GPT-5.6 Luna vs Qwen3.7 Max
GPT-5.6 Luna and Qwen3.7 Max are closely matched at 45.4 and 45.4 on the LLM Stats Score. GPT-5.6 Luna is 4.2x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5.6 Luna and Qwen3.7 Max are closely matched on the overall LLM Stats Score at 45.4 and 45.4.
The models split the 2 individual benchmarks reported for both models evenly.
On price, GPT-5.6 Luna is roughly 4.2x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.6 Luna
- cost matters — it's about 4.2x 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 Jul 2026
Choose Qwen3.7 Max
- you want predictable pricing at $1.25/M input and $3.75/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
45 reported for GPT-5.6 Luna · 42 for Qwen3.7 Max
GPT-5.6 Luna outperforms in 1 benchmarks (SWE-Bench Pro), while Qwen3.7 Max is better at 1 benchmark (GPQA).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.6 Luna ($0.20/1M tokens) is 6.3x cheaper than Qwen3.7 Max ($1.25/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) is 3.1x cheaper than Qwen3.7 Max ($3.75/1M tokens).
In conclusion, Qwen3.7 Max is more expensive than GPT-5.6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.6 Luna accepts 1,050,000 input tokens compared to Qwen3.7 Max's 1,000,000 tokens. GPT-5.6 Luna can generate longer responses up to 128,000 tokens, while Qwen3.7 Max is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.6 Luna supports multimodal inputs, whereas Qwen3.7 Max 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
Qwen3.7 Max
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-5.6 Luna was released on 2026-07-09, while Qwen3.7 Max was released on 2026-05-19.
GPT-5.6 Luna is 2 months newer than Qwen3.7 Max.
Jul 9, 2026
1 months ago
1mo newerMay 19, 2026
3 months ago
Knowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Qwen3.7 Max'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 Qwen3.7 Max's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Luna is available from OpenAI. Qwen3.7 Max is available from Novita, Together.
GPT-5.6 Luna
Qwen3.7 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and Qwen3.7 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs Qwen3.7 Max.