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  5. GLM 5vsLing 3.0 Flash
Updated Jul 2026

GLM 5vsLing 3.0 Flash

Ling 3.0 Flash is cheaper than GLM 5 at $0.021/M vs $0.8/M input tokens.

GLM 5 and Ling 3.0 Flash compared across 16 shared prompts
SpecGLM 5Ling 3.0 Flash
Input price$0.8/M tokens$0.021/M tokens
Output price$2.56/M tokens$0.063/M tokens
Context window203K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2026Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 16 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…

GLM 5742 words
The Experienced Software Engineer You’re right to be skeptical that a glorified Markov chain could reason, but the leap here is in scale and compression. Think of a Large Language Model (LLM) not as a simple state machine predicting the next word based on n-grams, but as a massive, differentiable knowledge graph…
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

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

GLM 51,005 words
This architecture contains several critical flaws that would lead to data loss, poor user experience, and system instability under load. Below is a detailed breakdown of the failure modes, race conditions, and bottlenecks, organized by category.
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

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…

GLM 5644 words
This 1-month plan is designed to build habits slowly. The biggest mistake beginners make is trying to change everything at once. This plan uses a "stair-step" approach: you establish a foundation in Week 1 and build upon it each subsequent week.
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…

GLM 5214 words
Dish Name: Midnight Golden Garlic Noodles Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes Ingredients: Spaghetti (or Linguine) Butter (salted) Garlic (fresh cloves, minced) Soy Sauce Parmesan Cheese (grated) Black Pepper (freshly cracked) Red Chili Flakes (optional for heat) Instructions: Boil the…
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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

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.…

GLM 5784 words
Based on the pitch deck summary provided, here are the three weakest claims, along with an analysis of why they fail and how to fix them. The Accuracy 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 Flash945 words
Three Weakest Claims in the MindMeld AI Pitch Deck "94% Accuracy" — Slide 3 (Solution) Why It's Weak This is presented as a single, impressive number with zero context, which makes it essentially meaningless — and likely misleading. Several critical questions go unanswered: What is the vocabulary size?
Read the full answer

Adversarial Contract Review

Here is a contract for a software consulting engagement: --- SOFTWARE CONSULTING AGREEMENT This Agreement is entered into between TechCorp…

GLM 51,322 words
This contract contains several heavily one-sided clauses that favor the Client and present significant legal and financial risks to the Contractor. Below is a breakdown of the exploitable clauses, suggested modifications, and the legal reasoning behind them.
Read the full answer
Ling 3.0 Flash2,036 words
Contract Analysis: Exploitative Clauses & Recommended Modifications Clause-by-Clause Analysis SCOPE — Unilateral Modification Without Compensation The Problem: Client can modify the scope at any time and for any reason without paying Contractor for the additional work.
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Our Verdict
GLM 5
GLM 5
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 41x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GLM 5
Input
$0.80
Output
$2.56
Ling 3.0 Flash
Input
$0.02
38× cheaper
Output
$0.06
41× cheaper

Ling 3.0 Flash is cheaper on both: 38× input, 41× output.

Where to run it

10 hosts, cheapest first

GLM 58 hosts
HostInOutContextUptime
GGMI Cloudfp8$0.60 in·$1.92 out·203k·98.6% upSStreamLakefp8$0.60 in·$1.92 out·198k·99.6% upBaidu Qianfanfp8$0.70 in·$2.24 out·203k·99.6% upSSiliconFlowfp8$0.95 in·$2.55 out·205k·99.6% upAmazon Bedrock$1.00 in·$3.20 out·203k·97.1% upNNovitafp8$1.00 in·$3.20 out·203k·100% up
2 more hostsFewer hosts
VVenicefp8$1.00 in·$3.20 out·198k·98.3% upZ.aifp8$1.00 in·$3.20 out·203k·100% 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

GLM 5 is developed by Zhipu AI while Ling 3.0 Flash is developed by inclusionAI. GLM 5 has a 203K 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. GLM 5 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.

GLM 5 costs $0.8/M input tokens and Ling 3.0 Flash costs $0.021/M input tokens. Ling 3.0 Flash is $0.78/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 GLM 5 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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