Model Comparison

DeepSeek-V3.2-Exp vs GPT-5.6 LunaWhich is better in 2026?

GPT-5.6 Luna significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is 7.4x cheaper per token.

Verdict: DeepSeek-V3.2-Exp vs GPT-5.6 Luna — which is better?

DeepSeek-V3.2-Exp (by DeepSeek) and GPT-5.6 Luna (by OpenAI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-V3.2-Exp outperforms in 0 benchmarks, while GPT-5.6 Luna is better at 2 benchmarks (BrowseComp, GPQA). GPT-5.6 Luna significantly outperforms across most benchmarks.

On price, DeepSeek-V3.2-Exp is roughly 7.4x 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.

Choose DeepSeek-V3.2-Exp if…

  • cost matters — it's about 7.4x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose GPT-5.6 Luna if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you process long inputs — it offers a 1,050,000 token context window
  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2-Exp outperforms in 0 benchmarks, while GPT-5.6 Luna is better at 2 benchmarks (BrowseComp, GPQA).

GPT-5.6 Luna significantly outperforms across most benchmarks.

Sun Jul 26 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2-Exp costs less

For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 3.7x cheaper than GPT-5.6 Luna ($1.00/1M tokens).

For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 14.6x cheaper than GPT-5.6 Luna ($6.00/1M tokens).

In conclusion, GPT-5.6 Luna is more expensive than DeepSeek-V3.2-Exp.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sun Jul 26 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
OpenAI
GPT-5.6 Luna
Input tokens$1.00
Output tokens$6.00
Best providerOpenAI
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

GPT-5.6 Luna accepts 1,050,000 input tokens compared to DeepSeek-V3.2-Exp's 163,840 tokens. GPT-5.6 Luna can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
OpenAI
GPT-5.6 Luna
Input1,050,000 tokens
Output128,000 tokens
Sun Jul 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.6 Luna supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.

GPT-5.6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2-Exp

Text
Images
Audio
Video

GPT-5.6 Luna

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Exp is licensed under MIT, while GPT-5.6 Luna uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V3.2-Exp

MIT

Open weights

GPT-5.6 Luna

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while GPT-5.6 Luna was released on 2026-07-09.

GPT-5.6 Luna is 9 months newer than DeepSeek-V3.2-Exp.

DeepSeek-V3.2-Exp

Sep 29, 2025

9 months ago

GPT-5.6 Luna

Jul 9, 2026

2 weeks ago

9mo newer

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while DeepSeek-V3.2-Exp'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 DeepSeek-V3.2-Exp's cutoff date.

DeepSeek-V3.2-Exp

GPT-5.6 Luna

Feb 2026

Provider Availability

DeepSeek-V3.2-Exp is available from Novita. GPT-5.6 Luna is available from OpenAI.

DeepSeek-V3.2-Exp

novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $0.41/1M

GPT-5.6 Luna

openai logo
OpenAI
Input Price:Input: $1.00/1MOutput Price:Output: $6.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Less expensive input tokens
Less expensive output tokens
Has open weights
Larger context window (1,050,000 tokens)
Supports multimodal inputs
Higher BrowseComp score (83.3% vs 40.1%)
Higher GPQA score (92.3% vs 79.9%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.2-Exp and GPT-5.6 Luna side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Exp
✓ Preferred
GPT-5.6 Luna
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
OpenAI
GPT-5.6 Luna

FAQ

Common questions about DeepSeek-V3.2-Exp vs GPT-5.6 Luna.

Which is better, DeepSeek-V3.2-Exp or GPT-5.6 Luna?

GPT-5.6 Luna significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and GPT-5.6 Luna is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.2-Exp compare to GPT-5.6 Luna in benchmarks?

DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. GPT-5.6 Luna scores Connectors: 99.9%, HealthBench Consensus: 95.1%, GPQA: 92.3%, Search and Function-Calling: 89.7%, Capture-the-Flag Challenges (Internal): 85.2%.

Is DeepSeek-V3.2-Exp cheaper than GPT-5.6 Luna?

DeepSeek-V3.2-Exp is 3.7x cheaper for input tokens. DeepSeek-V3.2-Exp costs $0.27/M input and $0.41/M output via novita. GPT-5.6 Luna costs $1.00/M input and $6.00/M output via openai.

What are the context window sizes for DeepSeek-V3.2-Exp and GPT-5.6 Luna?

DeepSeek-V3.2-Exp supports 164K tokens and GPT-5.6 Luna supports 1.1M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2-Exp and GPT-5.6 Luna?

Key differences include context window (164K vs 1.1M), input pricing ($0.27 vs $1.00/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Exp and GPT-5.6 Luna?

DeepSeek-V3.2-Exp is developed by DeepSeek and GPT-5.6 Luna is developed by OpenAI.