GPT-5.6 Luna vs Qwen3.8 Max
Qwen3.8 Max leads the LLM Stats Score 51.9 to 45.1. GPT-5.6 Luna is 5.5x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.8 Max leads the overall LLM Stats Score 51.9 to 45.1, ranking #11 overall.
In the 10 individual benchmarks reported for both models, Qwen3.8 Max wins 9; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-5.6 Luna is roughly 5.5x 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 5.5x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
Choose Qwen3.8 Max
- overall performance matters — it scores 51.9 and ranks #11 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 9 of 10 exact shared results
- 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
45 reported for GPT-5.6 Luna · 42 for Qwen3.8 Max
GPT-5.6 Luna outperforms in 1 benchmarks (DeepSWE 1.1), while Qwen3.8 Max is better at 9 benchmarks (Agents' Last Exam, AutomationBench, GPQA, HealthBench, MMMU-Pro, MRCR v2 (8-needle), SWE-Bench Pro, Terminal-Bench 2.1, Toolathlon).
Qwen3.8 Max significantly outperforms across most 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 8.2x cheaper than Qwen3.8 Max ($1.65/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) is 4.1x cheaper than Qwen3.8 Max ($4.95/1M tokens).
In conclusion, Qwen3.8 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 Qwen3.8 Max's 256,000 tokens. Qwen3.8 Max can generate longer responses up to 256,000 tokens, while GPT-5.6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.6 Luna and Qwen3.8 Max support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.6 Luna
Qwen3.8 Max
License
Usage and distribution terms
GPT-5.6 Luna is licensed under a proprietary license, while Qwen3.8 Max uses Qwen3.8-Max License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Qwen3.8-Max License
Open weights
Release Timeline
When each model was launched
GPT-5.6 Luna was released on 2026-07-09, while Qwen3.8 Max was released on 2026-08-02.
Qwen3.8 Max is 1 month newer than GPT-5.6 Luna.
Jul 9, 2026
2 months ago
Aug 2, 2026
1 months ago
3w newerKnowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Qwen3.8 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 Qwen3.8 Max's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Luna is available from OpenAI. Qwen3.8 Max is available from DeepInfra, Fireworks, Novita, Together.
GPT-5.6 Luna
Qwen3.8 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and Qwen3.8 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs Qwen3.8 Max.