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  5. Ling 3.0 Flash Fin (free)vsQwen3.8 27B
Updated Aug 2026

Ling 3.0 Flash Fin (free)vsQwen3.8 27B

Ling 3.0 Flash Fin (free) is cheaper than Qwen3.8 27B at $0/M vs $0.4/M input tokens.

Ling 3.0 Flash Fin (free) and Qwen3.8 27B compared across 20 shared prompts
SpecLing 3.0 Flash Fin (free)Qwen3.8 27B
Input priceFree$0.4/M tokens
Output priceFree$3/M tokens
Context window262K tokens262K tokens
Weights—Open
Free API (OpenRouter)Yes (1 provider)Yes (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.

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…

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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Qwen3.8 27B116 words
Pantry Firecracker Black Beans A quick, savory, one-pan dish made with only 7 common pantry ingredients. Estimated time: Prep: 5 minutes Cook: 10 minutes Total: about 15 minutes Ingredients 1 can black beans, drained 2 tablespoons olive oil 1 teaspoon ground cumin 1/2 teaspoon chili powder 1/2 teaspoon garlic powder…
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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…

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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Qwen3.8 27B3,174 words
Tidal Cellar Koji-Cured Scallop, Oyster, Black Garlic, 24-Month Parmigiano, Apple, and Sea Fennel Menu line: Koji-cured sea scallop, oyster-apple gel, charred celeriac, black garlic and 24-month Parmigiano velouté, apple-hazelnut shard, sea fennel–chive oil, black garlic–oak ash.
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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…

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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Qwen3.8 27B1,144 words
For an experienced software engineer Think of a large language model as a stateless inference service plus an enormous offline training pipeline. At inference time, the model takes a prompt, converts it into tokens, and produces a probability distribution over the next token.
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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.…

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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Qwen3.8 27B2,587 words
The 3 weakest claims are the ones that carry the investment thesis: product feasibility, market size, and proof of demand/valuation. Weakest claim: “MindMeld AI reads your brainwaves to predict what you want to type before you think it” + “94% accuracy. Works with any language, any device.”
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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…

Ling 3.0 Flash Fin (free)825 words
This 1-month plan is designed to build foundational habits without causing burnout. The golden rule of beginner health is "add before you subtract"—focus on adding good habits rather than punishing yourself by removing "bad" ones. Here is your simple, actionable 1-month plan focusing on Diet, Exercise, and Sleep.
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Qwen3.8 27B936 words
Here’s a simple, beginner-friendly 1-month plan focused on 3 key areas: movement, food, and sleep/stress. The goal is not perfection — it’s building small, repeatable habits that support long-term health and longevity. Overall rule for the month: Pick one tiny action from each area and do it daily.
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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…

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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Qwen3.8 27B837 words
Fictional internal memo; not investment advice. Recommendation: Short (moderate conviction) 12-month PT range: $30–$44 Thesis: LLLT is a high-quality, cash-rich spend-management SaaS business, but at $46 it embeds a peer EBIT multiple that its 20% FY26E EBIT margin and conservative DCF do not support.
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Our Verdict
Ling 3.0 Flash Fin (free)
Ling 3.0 Flash Fin (free)
Qwen3.8 27B
Qwen3.8 27BRunner-up

Not enough votes to call it. On the specs, Ling 3.0 Flash Fin (free) has the edge: bigger model tier.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Ling 3.0 Flash Fin (free)
Input
$0.000
Output
$0.000
Qwen3.8 27B
Input
$0.40
Output
$3.00
Where to run it

17 hosts, cheapest first

Ling 3.0 Flash Fin (free)1 host
HostInOutContextUptime
NNovita$0 in·$0 out·262k·100% up
Qwen3.8 27B16 hosts
HostInOutContextUptime
DDarkbloomfp4$0.10 in·$1.80 out·262k·99% upDDekaLLM$0.10 in·$2.50 out·262k·99.7% upWWafer$0.11 in·$2.50 out·262k·99.9% upRRekafp8$0.12 in·$2.48 out·262k·99.9% upDDeepInfrabf16$0.15 in·$1.88 out·262k·97% upPPhala$0.20 in·$2.08 out·262k·98% up
10 more hostsFewer hosts
MMancerfp8$0.20 in·$2.50 out·262k·99.8% upCChutesfp8$0.24 in·$2.20 out·262k·99.4% upPParasailfp8$0.24 in·$2.20 out·262k·99.9% upAAkashMLfp8$0.25 in·$2.20 out·262k·100% upIIonstreamfp8$0.28 in·$2.55 out·262k·97.9% upCCoreWeavefp8$0.40 in·$3.00 out·262k·99.5% upNNovita$0.42 in·$3.00 out·1M·99.9% upAlibaba Cloud$0.42 in·$2.55 out·1M·100% upCloudflare Workers AI$0.45 in·$3.20 out·262k·91.7% upVVenicefp8$0.45 in·$3.20 out·262k·97.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Ling 3.0 Flash Fin (free) is developed by inclusionAI while Qwen3.8 27B is developed by Qwen. Ling 3.0 Flash Fin (free) has a 262K token context window vs Qwen3.8 27B'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. Ling 3.0 Flash Fin (free) and Qwen3.8 27B 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.

Ling 3.0 Flash Fin (free) costs $0/M input tokens and Qwen3.8 27B costs $0.4/M input tokens. Ling 3.0 Flash Fin (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 Ling 3.0 Flash Fin (free) and Qwen3.8 27B 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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Explore all of Rival

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