GPT-5.6 Luna vs GPT-5.6 Terra
GPT-5.6 Terra leads the LLM Stats Score 50.8 to 45.1. GPT-5.6 Luna is 10.0x cheaper per token.
OpenAI · OpenAI · Updated for 2026
Which is better?
GPT-5.6 Terra leads the overall LLM Stats Score 50.8 to 45.1, ranking #16 overall.
In the 45 individual benchmarks reported for both models, GPT-5.6 Terra wins 42; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-5.6 Luna is roughly 10.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.6 Luna
- cost matters — it's about 10.0x cheaper per token
Choose GPT-5.6 Terra
- overall performance matters — it scores 50.8 and ranks #16 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 42 of 45 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
45 reported for GPT-5.6 Luna · 45 for GPT-5.6 Terra
GPT-5.6 Luna outperforms in 3 benchmarks (BenchCAD, Graphwalks BFS >128k, Toolathlon), while GPT-5.6 Terra is better at 41 benchmarks (Agents' Last Exam, ARC-AGI-3, Artificial Analysis, AutomationBench, BenchCAD (with Python tool), Big Finance Bench, BrowseComp, Capture-the-Flag Challenges (Internal), Connectors, DeepSWE, DeepSWE 1.1, ExploitBench, ExploitGym, FrontierCode 1.1, FrontierMath, FrontierMath Tier 4 (v2), GDP.pdf, GeneBench-Pro, GPQA, Graphwalks BFS 1M, HealthBench, HealthBench Hard, HealthBench Professional, Internal Research Debugging Evaluation, KernelGen 1P, LifeSciBench, Management Consulting Tasks (Internal), MedChemBench (Internal), MMMU-Pro, MMMU-Pro (with tools), MRCR v2 (8-needle), MRCR v2 (8-needle, 512K-1M), NanoGPT, OSWorld 2.0, PostTrainBench Lite, RSI Index, Search and Function-Calling, SEC-bench Pro, SWE-Bench Pro, Terminal-Bench 2.1, Terminal-Bench 4.0).
GPT-5.6 Terra significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.6 Luna ($0.20/1M tokens) is 10.0x cheaper than GPT-5.6 Terra ($2.00/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) is 10.0x cheaper than GPT-5.6 Terra ($12.00/1M tokens).
In conclusion, GPT-5.6 Terra is more expensive than GPT-5.6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,050,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.6 Luna and GPT-5.6 Terra support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.6 Luna
GPT-5.6 Terra
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Both models were released on 2026-07-09.
They likely represent similar generations of model development.
Jul 9, 2026
2 months ago
Jul 9, 2026
2 months ago
Knowledge Cutoff
When training data ends
Both models have the same knowledge cutoff date of 2026-02-16.
They should have similar awareness of historical events and information up to this date.
Feb 2026
Feb 2026
Provider Availability
GPT-5.6 Luna is available from OpenAI. GPT-5.6 Terra is available from OpenAI.
GPT-5.6 Luna
GPT-5.6 Terra
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and GPT-5.6 Terra side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs GPT-5.6 Terra.