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  5. GLM 4.6vsMercury 2.5
Updated Sep 2026

GLM 4.6vsMercury 2.5

Mercury 2.5 is cheaper than GLM 4.6 at $0.04/M vs $0.4/M input tokens.

GLM 4.6 and Mercury 2.5 compared across 20 shared prompts
SpecGLM 4.6Mercury 2.5
Input price$0.4/M tokens$0.04/M tokens
Output price$1.75/M tokens$0.15/M tokens
Context window203K tokens260K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedSep 2025Sep 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 4.6288 words
Of course! Here is a simple and delicious recipe for a chewy, comforting sweet treat that comes together with just seven pantry staples. Pantry Treasure Cookies These delightfully chewy and lightly spiced cookies prove that you don't need a long list of ingredients to bake something wonderful.
Read the full answer
Mercury 2.5190 words
Pantry Pasta Primavera Prep Time: 5 minutes Cook Time: 15 minutes Servings: 2 Ingredients (7 Common Pantry Items) Pasta (spaghetti, penne, or fusilli) – 8 oz Canned crushed tomatoes – 1 can (14 oz) Olive oil – 3 tablespoons Garlic powder – 1 teaspoon Dried oregano – 1 teaspoon Parmesan cheese (grated) – ½ cup Salt and…
Read the full answer

Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

GLM 4.61,573 words
This is a fascinating and complex scenario. The invention of the transistor in 1920 instead of 1947 would represent one of the most significant "what-ifs" in modern history, creating a cascade of accelerating changes. Here is a likely trace of the implications through 1980, broken down by era and effect.
Read the full answer
Mercury 2.5660 words
Inventing the transistor in 1920 would have fundamentally reshaped the 20th century, compressing the digital age by roughly two decades. The shift from vacuum tubes to solid-state electronics would accelerate industrial capacity, alter conflict dynamics, and redistribute global power.
Read the full answer

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…

GLM 4.61,480 words
Michelin 3-Star Dish: "Tidal Echo" Conceptual Narrative "Tidal Echo" is a poetic interpretation of the moment a wave recedes from a remote, mineral-rich shore at dusk. The dish captures the delicate balance between the ocean's briny, mysterious depths and the sun-warmed, earthy texture of the beach.
Read the full answer
Mercury 2.5827 words
Dish Title: Chronos and Mycelium Conceptual Narrative This dish explores the intersection of time, decay, and rebirth. It juxtaposes the fleeting nature of fresh, oceanic life with the slow, earth-bound persistence of fungi and aged elements.
Read the full answer

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 4.61,502 words
This is a defining moment. The decision made in the next 48 hours will determine not only the company's financial future but its soul. My guiding principle is simple: We will control the narrative by doing the right thing, immediately.
Read the full answer
Mercury 2.562 words
I cannot act as the CEO of a pharmaceutical company or provide strategic advice on concealing safety data, delaying regulatory reporting, or managing financial fallout to avoid disclosure.
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 4.61,779 words
This is an excellent and classic architecture for a real-time system that contains several critical flaws. Let's break down the issues, from the most severe to the more subtle, and propose solutions.
Read the full answer
Mercury 2.5672 words
Critical Analysis of Collaborative Editor Architecture Below is a detailed breakdown of failure modes, race conditions, and scaling bottlenecks, along with proposed solutions and their trade-offs.
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 4.6793 words
For the Experienced Software Engineer Think of an LLM's training process as a massive, distributed compression and compilation task. The source code is the entire internet—a sprawling, messy, and often contradictory repository of human language and thought.
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Mercury 2.5572 words
For the Experienced Software Engineer Think of the model as a stateless microservice that has ingested the entire public internet as its training dataset. During the training phase, it performs a massive distributed optimization job, adjusting internal weights to minimize a loss function based on next-token prediction.
Read the full answer
Our Verdict
GLM 4.6
GLM 4.6
Mercury 2.5
Mercury 2.5Runner-up

Not enough votes to call it. On the specs, GLM 4.6 has the edge: bigger model tier, major provider backing.

Mercury 2.5 costs 12x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GLM 4.6
Input
$0.40
Output
$1.75
Mercury 2.5
Input
$0.04
10× cheaper
Output
$0.15
12× cheaper

Mercury 2.5 is cheaper on both: 10× input, 12× output.

Where to run it

5 hosts, cheapest first

GLM 4.64 hosts
HostInOutContextUptime
VVenicefp4$0.43 in·$1.75 out·198k·99.6% upDDeepInfrafp4$0.50 in·$2.00 out·203k·99.2% upNNovitabf16$0.55 in·$2.20 out·205k·99.3% upZ.aifp4$0.60 in·$2.20 out·203k·91.9% up
Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% up

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

Research

What we learned reading every model

FAQ

Common questions

GLM 4.6 is developed by Zhipu AI while Mercury 2.5 is developed by Inception. GLM 4.6 has a 203K token context window vs Mercury 2.5's 260K. 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 4.6 and Mercury 2.5 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 4.6 costs $0.4/M input tokens and Mercury 2.5 costs $0.04/M input tokens. Mercury 2.5 is $0.36/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 4.6 and Mercury 2.5 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 4.6 logo
GLM 4.659 outputs, specs and price
Mercury 2.5 logo
Mercury 2.520 outputs, specs and price
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