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  5. GPT-5.4vsLing 3.0 Flash Fin (free)
Updated Aug 2026

GPT-5.4vsLing 3.0 Flash Fin (free)

Ling 3.0 Flash Fin (free) is cheaper than GPT-5.4 at $0/M vs $2.5/M input tokens.

GPT-5.4 and Ling 3.0 Flash Fin (free) compared across 20 shared prompts
SpecGPT-5.4Ling 3.0 Flash Fin (free)
Input price$2.5/M tokensFree
Output price$15/M tokensFree
Context window1.1M tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoYes (1 provider)
ReleasedMar 2026Aug 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 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-5.4169 words
Creative Name: Golden Crunch Honey Garlic Noodles 7 Pantry Ingredients: Spaghetti or any noodles Garlic Soy sauce Honey Olive oil Red pepper flakes Breadcrumbs Estimated Time: Prep: 5 minutes Cook: 12 minutes Total: 17 minutes Instructions: Cook the noodles according to package directions.
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Ling 3.0 Flash Fin (free)166 words
Midnight Molten Lava Cake Ingredients: All-purpose flour (4 tbsp) Granulated sugar (4 tbsp) Unsweetened cocoa powder (2 tbsp) Vegetable oil (3 tbsp) Water (2 tbsp) Vanilla extract (¼ tsp) Baking powder (¼ tsp) Instructions: Combine Dry Ingredients: In a standard microwave-safe mug, whisk together the flour, sugar…
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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-5.42,210 words
Dish Concept Hay-Smoked Duck, White Chocolate–Parsnip Velouté, Burnt Mandarin, Black Garlic-Licorice Jus, and Buckwheat Tuile with Oscietra Caviar Conceptual Narrative This dish explores the tension between pastoral warmth and urban refinement. At its core is duck: primal, luxurious, and deeply savory.
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Ling 3.0 Flash Fin (free)2,253 words
L'Archipel des Ombres (The Archipelago of Shadows) Michelin-Caliber Multi-Component Dish 7 Components Conceptual Narrative: Memory, Mineral Essence, and the Meeting of Land and Sea CONCEPTUAL NARRATIVE This dish is an edible cartography—a map of an imaginary archipelago where volcanic soil meets oceanic tides.
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Advanced Longevity Plan (Biohacker)

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

GPT-5.42,946 words
Below is a high-level, educational 12-week framework for “longevity-oriented performance optimization.” It is not medical advice and shouldn’t replace care from a physician, especially because some interventions biohackers use can interact with medications, affect liver/kidney function, sleep, mood, blood pressure…
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Ling 3.0 Flash Fin (free)2,898 words
🧬 THE BIOHACKER'S 90-DAY LONGEVITY OPTIMIZATION PLAN Disclaimer: This plan is for informational purposes only. Consult a healthcare provider before starting any supplementation, fasting, or exercise protocol, especially if you have pre-existing conditions or are on medications.
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Advanced Investment Memo (IC Memo)

You are writing an internal investment committee memo for a long/short equity fund. Company (fictional): LedgerLift (ticker: LLLT) – B2B…

GPT-5.41,307 words
LedgerLift (LLLT) — Internal IC Memo Recommendation: Long Current Price: $46 12-month PT range: $58–$74 (base-centered fair value ~$66; downside ~$47; upside ~$86 on DCF, but we cap 12-month bull PT at $74 to reflect execution/rating risk) Two-sentence thesis: LedgerLift screens as a high-quality vertical SaaS/fintech…
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Ling 3.0 Flash Fin (free)771 words
INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: Equity Research Date: October 24, 2025 Subject: LedgerLift (LLLT) – Short Recommendation Recommendation & Thesis Recommendation: Short 12-Month PT Range: $30 – $38 Thesis: LedgerLift’s 123% NRR and 18-month CAC payback mask an eventual growth…
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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…

GPT-5.41,322 words
For an experienced software engineer A large language model is easiest to understand as a very large function that maps a sequence of tokens to a probability distribution over the next token. “Tokens” are subword chunks, not necessarily words.
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Ling 3.0 Flash Fin (free)928 words
For the Experienced Software Engineer Here's the thing: the way you build a distributed system that "does the right thing" isn't by writing rules for every possible scenario — it's by designing the system so that correct behavior emerges from many simple, well-specified interactions.
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Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

GPT-5.41,258 words
Below is a simplified 5-year LBO model for HarborTech Services (HTS) using only the assumptions provided. Entry, sources & uses Purchase price FY2025 EBITDA = $120.0m Entry multiple = 12.0x Enterprise Value = 12.0 × 120.0 = $1,440.0m Fees Transaction fees = 2.0% of EV = 2.0% × 1,440.0 = $28.8m Uses Purchase of…
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Ling 3.0 Flash Fin (free)556 words
Entry & Sources & Uses FY2025 EBITDA: $120m Purchase Price (EV): 12.0x × $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m Total Uses: $1,440m + $28.8m = $1,468.8m Total Leverage: 5.5x × $120m = $660m Term Loan: 4.0x × $120m = $480m (9.0% cash interest, 1.0% mandatory amortization = $4.8m/yr) Mezzanine: 1.5x ×…
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Our Verdict
GPT-5.4
GPT-5.4
Ling 3.0 Flash Fin (free)
Ling 3.0 Flash Fin (free)Runner-up

Not enough votes to call it. On the specs, GPT-5.4 has the edge: bigger model tier, bigger context window, major provider backing.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-5.4
Input
$2.50
Output
$15.00
Ling 3.0 Flash Fin (free)
Input
$0.000
Output
$0.000
Where to run it

4 hosts, cheapest first

GPT-5.43 hosts
HostInOutContextUptime
Azure AI Foundry$2.50 in·$15.00 out·1.1M·100% upOpenAI$2.50 in·$15.00 out·1.1M·100% upAmazon Bedrock$2.75 in·$16.50 out·1.1M—
Ling 3.0 Flash Fin (free)1 host
HostInOutContextUptime
NNovita$0 in·$0 out·262k·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-5.4 is developed by OpenAI while Ling 3.0 Flash Fin (free) is developed by inclusionAI. GPT-5.4 has a 1.1M token context window vs Ling 3.0 Flash Fin (free)'s 262K. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5.4 and Ling 3.0 Flash Fin (free) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 20 challenges so you can judge which fits your needs best.

GPT-5.4 costs $2.5/M input tokens and Ling 3.0 Flash Fin (free) costs $0/M input tokens. Ling 3.0 Flash Fin (free) is $2.50/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-5.4 and Ling 3.0 Flash Fin (free) 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

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