Model Comparison

GPT-5.6 Luna vs Qwen3-235B-A22B-Thinking-2507Which is better in 2026?

GPT-5.6 Luna significantly outperforms across most benchmarks. Qwen3-235B-A22B-Thinking-2507 is 2.3x cheaper per token.

Verdict: GPT-5.6 Luna vs Qwen3-235B-A22B-Thinking-2507 — which is better?

GPT-5.6 Luna (by OpenAI) and Qwen3-235B-A22B-Thinking-2507 (by Alibaba Cloud / Qwen Team) 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.

GPT-5.6 Luna outperforms in 1 benchmarks (GPQA), while Qwen3-235B-A22B-Thinking-2507 is better at 0 benchmarks. GPT-5.6 Luna significantly outperforms across most benchmarks.

On price, Qwen3-235B-A22B-Thinking-2507 is roughly 2.3x 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 GPT-5.6 Luna if…

  • you want the strongest raw capability — it leads on 1 of 1 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

Choose Qwen3-235B-A22B-Thinking-2507 if…

  • cost matters — it's about 2.3x cheaper per token
  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GPT-5.6 Luna outperforms in 1 benchmarks (GPQA), while Qwen3-235B-A22B-Thinking-2507 is better at 0 benchmarks.

GPT-5.6 Luna significantly outperforms across most benchmarks.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-235B-A22B-Thinking-2507 costs less

For input processing, GPT-5.6 Luna ($1.00/1M tokens) is 3.3x more expensive than Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens).

For output processing, GPT-5.6 Luna ($6.00/1M tokens) is 2.0x more expensive than Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens).

In conclusion, GPT-5.6 Luna is more expensive than Qwen3-235B-A22B-Thinking-2507.*

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

Lowest available price from all providers
Tue Jul 21 2026 • llm-stats.com
OpenAI
GPT-5.6 Luna
Input tokens$1.00
Output tokens$6.00
Best providerOpenAI
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input tokens$0.30
Output tokens$3.00
Best providerFireworks
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 Qwen3-235B-A22B-Thinking-2507's 262,144 tokens. Qwen3-235B-A22B-Thinking-2507 can generate longer responses up to 131,072 tokens, while GPT-5.6 Luna is limited to 128,000 tokens.

OpenAI
GPT-5.6 Luna
Input1,050,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.6 Luna supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 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

Qwen3-235B-A22B-Thinking-2507

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-5.6 Luna is licensed under a proprietary license, while Qwen3-235B-A22B-Thinking-2507 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

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-5.6 Luna was released on 2026-07-09, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

GPT-5.6 Luna is 12 months newer than Qwen3-235B-A22B-Thinking-2507.

GPT-5.6 Luna

Jul 9, 2026

1 weeks ago

11mo newer
Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

12 months ago

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Qwen3-235B-A22B-Thinking-2507'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 Qwen3-235B-A22B-Thinking-2507's cutoff date.

GPT-5.6 Luna

Feb 2026

Qwen3-235B-A22B-Thinking-2507

—

Provider Availability

GPT-5.6 Luna is available from OpenAI. Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita.

GPT-5.6 Luna

openai logo
OpenAI
Input Price:Input: $1.00/1MOutput Price:Output: $6.00/1M

Qwen3-235B-A22B-Thinking-2507

fireworks logo
Fireworks
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

OpenAI
Larger context window (1,050,000 tokens)
Supports multimodal inputs
Higher GPQA score (92.3% vs 81.1%)
Alibaba Cloud / Qwen Team
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GPT-5.6 Luna and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.

GPT-5.6 Luna
✓ Preferred
Qwen3-235B-A22B-Thinking-2507
Open in Playground
AI Model Comparison Table
Feature
OpenAI
GPT-5.6 Luna
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507

FAQ

Common questions about GPT-5.6 Luna vs Qwen3-235B-A22B-Thinking-2507.

Which is better, GPT-5.6 Luna or Qwen3-235B-A22B-Thinking-2507?

GPT-5.6 Luna significantly outperforms across most benchmarks. GPT-5.6 Luna is made by OpenAI and Qwen3-235B-A22B-Thinking-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-5.6 Luna compare to Qwen3-235B-A22B-Thinking-2507 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%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.

Is GPT-5.6 Luna cheaper than Qwen3-235B-A22B-Thinking-2507?

Qwen3-235B-A22B-Thinking-2507 is 3.3x cheaper for input tokens. GPT-5.6 Luna costs $1.00/M input and $6.00/M output via openai. Qwen3-235B-A22B-Thinking-2507 costs $0.30/M input and $3.00/M output via fireworks.

What are the context window sizes for GPT-5.6 Luna and Qwen3-235B-A22B-Thinking-2507?

GPT-5.6 Luna supports 1.1M tokens and Qwen3-235B-A22B-Thinking-2507 supports 262K 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 Qwen3-235B-A22B-Thinking-2507?

Key differences include context window (1.1M vs 262K), input pricing ($1.00 vs $0.30/M), 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 Qwen3-235B-A22B-Thinking-2507?

GPT-5.6 Luna is developed by OpenAI and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.

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