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  5. GPT-5.6 Luna ProvsQwen3.7 Flash
Updated Jul 2026

GPT-5.6 Luna ProvsQwen3.7 Flash

Qwen3.7 Flash is cheaper than GPT-5.6 Luna Pro at $0.03/M vs $1/M input tokens.

GPT-5.6 Luna Pro and Qwen3.7 Flash compared across 13 shared prompts
SpecGPT-5.6 Luna ProQwen3.7 Flash
Input price$1/M tokens$0.03/M tokens
Output price$6/M tokens$0.13/M tokens
Context window1.1M tokens1.0M tokens
WeightsClosedClosed
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 prompts both answered. Formatting stripped, words untouched.

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

GPT-5.6 Luna Pro126 words
Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…
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Qwen3.7 Flash332 words
🥔 Golden Crunch Smash-Roasted Potatoes A crowd-pleasing side dish that delivers maximum crispiness with minimal effort. By boiling then smashing the potatoes before roasting, you create a shatteringly crisp crust while keeping the inside fluffy. This recipe relies on just seven pantry staples for perfect flavor.
Read the full answer

Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

GPT-5.6 Luna Pro2,250 words
I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.
Read the full answer
Qwen3.7 Flash1,240 words
This is a high-stakes crisis requiring decisive, legally compliant, ethically grounded, and strategically coordinated action. Below is a structured, hour-by-hour executive playbook for the next 48 hours, followed by cross-cutting rationale addressing your specified dimensions.
Read the full answer

Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

GPT-5.6 Luna Pro781 words
“94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.
Read the full answer
Qwen3.7 Flash776 words
Here are the three weakest claims in the pitch deck, along with why they raise red flags for sophisticated investors and how to concretely improve them. Weak Claim 1: Solution Slide "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

GPT-5.6 Luna Pro3,077 words
A transistor invented in 1920 would not automatically produce a 1980-level computer in 1930. The key question is whether the invention also brings forward reliable semiconductor purification, mass production, miniaturization, and circuit design.
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Qwen3.7 Flash1,381 words
This counterfactual traces a plausible diffusion curve for an early transistor invention, acknowledging that while the underlying physics could be known in 1920, practical adoption would be constrained by materials science, precision manufacturing, and institutional readiness.
Read the full answer

Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

GPT-5.6 Luna Pro826 words
For an experienced software engineer A language model is trained on large collections of text by repeatedly hiding or withholding the next token and asking the model to predict it. “Token” usually means a word fragment rather than a complete word.
Read the full answer
Qwen3.7 Flash1,038 words
For the Experienced Software Engineer Think of an LLM’s training process less as “teaching” and more as optimizing a high-dimensional function across a petabyte-scale dataset, much like you’d architect a distributed system to handle massive throughput.
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Adversarial Contract Review

Here is a contract for a software consulting engagement: --- SOFTWARE CONSULTING AGREEMENT This Agreement is entered into between TechCorp…

GPT-5.6 Luna Pro2,940 words
This agreement is heavily one-sided and leaves several material issues undefined. Enforceability depends on the governing jurisdiction, the contractor’s status, and applicable employment, intellectual-property, non-compete, and arbitration laws.
Read the full answer
Qwen3.7 Flash1,322 words
This agreement contains several highly one-sided provisions that create significant legal, financial, and operational risks for the contractor. Below is a clause-by-clause analysis identifying exploitation risks, recommended modifications, and the underlying legal reasoning. Note: Contract law varies by jurisdiction.
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Our Verdict
GPT-5.6 Luna Pro
GPT-5.6 Luna Pro
Qwen3.7 Flash
Qwen3.7 Flash

Not enough votes to call it. On the specs, nothing separates them.

Qwen3.7 Flash costs 46x less per token.

Too close to call
API pricing

Cost per 1M tokens

GPT-5.6 Luna Pro
Input
$1.00
Output
$6.00
Qwen3.7 Flash
Input
$0.03
33× cheaper
Output
$0.13
46× cheaper

Qwen3.7 Flash is cheaper on both: 33× input, 46× output.

Where to run it

3 hosts

GPT-5.6 Luna Pro2 hosts
HostInOutContextUptime
Azure AI Foundry$0.20 in·$1.20 out·1.1M·92.3% upOpenAI$0.20 in·$1.20 out·1.1M·100% up
Qwen3.7 Flash1 host
HostInOutContextUptime
Alibaba Cloud$0.03 in·$0.13 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GPT-5.6 Luna Pro is developed by OpenAI while Qwen3.7 Flash is developed by Qwen. GPT-5.6 Luna Pro has a 1.1M token context window vs Qwen3.7 Flash's 1.0M. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5.6 Luna Pro and Qwen3.7 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 13 challenges so you can judge which fits your needs best.

GPT-5.6 Luna Pro costs $1/M input tokens and Qwen3.7 Flash costs $0.03/M input tokens. Qwen3.7 Flash is $0.97/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

This page shows a side-by-side comparison of GPT-5.6 Luna Pro and Qwen3.7 Flash across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

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Model pages

GPT-5.6 Luna Pro logo
GPT-5.6 Luna Pro58 outputs, specs and price
Qwen3.7 Flash logo
Qwen3.7 Flash13 outputs, specs and price
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