Claude Opus 4.8 vs GPT-6 Luna
Claude Opus 4.8 and GPT-6 Luna are closely matched at 50.3 and 44.5 on the LLM Stats Score. GPT-6 Luna is 50.0x cheaper per token.
Anthropic · OpenAI · Updated for 2026
Which is better?
Claude Opus 4.8 and GPT-6 Luna are closely matched on the overall LLM Stats Score at 50.3 and 44.5.
The models split the 2 individual benchmarks reported for both models evenly.
On price, GPT-6 Luna is roughly 50.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-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
- you want predictable pricing at $5.00/M input and $25.00/M output
Choose GPT-6 Luna
- cost matters — it's about 50.0x 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 Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
27 reported for Claude Opus 4.8 · 5 for GPT-6 Luna
Claude Opus 4.8 outperforms in 1 benchmarks (FrontierCode 1.1), while GPT-6 Luna is better at 1 benchmark (DeepSWE 1.1).
Both models are evenly matched across the 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 50.0x more expensive than GPT-6 Luna ($0.10/1M tokens).
For output processing, Claude Opus 4.8 ($25.00/1M tokens) is 50.0x more expensive than GPT-6 Luna ($0.50/1M tokens).
In conclusion, Claude Opus 4.8 is more expensive than GPT-6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-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-6 Luna support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Claude Opus 4.8
GPT-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-6 Luna was released on 2026-09-22.
GPT-6 Luna is 4 months newer than Claude Opus 4.8.
May 28, 2026
3 months ago
Sep 22, 2026
0 days ago
3mo newerKnowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while Claude Opus 4.8's cutoff date is not specified.
We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without Claude Opus 4.8's cutoff date.
—
May 2026
Provider Availability
Claude Opus 4.8 is available from Anthropic, DeepInfra, Vertex AI. GPT-6 Luna is available from OpenAI.
Claude Opus 4.8
GPT-6 Luna
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude Opus 4.8 and GPT-6 Luna side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude Opus 4.8 vs GPT-6 Luna.