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  5. GLM 5vsLing 3.0 Flash Fin (free)
Updated Aug 2026

GLM 5vsLing 3.0 Flash Fin (free)

Ling 3.0 Flash Fin (free) is cheaper than GLM 5 at $0/M vs $0.8/M input tokens.

GLM 5 and Ling 3.0 Flash Fin (free) compared across 20 shared prompts
SpecGLM 5Ling 3.0 Flash Fin (free)
Input price$0.8/M tokensFree
Output price$2.56/M tokensFree
Context window203K tokens262K tokens
WeightsOpen—
Free API (OpenRouter)NoYes (1 provider)
ReleasedFeb 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…

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 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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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…
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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…

GLM 51,134 words
Moving the invention of the transistor from 1947 to 1920 alters the fundamental trajectory of the 20th century. It compresses the electronic age, shifting the "Digital Revolution" from the 1980s to the 1950s. Here is a trace of the implications through 1980. I.
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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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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.
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Ling 3.0 Flash Fin (free)2,560 words
Comprehensive Architecture Analysis: Real-Time Collaborative Document Editor CRITICAL: WebSocket Broadcasting Is Siloed Per-Server Problem: Each server maintains its own WebSocket connections. When User A (on Server 1) types, the change is only broadcast to clients connected to Server 1.
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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.…

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 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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Advanced Longevity Plan (Biohacker)

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

GLM 5941 words
This comprehensive 3-month protocol is designed for the advanced biohacker. It integrates synergistic systems: metabolic flexibility, hormetic stress, cognitive enhancement, and recovery optimization. Disclaimer: This plan is for informational purposes only and does not constitute medical advice.
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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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Our Verdict
GLM 5
GLM 5
Ling 3.0 Flash Fin (free)
Ling 3.0 Flash Fin (free)Runner-up

Not enough votes to call it. On the specs, GLM 5 has the edge: bigger model tier, major provider backing.

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 Fin (free)
Input
$0.000
Output
$0.000
Where to run it

9 hosts, cheapest first

GLM 58 hosts
HostInOutContextUptime
GGMI Cloudfp8$0.60 in·$1.92 out·203k·97.3% upSStreamLakefp8$0.60 in·$1.92 out·198k·99.7% upBaidu Qianfanfp8$0.70 in·$2.24 out·203k·99.8% upSSiliconFlowfp8$0.95 in·$2.55 out·205k·99.6% upAmazon Bedrock$1.00 in·$3.20 out·203k·97.5% upNNovitafp8$1.00 in·$3.20 out·203k·100% up
2 more hostsFewer hosts
VVenicefp8$1.00 in·$3.20 out·198k·98.5% upZ.aifp8$1.00 in·$3.20 out·203k·100% 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

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

GLM 5 costs $0.8/M input tokens and Ling 3.0 Flash Fin (free) costs $0/M input tokens. Ling 3.0 Flash Fin (free) is $0.80/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 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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