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GPT-5.6 Luna vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 46.5.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 50.5 to 46.5, ranking #14 overall.

In the 6 individual benchmarks reported for both models, GPT-5.6 Luna wins 4; 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 4 of 6 exact shared results

Choose Qwen3.8-Flash-Next

  • overall performance matters — it scores 50.5 and ranks #14 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Aug 2026
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

GPT-5.6 Luna
OpenAI
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
46.5
#21
50.5
#14
Reasoning
45.6
#25
50.6
#12
Coding
39.9
#13
38.4
#19
Agents
33.7
#18
37.2
#12
Cost, coverage & limits
Benchmark wins
4 of 6
2 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

4 shared
Index
GPT-5.6 Luna
Qwen3.8-Flash-Next
Math
29.1#81
33.3#50
Vision
25.3#42
34.6#11
Tool use
27.6#19
32.3#8
Multimodal
25.7#37
35.3#8
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

44 reported for GPT-5.6 Luna · 22 for Qwen3.8-Flash-Next

6 shared

GPT-5.6 Luna outperforms in 4 benchmarks (DeepSWE 1.1, GPQA, OSWorld 2.0, SWE-Bench Pro), while Qwen3.8-Flash-Next is better at 2 benchmarks (Agents' Last Exam, Toolathlon).

GPT-5.6 Luna shows notably better performance in the majority of benchmarks.

Fri Aug 28 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
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-5.6 Luna and Qwen3.8-Flash-Next support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GPT-5.6 Luna

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-5.6 Luna is licensed under a proprietary license, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.

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

GPT-5.6 Luna

Proprietary

Closed source

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

GPT-5.6 Luna was released on 2026-07-09, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 2 months newer than GPT-5.6 Luna.

GPT-5.6 Luna

Jul 9, 2026

1 months ago

Qwen3.8-Flash-Next

Aug 26, 2026

2 days ago

1mo newer

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Qwen3.8-Flash-Next'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 Qwen3.8-Flash-Next's cutoff date.

GPT-5.6 Luna

Feb 2026

Qwen3.8-Flash-Next

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GPT-5.6 Luna and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

GPT-5.6 Luna
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about GPT-5.6 Luna vs Qwen3.8-Flash-Next.

Which is better, GPT-5.6 Luna or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 46.5. GPT-5.6 Luna is made by OpenAI and Qwen3.8-Flash-Next is made by Alibaba Cloud / Qwen Team. 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 Qwen3.8-Flash-Next 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%. Qwen3.8-Flash-Next scores MathVision: 95.7%, LiveCodeBench v6: 91.9%, GPQA: 91.7%, CharXiv-R: 90.6%, RealWorldQA: 88.5%.

What are the context window sizes for GPT-5.6 Luna and Qwen3.8-Flash-Next?

GPT-5.6 Luna supports 1.1M tokens and Qwen3.8-Flash-Next 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 Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (46.5 vs 50.5), licensing (Proprietary vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-5.6 Luna and Qwen3.8-Flash-Next?

GPT-5.6 Luna is developed by OpenAI and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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