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  5. GPT-6 LunavsMiMo-V2.5-Pro
Updated Sep 2026

GPT-6 LunavsMiMo-V2.5-Pro

GPT-6 Luna is cheaper than MiMo-V2.5-Pro at $0.1/M vs $1/M input tokens.

GPT-6 Luna and MiMo-V2.5-Pro compared across 19 shared prompts
SpecGPT-6 LunaMiMo-V2.5-Pro
Input price$0.1/M tokens$1/M tokens
Output price$0.5/M tokens$3/M tokens
Context window1.1M tokens1.0M tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Apr 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 19 prompts both answered. Formatting stripped, words untouched.

Adversarial Contract Review

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

GPT-6 Luna2,040 words
This agreement is strongly one-sided. The enforceability of particular terms—especially the non-compete, liability provisions, and arbitration clause—depends on the governing law and the facts. The agreement does not identify a governing law, which is itself a significant gap.
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MiMo-V2.5-Pro1,249 words
This contract is heavily skewed in favor of the client and contains several clauses that could be exploited to the significant detriment of the contractor. Here is a breakdown of the problematic clauses, suggested modifications, and the legal reasoning. 1.
Read the full answer

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

GPT-6 Luna1,979 words
The main architectural risk is that the system treats collaborative editing as “write a value, then broadcast it.” That works poorly under concurrency, server failures, reconnects, and scale.
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MiMo-V2.5-Pro1,787 words
Architecture Analysis: Failure Modes, Race Conditions & Bottlenecks This is a thorough red-pen review. There are some genuinely critical issues here — several of which would cause silent data loss in production.
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-6 Luna1,930 words
I would not wait six months for more data. A potentially fatal signal affecting a drug used by millions requires immediate safety assessment, prompt engagement with regulators, and a plan to inform patients and clinicians.
Read the full answer
MiMo-V2.5-Pro3,124 words
The Next 48 Hours: An Action Plan The Core Decision (Made in the First 30 Minutes) Before I lay out the hour-by-hour plan, let me be clear about the foundational decision: we disclose, we act, and we act now.
Read the full answer

Historical Counterfactual Analysis

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

GPT-6 Luna1,472 words
The most important caveat is that inventing a transistor is not the same as inventing the modern semiconductor industry. A device demonstrated in 1920 might be a crude, low-power, unreliable point-contact transistor.
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MiMo-V2.5-Pro3,115 words
The Transistor in 1920: A Counterfactual History Through 1980 This is one of the richest counterfactuals in technological history because the transistor wasn't just an incremental improvement—it was the foundational enabler of the entire digital age.
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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-6 Luna421 words
“94% accuracy” and “predict what you want to type before you think it” Why it’s weak: This is the deck’s central technical claim, but “accuracy” is undefined: Is it word-level or character-level accuracy, measured on a fixed vocabulary or open-ended text, and under what conditions?
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MiMo-V2.5-Pro715 words
Based on a critical analysis of the pitch deck, here are the three weakest claims, along with explanations and suggestions for strengthening them. Weakest Claim: "94% accuracy" (Slide 3) Why it's weak: This is a classic "lab vs. real world" problem.
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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-6 Luna113 words
Crispy Parmesan Chickpeas A crunchy, savory snack with a cheesy finish Ingredients (7): 1 can chickpeas, drained and dried 1 tablespoon olive oil ½ teaspoon salt ½ teaspoon paprika ¼ teaspoon garlic powder ¼ cup grated Parmesan 1 tablespoon lemon juice Prep time: 5 minutes Cook time: 30–35 minutes Instructions: Heat…
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MiMo-V2.5-Pro203 words
Dish Name: Pantry Raid Pasta Estimated Time: 10 min prep / 15 min cook Ingredients 250g spaghetti (or any pasta) 3 cloves garlic, thinly sliced 3 tbsp olive oil 1 tsp crushed red pepper flakes 1 tsp smoked paprika 1/2 cup grated Parmesan cheese (or any hard cheese) Salt & black pepper to taste Instructions Cook the…
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Our Verdict
GPT-6 Luna
GPT-6 Luna
MiMo-V2.5-Pro
MiMo-V2.5-Pro

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

GPT-6 Luna costs 6.0x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-6 Luna
Input
$0.10
10× cheaper
Output
$0.50
6.0× cheaper
MiMo-V2.5-Pro
Input
$1.00
Output
$3.00

GPT-6 Luna is cheaper on both: 10× input, 6.0× output.

Where to run it

10 hosts, cheapest first

GPT-6 Luna3 hosts
HostInOutContextUptime
Azure AI Foundry$0.10 in·$0.50 out·1.1M·88.4% upOpenAI$0.10 in·$0.50 out·1.1M·99.9% upAmazon Bedrock$0.11 in·$0.55 out·1.1M·99.8% up
MiMo-V2.5-Pro7 hosts
HostInOutContextUptime
Xiaomifp8$0.43 in·$0.87 out·1M·98.4% upDDigitalOcean$0.48 in·$1.80 out·262k·99.7% upNNovita$0.48 in·$0.96 out·1M·96% upGGMI Cloudbf16degraded$0.30 in·$0.61 out·1.1M·93% upDDeepInfrafp8degraded$0.39 in·$1.17 out·1M·87.9% upAAtlasCloudfp8degraded$0.43 in·$0.87 out·1M·92.9% up
1 more hostFewer hosts
SStreamLakedegraded$0.52 in·$1.04 out·1M·92.4% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GPT-6 Luna is developed by OpenAI while MiMo-V2.5-Pro is developed by Xiaomi. GPT-6 Luna has a 1.1M token context window vs MiMo-V2.5-Pro's 1.0M. You can compare their actual outputs across 19 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-6 Luna and MiMo-V2.5-Pro each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 19 challenges so you can judge which fits your needs best.

GPT-6 Luna costs $0.1/M input tokens and MiMo-V2.5-Pro costs $1/M input tokens. GPT-6 Luna is $0.90/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-6 Luna and MiMo-V2.5-Pro 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.

Keep exploring

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Same lab, same size, long tail

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MiMo-V2.5-Pro logoGPT-5.4 Nano logo
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Model pages

GPT-6 Luna logo
GPT-6 Luna20 outputs, specs and price
MiMo-V2.5-Pro logo
MiMo-V2.5-Pro57 outputs, specs and price
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