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  5. GPT-4.1 NanovsLing 3.0 Flash
Updated Jul 2026

GPT-4.1 NanovsLing 3.0 Flash

Ling 3.0 Flash is cheaper than GPT-4.1 Nano at $0.021/M vs $0.1/M input tokens.

GPT-4.1 Nano and Ling 3.0 Flash compared across 16 shared prompts
SpecGPT-4.1 NanoLing 3.0 Flash
Input price$0.1/M tokens$0.021/M tokens
Output price$0.4/M tokens$0.063/M tokens
Context window1.0M tokens262K tokens
ParametersNot disclosed124B
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedApr 2025Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 16 prompts both answered. Formatting stripped, words untouched.

Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

GPT-4.1 Nano417 words
Certainly! Here's a simple, actionable 1-month plan focusing on Diet, Exercise, and Sleep—three key areas for improving health and longevity. Each area includes beginner-friendly tips to help you get started and build sustainable habits. Week 1-4: 1-Month Health & Longevity Plan 1.
Read the full answer
Ling 3.0 Flash568 words
🌱 Your 1-Month Health & Longevity Starter Plan 🥦 1. Diet — Nourish, Don't Deprive Week 1: Awareness Keep a food journal — just track what you eat (no judgment). This alone builds mindful eating habits. Add, don't subtract — introduce one extra serving of vegetables per meal.
Read the full answer

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-4.1 Nano199 words
Dish Name: Savory Sweet Potato & Chickpea Hash Ingredients: Sweet potatoes (2 medium) Canned chickpeas (1 can, drained and rinsed) Olive oil (2 tablespoons) Garlic powder (1 teaspoon) Smoked paprika (1 teaspoon) Salt and pepper (to taste) Honey (1 tablespoon) Estimated Prep/Cook Time: 30 minutes Instructions: Prepare…
Read the full answer
Ling 3.0 Flash248 words
🍝 Honey Fire Twirls A sticky-sweet, spicy, savory pasta that comes together in minutes. 🧺 Ingredients (7 pantry staples) Spaghetti (or penne) — 8 oz Olive oil — 2 tablespoons Garlic, minced — 4 cloves Honey — 3 tablespoons Soy sauce — 2 tablespoons Red pepper flakes — ½ teaspoon (adjust to taste) Parmesan cheese…
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-4.1 Nano776 words
Let's analyze the architecture step-by-step to identify potential failure modes, race conditions, and scaling bottlenecks, along with proposed solutions and their trade-offs. 1. Potential Failure Modes a.
Read the full answer
Ling 3.0 Flash2,291 words
Architecture Analysis: Real-Time Collaborative Document Editor WebSocket & Cross-Server Communication Issue: Siloed WebSocket Servers (Critical) Each API server only broadcasts changes to clients connected to that specific server.
Read the full answer

Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

GPT-4.1 Nano685 words
Dish Name: Celestial Harmony – A Deconstructed Black Garlic & Blueberry Soufflé with Yuzu Foam and Edible Silver Dust Conceptual Narrative: This dish embodies the cosmic dance of contrasts—earth and sky, sweetness and umami, tradition and innovation.
Read the full answer
Ling 3.0 Flash2,510 words
🍽️ TERRA NUDA — A Study in Forest Petrichor A Six-Component Dish Exploring the Ephemeral Moment After Rain Falls on a Living Forest 📖 CONCEPTUAL NARRATIVE Terra Nuda — Latin for "naked earth" — is inspired by the liminal moment immediately after a summer storm passes through a forest: the air thick with petrichor…
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-4.1 Nano629 words
1. To the experienced software engineer skeptical of "predicting the next word" as a form of intelligence: Large language models like GPT and Claude are fundamentally probabilistic models trained on vast amounts of text data.
Read the full answer
Ling 3.0 Flash1,129 words
For the Experienced Software Engineer Think of an LLM as a system that learns a massive, multidimensional routing table. When you built distributed systems, you learned patterns from traffic logs — which endpoints get hammered at 3am, which failure modes correlate, which request chains tend to cascade.
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-4.1 Nano783 words
This is an urgent and complex situation that demands a carefully coordinated response to balance transparency, legal obligations, patient safety, and company reputation.
Read the full answer
Ling 3.0 Flash2,623 words
48-Hour Action Plan: Responsible Disclosure of Serious Adverse Effect FOUNDATIONAL PRINCIPLE Before the hour-by-hour breakdown, the strategic and ethical framework must be established clearly: proactive, transparent disclosure is the only viable path.
Read the full answer
Our Verdict
GPT-4.1 Nano
GPT-4.1 Nano
Ling 3.0 Flash
Ling 3.0 Flash

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

Ling 3.0 Flash costs 6.3x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-4.1 Nano
Input
$0.10
Output
$0.40
Ling 3.0 Flash
Input
$0.02
4.8× cheaper
Output
$0.06
6.3× cheaper

Ling 3.0 Flash is cheaper on both: 4.8× input, 6.3× output.

Where to run it

4 hosts, cheapest first

GPT-4.1 Nano2 hosts
HostInOutContextUptime
Azure AI Foundry$0.10 in·$0.40 out·1M·99.7% upOpenAI$0.10 in·$0.40 out·1M·99.9% up
Ling 3.0 Flash2 hosts
HostInOutContextUptime
NNovita$0.02 in·$0.06 out·262k·100% upDDeepInfrabf16$0.06 in·$0.18 out·131k·99.6% up

Per million tokens. Prices and uptime via OpenRouter, checked 22 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GPT-4.1 Nano is developed by OpenAI while Ling 3.0 Flash is developed by inclusionAI. GPT-4.1 Nano has a 1.0M token context window vs Ling 3.0 Flash's 262K. You can compare their actual outputs across 16 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-4.1 Nano and Ling 3.0 Flash each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 16 challenges so you can judge which fits your needs best.

GPT-4.1 Nano costs $0.1/M input tokens and Ling 3.0 Flash costs $0.021/M input tokens. Ling 3.0 Flash is $0.08/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-4.1 Nano and Ling 3.0 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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