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  5. Nex-N2.5-Mini (free)vsQwen3.7 Plus
Updated Sep 2026

Nex-N2.5-Mini (free)vsQwen3.7 Plus

Nex-N2.5-Mini (free) is cheaper than Qwen3.7 Plus at $0/M vs $0.4/M input tokens.

Nex-N2.5-Mini (free) and Qwen3.7 Plus compared across 15 shared prompts
SpecNex-N2.5-Mini (free)Qwen3.7 Plus
Input priceFree$0.4/M tokens
Output priceFree$1.6/M tokens
Context window262K tokens1.0M tokens
Weights—Closed
Free API (OpenRouter)Yes (1 provider)No
ReleasedSep 2026May 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 15 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…

Nex-N2.5-Mini (free)111 words
Golden Peanut Lantern Noodles Time: Prep 5 min Cook 10 min Serves: 2 Ingredients — 7 pantry staples Spaghetti or any noodles Peanut butter Soy sauce Honey Garlic powder Rice vinegar Water Instructions Cook the noodles: Boil noodles in water until tender. Reserve about ½ cup cooking water, then drain.
Read the full answer
Qwen3.7 Plus311 words
Creative Name: Midnight Velvet Chocolate Peanut Butter Bites These no-bake, fudgy bites taste like a cross between a chocolate peanut butter cup and a soft oatmeal cookie. They require zero baking, come together in minutes, and use strictly shelf-stable staples you likely already have.
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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…

Nex-N2.5-Mini (free)889 words
Experienced software engineer, skeptical of “next word prediction” Think of training an LLM less like teaching it rules and more like running a huge offline simulation. You feed it a corpus of text, tokenize it into chunks, and give it a simple task: given the previous tokens, predict the next token.
Read the full answer
Qwen3.7 Plus863 words
Here is how a Large Language Model learns and generates text, tailored specifically to the background, skepticism, and priorities of each audience. The Experienced Software Engineer Focus: Distributed systems, latent space, emergent behavior, and addressing the "glorified autocomplete" skepticism.
Read the full answer

Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

Nex-N2.5-Mini (free)3,213 words
Below is a 12-week longevity/performance protocol for a generally healthy adult. It is not medical advice. Before starting—especially if you have diabetes, hypertension, arrhythmia, kidney/liver disease, a history of eating disorders, are pregnant, or take medications—get clinician clearance and use labs to personalize…
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Qwen3.7 Plus1,220 words
This is a comprehensive, cutting-edge 3-month longevity and performance protocol designed for an advanced biohacker. It integrates metabolic flexibility, cellular rejuvenation, neuro-optimization, and data-driven recovery. Disclaimer: This protocol is for educational purposes.
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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…

Nex-N2.5-Mini (free)2,076 words
A 1920 transistor would not by itself prevent fascism, the Great Depression, or imperial expansion, so World War II might still happen. But it would make electronics 10–20 years more advanced than in our timeline, with huge effects on radar, codebreaking, computing, missiles, space, consumer goods, and Cold War power…
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Qwen3.7 Plus1,170 words
If the transistor had been invented and commercialized in 1920 (perhaps by Julius Lilienfeld, who patented the field-effect concept in 1925, or an alternate timeline version of the Bell Labs team), the 20th century would have undergone a profound acceleration.
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Debug This Architecture

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

Nex-N2.5-Mini (free)1,869 words
The biggest red flags are: client-clock LWW for document content, polling PostgreSQL for real-time fanout, CDN caching mutable authenticated APIs, per-server WebSocket state with no durable replay, and full HTML snapshots as the main save mechanism.
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Qwen3.7 Plus1,206 words
This architecture contains several critical anti-patterns for a real-time collaborative system. While it might work for a handful of users, it will fail catastrophically under load and produce severe data consistency issues.
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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.…

Nex-N2.5-Mini (free)594 words
The 3 weakest claims are the ones that are broadest, least falsifiable, or mathematically inconsistent. # Weak claim Why it’s weak How to strengthen it 1 “MindMeld AI reads your brainwaves to predict what you want to type before you think it.”
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Qwen3.7 Plus733 words
Here are the 3 weakest claims in the MindMeld AI pitch deck, along with an analysis of why they fail and concrete ways to fix them. (Note: These critiques are written from the perspective of a seasoned technical investor or VC, who will immediately scrutinize scientific plausibility and business model alignment).
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Our Verdict
Nex-N2.5-Mini (free)
Nex-N2.5-Mini (free)
Qwen3.7 Plus
Qwen3.7 Plus

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

Too close to call
API pricing

Cost per 1M tokens

Nex-N2.5-Mini (free)
Input
$0.000
Output
$0.000
Qwen3.7 Plus
Input
$0.40
Output
$1.60
Where to run it

2 hosts

Nex-N2.5-Mini (free)1 host
HostInOutContextUptime
NNex AGIbf16degraded$0 in·$0 out·262k·92.2% up
Qwen3.7 Plus1 host
HostInOutContextUptime
Alibaba Cloud$0.32 in·$1.28 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

Nex-N2.5-Mini (free) is developed by Nex AGI while Qwen3.7 Plus is developed by Qwen. Nex-N2.5-Mini (free) has a 262K token context window vs Qwen3.7 Plus's 1.0M. You can compare their actual outputs across 15 challenges on Rival to see how they differ in practice.

It depends on your use case. Nex-N2.5-Mini (free) and Qwen3.7 Plus each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 15 challenges so you can judge which fits your needs best.

Nex-N2.5-Mini (free) costs $0/M input tokens and Qwen3.7 Plus costs $0.4/M input tokens. Nex-N2.5-Mini (free) is $0.40/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 Nex-N2.5-Mini (free) and Qwen3.7 Plus 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

Nex-N2.5-Mini (free) logo
Nex-N2.5-Mini (free)15 outputs, specs and price
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Qwen3.7 Plus58 outputs, specs and price
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