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GPT-5.6 Luna vs Hy3

GPT-5.6 Luna and Hy3 are closely matched at 45.4 and 42.9 on the LLM Stats Score.

OpenAI · Tencent · Updated for 2026

Which is better?

GPT-5.6 Luna and Hy3 are closely matched on the overall LLM Stats Score at 45.4 and 42.9.

In the 6 individual benchmarks reported for both models, GPT-5.6 Luna wins 5; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-5.6 Luna

  • you value its reported benchmark strengths — it wins 5 of 6 exact shared results
  • you want the most recent training data — it shipped Jul 2026

Choose Hy3

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
45.4
#29
42.9
#42
44.4
#33
43.0
#40
36.5
#19
32.8
#35
31.3
#25
26.6
#42
Cost, coverage & limits
Benchmark wins
5 of 6
1 of 6
Input price
$0.20 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,050,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
GPT-5.6 Luna
Hy3
28.7#86
35.6#41
25.6#32
21.5#50
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

45 reported for GPT-5.6 Luna · 31 for Hy3

6 shared

GPT-5.6 Luna outperforms in 5 benchmarks (DeepSWE, GPQA, SWE-Bench Pro, Terminal-Bench 2.1, Toolathlon), while Hy3 is better at 1 benchmark (BrowseComp).

GPT-5.6 Luna significantly outperforms across most benchmarks.

Sun Sep 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-5.6 Luna specifies input context (1,050,000 tokens). Only GPT-5.6 Luna specifies output context (128,000 tokens).

OpenAI
GPT-5.6 Luna
Input1,050,000 tokens
Output128,000 tokens
Tencent
Hy3
Input- tokens
Output- tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-5.6 Luna supports multimodal inputs, whereas Hy3 does not.

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

GPT-5.6 Luna

Text
Images
Audio
Video

Hy3

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-5.6 Luna is licensed under a proprietary license, while Hy3 uses Apache 2.0.

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

GPT-5.6 Luna

Proprietary

Closed source

Hy3

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-5.6 Luna was released on 2026-07-09, while Hy3 was released on 2026-07-06.

GPT-5.6 Luna is 0 month newer than Hy3.

GPT-5.6 Luna

Jul 9, 2026

1 months ago

3d newer
Hy3

Jul 6, 2026

2 months ago

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Hy3'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 Hy3's cutoff date.

GPT-5.6 Luna

Feb 2026

Hy3

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-5.6 Luna and Hy3 side-by-side, then vote on the output you prefer.

GPT-5.6 Luna
✓ Preferred
Hy3
Open in Playground

FAQ

Common questions about GPT-5.6 Luna vs Hy3.

Which is better, GPT-5.6 Luna or Hy3?

GPT-5.6 Luna and Hy3 are closely matched on the LLM Stats Score at 45.4 and 42.9. GPT-5.6 Luna is made by OpenAI and Hy3 is made by Tencent. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-5.6 Luna compare to Hy3 in benchmarks?

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%. Hy3 scores DeepSearchQA: 91.0%, GPQA: 90.4%, IMO-AnswerBench: 90.0%, BrowseComp: 84.2%, MCP Atlas: 79.1%.

What are the context window sizes for GPT-5.6 Luna and Hy3?

GPT-5.6 Luna supports 1.1M tokens and Hy3 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-5.6 Luna and Hy3?

Key differences include LLM Stats Score (45.4 vs 42.9), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-5.6 Luna and Hy3?

GPT-5.6 Luna is developed by OpenAI and Hy3 is developed by Tencent.