DeepSeek-V3.2-Speciale vs GPT-6 Luna
GPT-6 Luna leads the LLM Stats Score 44.5 to 33.9. GPT-6 Luna is 1.6x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 44.5 to 33.9, ranking #41 overall.
On price, GPT-6 Luna is roughly 1.6x 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 DeepSeek-V3.2-Speciale
- you need open weights you can self-host or fine-tune
Choose GPT-6 Luna
- overall performance matters — it scores 44.5 and ranks #41 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 1.6x 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
8 reported for DeepSeek-V3.2-Speciale · 5 for GPT-6 Luna
DeepSeek-V3.2-Speciale and GPT-6 Lunadon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2-Speciale ($0.28/1M tokens) is 2.8x more expensive than GPT-6 Luna ($0.10/1M tokens).
For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 1.2x cheaper than GPT-6 Luna ($0.50/1M tokens).
In conclusion, DeepSeek-V3.2-Speciale 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 DeepSeek-V3.2-Speciale's 131,072 tokens. DeepSeek-V3.2-Speciale can generate longer responses up to 131,072 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Luna supports multimodal inputs, whereas DeepSeek-V3.2-Speciale does not.
GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Speciale
GPT-6 Luna
License
Usage and distribution terms
DeepSeek-V3.2-Speciale is licensed under MIT, while GPT-6 Luna uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3.2-Speciale was released on 2025-12-01, while GPT-6 Luna was released on 2026-09-22.
GPT-6 Luna is 10 months newer than DeepSeek-V3.2-Speciale.
Dec 1, 2025
9 months ago
Sep 22, 2026
0 days ago
9mo newerKnowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while DeepSeek-V3.2-Speciale'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 DeepSeek-V3.2-Speciale's cutoff date.
—
May 2026
Provider Availability
DeepSeek-V3.2-Speciale is available from DeepSeek. GPT-6 Luna is available from OpenAI.
DeepSeek-V3.2-Speciale
GPT-6 Luna
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Speciale and GPT-6 Luna side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Speciale vs GPT-6 Luna.