Claude Opus 4.8 vs GPT-5.6 Luna
Claude Opus 4.8 leads the LLM Stats Score 50.8 to 45.1. GPT-5.6 Luna is 22.2x cheaper per token.
Anthropic · OpenAI · Updated for 2026
Which is better?
Claude Opus 4.8 leads the overall LLM Stats Score 50.8 to 45.1, ranking #15 overall.
In the 9 individual benchmarks reported for both models, Claude Opus 4.8 wins 7; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-5.6 Luna is roughly 22.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.6 Luna also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Claude Opus 4.8
- overall performance matters — it scores 50.8 and ranks #15 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 7 of 9 exact shared results
Choose GPT-5.6 Luna
- cost matters — it's about 22.2x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Jul 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
1 more shared indexes
Individual benchmarks
27 reported for Claude Opus 4.8 · 45 for GPT-5.6 Luna
Claude Opus 4.8 outperforms in 7 benchmarks (BrowseComp, FrontierCode 1.1, GPQA, HealthBench Professional, SWE-Bench Pro, Terminal-Bench 4.0, Toolathlon), while GPT-5.6 Luna is better at 2 benchmarks (DeepSWE 1.1, Graphwalks BFS >128k).
Claude Opus 4.8 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, Claude Opus 4.8 ($5.00/1M tokens) is 25.0x more expensive than GPT-5.6 Luna ($0.20/1M tokens).
For output processing, Claude Opus 4.8 ($25.00/1M tokens) is 20.8x more expensive than GPT-5.6 Luna ($1.20/1M tokens).
In conclusion, Claude Opus 4.8 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
GPT-5.6 Luna accepts 1,050,000 input tokens compared to Claude Opus 4.8's 1,000,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Claude Opus 4.8 and GPT-5.6 Luna support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Claude Opus 4.8
GPT-5.6 Luna
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
Claude Opus 4.8 was released on 2026-05-28, while GPT-5.6 Luna was released on 2026-07-09.
GPT-5.6 Luna is 1 month newer than Claude Opus 4.8.
May 28, 2026
3 months ago
Jul 9, 2026
2 months ago
1mo newerKnowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Claude Opus 4.8's cutoff date is not specified.
We can confirm GPT-5.6 Luna's training data extends to 2026-02-16, but cannot make a direct comparison without Claude Opus 4.8's cutoff date.
—
Feb 2026
Provider Availability
Claude Opus 4.8 is available from Anthropic, DeepInfra, Vertex AI. GPT-5.6 Luna is available from OpenAI.
Claude Opus 4.8
GPT-5.6 Luna
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude Opus 4.8 and GPT-5.6 Luna side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude Opus 4.8 vs GPT-5.6 Luna.