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  5. Ling 3.0 FlashvsLlama 3.1 70B (Instruct)
Updated Jul 2026

Ling 3.0 FlashvsLlama 3.1 70B (Instruct)

Ling 3.0 Flash is cheaper than Llama 3.1 70B (Instruct) at $0.021/M vs $0.59/M input tokens.

Ling 3.0 Flash and Llama 3.1 70B (Instruct) compared across 16 shared prompts
SpecLing 3.0 FlashLlama 3.1 70B (Instruct)
Input price$0.021/M tokens$0.59/M tokens
Output price$0.063/M tokens$0.79/M tokens
Context window262K tokens128K tokens
Parameters124B70B
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2024
Side by side

Same prompt, both answers

Opening lines from 6 of the 16 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 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…
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Llama 3.1 70B (Instruct)311 words
Here is a simple recipe for a delicious dish using only 7 common pantry ingredients: Dish Name: "Sunset Crunch Bites" Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/4 cup honey 1/4 cup chopped peanuts 1/2 teaspoon salt 1/4 teaspoon cinnamon 1/4 cup chocolate chips (semi-sweet) Instructions: Preheat your oven to…
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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 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…
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Llama 3.1 70B (Instruct)653 words
Dish Name: "Aurora Australis" - A Harmonious Union of Smoked Eel, Saffron-Infused Sunchokes, and Frozen Finger Lime Pearls Conceptual Narrative: Inspired by the breathtaking display of the Southern Lights, "Aurora Australis" is a dish that embodies the ethereal beauty of the Antarctic night sky.
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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 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.
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Llama 3.1 70B (Instruct)729 words
For the experienced software engineer: You're likely familiar with the concept of prediction in distributed systems, where a model predicts the likelihood of a certain event or outcome. Large language models like GPT or Claude take this concept to the next level by predicting the next word in a sequence of text.
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…

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.
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Llama 3.1 70B (Instruct)612 words
Potential Failure Modes: Single Point of Failure (SPOF) in Load Balancer: If the load balancer fails, all incoming traffic will be lost. Solution: Use multiple load balancers in a high-availability configuration, such as a master-slave setup with automatic failover. Trade-off: Additional complexity and cost.
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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 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.
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Llama 3.1 70B (Instruct)420 words
Here's a simple, actionable 1-month plan for someone starting their journey towards better health and longevity, focusing on 3 key areas: diet, exercise, and sleep. Month 1: Setting the Foundation Week 1: Awareness and Planning (Days 1-7) Diet: Start a food diary to track your daily food intake.
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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…

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.
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Llama 3.1 70B (Instruct)533 words
Hour 1-2: Immediate Review and Verification (Now - 1 hour) Summon the internal research team to confirm the findings, understand the methodology, and assess the confidence level of the results.
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Our Verdict
Ling 3.0 Flash
Ling 3.0 Flash
Llama 3.1 70B (Instruct)
Llama 3.1 70B (Instruct)Runner-up

Not enough votes to call it. On the specs, Ling 3.0 Flash has the edge: bigger model tier, newer, bigger context window.

Ling 3.0 Flash costs 13x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Ling 3.0 Flash
Input
$0.02
28× cheaper
Output
$0.06
13× cheaper
Llama 3.1 70B (Instruct)
Input
$0.59
Output
$0.79

Ling 3.0 Flash is cheaper on both: 28× input, 13× output.

Where to run it

4 hosts, cheapest first

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
Llama 3.1 70B (Instruct)2 hosts
HostInOutContextUptime
DDeepInfrafp8$0.40 in·$0.40 out·131k·96.9% upAmazon Bedrock$0.72 in·$0.72 out·131k·100% up

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

Research

What we learned reading every model

FAQ

Common questions

Ling 3.0 Flash is developed by inclusionAI while Llama 3.1 70B (Instruct) is developed by Meta AI. Ling 3.0 Flash has a 262K token context window vs Llama 3.1 70B (Instruct)'s 128K. You can compare their actual outputs across 16 challenges on Rival to see how they differ in practice.

It depends on your use case. Ling 3.0 Flash and Llama 3.1 70B (Instruct) 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.

Ling 3.0 Flash costs $0.021/M input tokens and Llama 3.1 70B (Instruct) costs $0.59/M input tokens. Ling 3.0 Flash is $0.57/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 and Llama 3.1 70B (Instruct) 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

Ling 3.0 Flash logo
Ling 3.0 Flash16 outputs, specs and price
Llama 3.1 70B (Instruct) logo
Llama 3.1 70B (Instruct)56 outputs, specs and price
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