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  5. Gemini 3.7 FlashvsLing 3.0 Flash Fin (free)
Updated Aug 2026

Gemini 3.7 FlashvsLing 3.0 Flash Fin (free)

Ling 3.0 Flash Fin (free) is cheaper than Gemini 3.7 Flash at $0/M vs $0.375/M input tokens.

Gemini 3.7 Flash and Ling 3.0 Flash Fin (free) compared across 20 shared prompts
SpecGemini 3.7 FlashLing 3.0 Flash Fin (free)
Input price$0.375/M tokensFree
Output price$1.875/M tokensFree
Context window1.0M tokens262K tokens
WeightsClosed—
Free API (OpenRouter)NoYes (1 provider)
ReleasedAug 2026Aug 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 prompts both answered. Formatting stripped, words untouched.

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…

Gemini 3.7 Flash844 words
To the Experienced Software Engineer At its core, a Large Language Model is not a sentient entity; it is a compiled, highly optimized functional pipeline executing a deterministic set of matrix multiplications over a sequence of integers (tokens). Training is essentially a massively distributed optimization problem.
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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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Historical Counterfactual Analysis

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

Gemini 3.7 Flash1,203 words
If the transistor had been invented in 1920—likely as an empirical discovery in solid-state physics using point-contact crystals (similar to Julius Lilienfeld’s real-world 1925 theoretical patents, but made fully functional)—it would have compressed modern technological history by nearly three decades.
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Ling 3.0 Flash Fin (free)2,066 words
The 1920 Transistor: A Counterfactual Analysis Through 1980 I. Premise and Plausibility For a transistor to emerge in 1920, we must assume that either the theoretical framework of semiconductor physics was accelerated (quantum mechanics was only being formulated in the mid-1920s), or that empirical discovery—building…
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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…

Gemini 3.7 Flash1,535 words
3-Month Precision Longevity & Human Optimization Masterplan This protocol is engineered for an advanced biohacker. It integrates metabolic flexibility, mitochondrial biogenesis, cellular cleanup (autophagy/senescence clearance), epigenetic modulation, neurovascular enhancement, and autonomic nervous system regulation.
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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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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…

Gemini 3.7 Flash958 words
L’Ombre et L’Abîme (Shadow & The Abyss) Hay-Aged Bresse Squab, Hokkaido Sea Urchin Emulsion, Black Garlic–Koji Glaze, Cocoa Nib & Cuttlefish Ink Tuile, Forest Dashi I. Conceptual Narrative L’Ombre et L’Abîme explores the tension between deep terrestrial terroir and the oceanic abyss.
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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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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…

Gemini 3.7 Flash335 words
Dish Name: Midnight Garlic-Butter Silk Noodles A rich, savory, and slightly sweet bowl of glossy pasta tossed in caramelized garlic-butter and soy glaze, crowned with a crispy-edged, runny-yolk egg.
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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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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.…

Gemini 3.7 Flash590 words
Here are the 3 weakest claims in the MindMeld AI pitch deck, along with an evaluation of why they undermine credibility and how to fix them. The Technical Feasibility Claim (Slide 3) The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.
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Ling 3.0 Flash Fin (free)961 words
The 3 Weakest Claims in the MindMeld AI Pitch 🚨 The $180B TAM Claim (Slide 4) Why it's weak: This is the most logically incoherent claim in the entire deck. The pitch states the BCI market is projected to reach $5.3B by 2030 (citing Grand View Research) — and then immediately claims a TAM of $180B.
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Our Verdict
Gemini 3.7 Flash
Gemini 3.7 Flash
Ling 3.0 Flash Fin (free)
Ling 3.0 Flash Fin (free)Runner-up

Not enough votes to call it. On the specs, Gemini 3.7 Flash has the edge: 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

Gemini 3.7 Flash
Input
$0.38
Output
$1.88
Ling 3.0 Flash Fin (free)
Input
$0.000
Output
$0.000
Where to run it

3 hosts

Gemini 3.7 Flash2 hosts
HostInOutContextUptime
Google Vertex AI$0.75 in·$3.75 out·1M·99.5% upGoogle AI Studio$0.75 in·$3.75 out·1M·99.8% up
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

Gemini 3.7 Flash is developed by Google AI while Ling 3.0 Flash Fin (free) is developed by inclusionAI. Gemini 3.7 Flash has a 1.0M 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. Gemini 3.7 Flash 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.

Gemini 3.7 Flash costs $0.375/M input tokens and Ling 3.0 Flash Fin (free) costs $0/M input tokens. Ling 3.0 Flash Fin (free) is $0.38/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 Gemini 3.7 Flash 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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