol
Reasoning setting: high
Pinned endpoint: OpenAI | openai/gpt-5.6-sol-20260709
Temperature: Provider default
Token limit including reasoning: 8,192 tokens
Test protocol: community-visual-tests-v1
Technical checks: Passed, not a quality rating
Response time: 58.7 s

Visually reviewed. This individual test does not establish overall model quality.

Earlier attempts (1)

7 Sept 2026API request failedReasoning setting: high

Prompt and test conditions

Generate an SVG of a pelican riding a bicycle

Token limit including reasoning: 8,192 tokens

Task origin (Simon Willison)

How to read this comparison

Winning one benchmark is not an overall verdict

Your workload, budget, and required context length matter most. A coding benchmark says little about visual understanding or agent performance.

The standard price table uses direct developer rates. The provider comparison labels OpenRouter endpoints, regions, and special tariffs separately.

Every result links to its measurement source and retrieval date. Labels distinguish vendor reports, official benchmark leaderboards, and independent evaluations. Disputed or archived results are excluded.

More matchups

Compare GPT-6 Luna and GPT-5.6 Sol with other leading models using the same data and benchmark logic.

View the complete LLM comparison