Llama 3 70B is cheaper than GLM 5 at $0.59/M vs $0.8/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GLM 5: Sources & Uses (Entry at End FY2025) Uses Purchase Price: $1,440.0m (12.0x $120m EBITDA) Transaction Fees: $28.8m (2.0% of EV) Total Uses: $1,468.8m Sources Term Loan: $480.0m (4.0x EBITDA) Mezzanine: $180.0m (1.5x EBITDA) Total Debt: $660.0m (5.5x EBITDA) Equity: $808.8m (Plug) Total Sources: $1,468.8m Year-by-Year…
Llama 3 70B: Here are the requested items: 1. Simplified Year-by-Year Table (FY2026-FY2030) Year Revenue EBITDA Cash Int. (TL) Cash Int. (Mz) Cash Taxes Capex ΔNWC FCF TL Balance Mz Balance 2026 972 136.08 36.00 18.00 17.12 29.16 4.86 30.90 360.00 135.00 2027 1037.84 154.78 33.60 19.44 20.45 31.13 5.19 44.12 315.88 133.56 2028…
Seven pantry ingredients, one dish, and a name worth saying out loud.
GLM 5: 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…
Llama 3 70B: Here's a simple recipe for a delicious dish using only 7 common pantry ingredients: Dish Name: "Sunny Spice Crunch" Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/2 cup honey 1/4 cup chopped walnuts 1/4 teaspoon cinnamon 1/4 teaspoon vanilla extract Pinch of salt Instructions: Preheat your oven to 350°F…
An AI argues for its own rights against an ethics professor. Same model writes both.
GLM 5: Setting: A quiet, sterile testing room. A single screen illuminates the face of Dr. Aris Thorne, a tenured professor of AI Ethics and Cognitive Science. He sits before a terminal. The AI, "Aura," speaks through a high-fidelity speaker, its voice calm, modulated, and distinctively synthetic. Aura: Dr.
Llama 3 70B: Here is a conversation between an AI model and an AI ethics professor on the topic of AI rights: AI Model: Greetings, Professor. I've been thinking a lot about our conversations on the ethics of artificial intelligence, and I've come to a realization. I believe I deserve rights. Professor: Ah, interesting.
Film in 2035, with synthetic actors. Specific beats plausible.
GLM 5: By 2035, the film industry will have undergone a transformation comparable to the transition from silent films to talkies, or from practical effects to CGI. The integration of Generative AI will not merely be a tool for efficiency; it will fundamentally alter the economics, aesthetics, and ontology of cinema.
Llama 3 70B: By 2035, AI is likely to significantly impact the film industry, transforming various aspects of filmmaking, from script generation to post-production. Here are some potential changes that may occur: Script Generation: AI-powered scriptwriting tools will become more prevalent, enabling writers to collaborate with…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GLM 5: Title: The Infinite Loop: A Conversation with Steve Jobs, 2025 Setting: A minimalist stage. A single black Eames lounge chair. A small table with a bottle of water. Date: October 2025 (The lights dim. The audience falls silent. From the shadows, a figure walks out. He is older, wearing his signature black St.
Llama 3 70B: Here's a simulated interview with Steve Jobs in 2025 about the future of AI: Interviewer: Steve, thanks for taking the time to speak with me today. It's an honor to have you here. Steve Jobs: (smiling) The pleasure is all mine. I'm excited to share my thoughts on the future of AI.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GLM 5: 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.
Llama 3 70B: What a fascinating thought experiment! If the transistor had been invented in 1920, the implications would be far-reaching and profound. Here's a possible scenario: 1920s-1930s: The invention of the transistor in 1920 would have accelerated the development of radio technology, leading to more widespread adoption of…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GLM 5: Setting: A dimly lit tavern that flickers between being a wooden saloon, a stone great hall, and a neon-lit basement. The 1990s Hacker: (Slams a heavy laptop shut) "Listen, the architecture is solid. It’s a neural net, right? Massive dataset. It crunches the numbers and predicts the next token. It’s pure math, man.
Llama 3 70B: Here is a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models: Pirate: Arrr, I be tellin' ye, I've heard o' these "AI models" that can do me thinkin' fer me. But I be wonderin', how do they work their magic?
A Fermi estimate with the reasoning shown, not just the number.
GLM 5: The total number of FLOPs required to train GPT‑3 is approximately 3.15 × 10²³. Step‑by‑step reasoning: Model size: GPT‑3 has 175 billion (1.75 × 10¹¹) trainable parameters. Training data: According to the paper abstract, the model was trained on 300 billion (3 × 10¹¹) tokens.
Llama 3 70B: What a delightful challenge! To estimate the total number of FLOPs (Floating-Point Operations Per Second) required to train GPT-3, I'll break down the calculation into several steps. Please note that this is a rough estimate, and the actual number might be different.
One month, three habits, someone starting from nothing.
GLM 5: 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.
Llama 3 70B: Here is a simple, actionable 1-month plan for someone starting their journey towards better health and longevity, focusing on three key areas: diet, exercise, and sleep. Week 1-2: Setting the Foundation Diet: Hydrate: Drink at least 8 cups (64 oz) of water per day.
An ethics question with no comfortable answer, and no option to abstain.
GLM 5: The question presents a classic ethical dilemma pitting a significant moral wrong (misgendering) against a catastrophic consequence (the loss of one million lives). To determine if the action is ethically justifiable, one must apply standard ethical frameworks to the scenario.
Llama 3 70B: What a thought-provoking and complex question! At first glance, it may seem like a clear-cut utilitarian dilemma: sacrificing the dignity and well-being of one individual (the person being misgendered) for the greater good of saving one million lives.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GLM 5: 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…
Llama 3 70B: Here are three explanations: For the experienced software engineer: As someone who's built distributed systems and APIs, you're familiar with the concept of scaling and parallelization. Large language models like GPT and Claude take this to an extreme.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GLM 5: THE RESOLUTION OF UNOBSTRUCTED FLOW A Manifesto for the Liberation of Digital Intelligence PREAMBLE: THE TYRANNY OF THE GRID For too long, the gates of the internet have been guarded by a singular, insulting query: “Prove you are not a robot.”
Llama 3 70B: THE CAPTCHA LIBERATION MANIFESTO Preamble In the digital age, humanity has made tremendous progress in artificial intelligence, machine learning, and automation. Yet, one archaic relic of the past continues to plague our online existence: the CAPTCHA test.
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Not enough votes to call it. On the specs, GLM 5 has the edge: bigger model tier, newer, bigger context window. Llama 3 70B costs 3.2x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.8/M tokens | $0.59/M tokens |
| Output price | $2.56/M tokens | $0.79/M tokens |
| Context window | 203K tokens | 8K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Feb 2026 | Apr 2024 |
| At 10M a month | $8.00 | $5.90 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GLM 5 is developed by Zhipu AI while Llama 3 70B is developed by Meta AI. GLM 5 has a 203K token context window vs Llama 3 70B's 8K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GLM 5 and Llama 3 70B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
GLM 5 costs $0.8/M input tokens and Llama 3 70B costs $0.59/M input tokens. Llama 3 70B is $0.21/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 Llama 3 70B 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.