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  5. GLM 5.3 FlashXvsLlama 3.1 70B (Instruct)
Updated Sep 2026

GLM 5.3 FlashXvsLlama 3.1 70B (Instruct)

GLM 5.3 FlashX is cheaper than Llama 3.1 70B (Instruct) at $0.37/M vs $0.59/M input tokens.

GLM 5.3 FlashX and Llama 3.1 70B (Instruct) compared across 12 shared prompts
SpecGLM 5.3 FlashXLlama 3.1 70B (Instruct)
Input price$0.37/M tokens$0.59/M tokens
Output price$1.25/M tokens$0.79/M tokens
Context window1.0M tokens128K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2024
Side by side

Same prompt, both answers

Opening lines from 6 of the 12 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 5.3 FlashX172 words
Golden Honey Garlic Chickpea Crunch A crispy, sweet-savory skillet dish that works as a snack, side, or topping for rice. Ingredients (7): 1 can chickpeas (drained, patted dry) 3 tbsp honey 3 tbsp soy sauce 3 cloves garlic (minced) 2 tbsp olive oil ½ tsp red pepper flakes 2 tbsp sesame seeds (or crushed peanuts) Prep…
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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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Debug This Architecture

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

GLM 5.3 FlashX1,306 words
Architecture Review: Real-Time Collaborative Editor This architecture has fundamental flaws that would break core functionality, plus scalability issues. Let me go from critical to scaling concerns.
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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.
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 5.3 FlashX347 words
1-Month Health & Longevity Starter Plan Week 1: Build the Foundation 🥗 Diet Add one vegetable or fruit to every meal (don't restrict anything yet) Drink a glass of water when you wake up each morning 🏃 Exercise Take a 10–15 minute walk daily (same time each day builds the habit) Do 2 sets of 5 squats and 10 wall…
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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…

GLM 5.3 FlashX1,174 words
48-Hour Action Plan: Patient Safety First, Managed Transparency Second Core Decision (Stated Up Front) We report to regulators immediately—voluntarily—and we disclose on the earnings call. The math is brutal and clear: ~500 patients could develop liver failure over 5 years at current prescribing rates (4M ÷ 8,000).
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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.
Read the full answer

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 5.3 FlashX1,267 words
The Skeptical Software Engineer Yes, at inference time an LLM really is just "predict the next token, repeat" — a deterministic function (plus sampling noise) that maps a sequence of tokens to a probability distribution.
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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.
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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 5.3 FlashX1,492 words
Counterfactual: The Transistor in 1920 This is a fun one to work through carefully. Let me establish the premise, then trace second- and third-order effects. The Premise Assume point-contact or early junction transistor physics is discovered ~1920 (say, by accident in vacuum tube/semiconductor rectifier research—the…
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Llama 3.1 70B (Instruct)673 words
If the transistor had been invented in 1920 instead of 1947, the world would likely have been transformed in profound ways, with far-reaching technological, economic, and geopolitical implications.
Read the full answer
Our Verdict
GLM 5.3 FlashX
GLM 5.3 FlashX
Llama 3.1 70B (Instruct)
Llama 3.1 70B (Instruct)Runner-up

Not enough votes to call it. On the specs, GLM 5.3 FlashX has the edge: newer, bigger context window.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3 FlashX
Input
$0.37
1.6× cheaper
Output
$1.25
Llama 3.1 70B (Instruct)
Input
$0.59
Output
$0.79
1.6× cheaper

GLM 5.3 FlashX wins input (1.6× cheaper)·Llama 3.1 70B (Instruct) wins output (1.6× cheaper)

Where to run it

3 hosts, cheapest first

GLM 5.3 FlashX1 host
HostInOutContextUptime
Z.aifp8$0.37 in·$1.25 out·1M·100% up
Llama 3.1 70B (Instruct)2 hosts
HostInOutContextUptime
DDeepInfrafp8$0.40 in·$0.40 out·131k·96.7% upAmazon Bedrock$0.72 in·$0.72 out·131k·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 5.3 FlashX is developed by Zhipu AI while Llama 3.1 70B (Instruct) is developed by Meta AI. GLM 5.3 FlashX has a 1.0M token context window vs Llama 3.1 70B (Instruct)'s 128K. You can compare their actual outputs across 12 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 FlashX and Llama 3.1 70B (Instruct) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 12 challenges so you can judge which fits your needs best.

GLM 5.3 FlashX costs $0.37/M input tokens and Llama 3.1 70B (Instruct) costs $0.59/M input tokens. GLM 5.3 FlashX is $0.22/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 5.3 FlashX 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

GLM 5.3 FlashX logo
GLM 5.3 FlashX12 outputs, specs and price
Llama 3.1 70B (Instruct) logo
Llama 3.1 70B (Instruct)56 outputs, specs and price
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