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  5. Mercury 2.5vsQwen3 Max
Updated Sep 2026

Mercury 2.5vsQwen3 Max

Mercury 2.5 is cheaper than Qwen3 Max at $0.04/M vs $1.2/M input tokens.

Mercury 2.5 and Qwen3 Max compared across 20 shared prompts
SpecMercury 2.5Qwen3 Max
Input price$0.04/M tokens$1.2/M tokens
Output price$0.15/M tokens$6/M tokens
Context window260K tokens256K tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedSep 2026Sep 2025
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…

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…
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Qwen3 Max219 words
Dish Name: Midnight Magic Mug Cake (A rich, chocolatey single-serving cake you whip up in minutes — perfect for late-night cravings or quick sweet fixes!) Ingredients (7 Pantry Staples): All-purpose flour – 4 tbsp Sugar – 3 tbsp Cocoa powder – 2 tbsp Baking powder – ¼ tsp Salt – pinch Milk – 3 tbsp (dairy or…
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…

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.
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Qwen3 Max845 words
For the Experienced Software Engineer Think of a large language model (LLM) as a massively scaled, probabilistic autocomplete system—except instead of just your last few words, it conditions predictions on everything you’ve typed so far, using a context window that can span tens of thousands of tokens.
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…

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.
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Qwen3 Max953 words
Dish: "Tide & Terroir" A symphony of coastal brine and alpine earth, where the ocean whispers to the mountain. Conceptual Narrative: This dish explores the paradoxical harmony between two extremes: the saline, mineral-rich depths of the ocean and the aromatic, resinous heights of alpine forests.
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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…

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.
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Qwen3 Max1,078 words
If the transistor had been invented in 1920—a full 27 years earlier than its actual 1947 debut—the ripple effects across technology, warfare, economics, and geopolitics would be profound and far-reaching.
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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…

Mercury 2.5610 words
3-Month Biohacking Longevity & Performance Plan Disclaimer: I am an AI, not a physician or certified health professional. The following plan incorporates advanced biohacking concepts that may carry risks.
Read the full answer
Qwen3 Max1,138 words
The Chronos Protocol: A 3-Month Cutting-Edge Longevity & Performance Optimization Plan Core Philosophy: Synergistic integration of mitochondrial optimization, autophagy enhancement, epigenetic regulation, and systemic resilience through precise, data-driven interventions.
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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…

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.
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Qwen3 Max1,056 words
Critical Issues in the Collaborative Document Editor Architecture Last-Write-Wins with Client Clocks (Critical) Problem: Client clocks are unreliable and can be out of sync by seconds, minutes, or even hours.
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Our Verdict
Mercury 2.5
Mercury 2.5
Qwen3 Max
Qwen3 Max

Not enough votes to call it. On the specs, nothing separates them.

Mercury 2.5 costs 40x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Mercury 2.5
Input
$0.04
30× cheaper
Output
$0.15
40× cheaper
Qwen3 Max
Input
$1.20
Output
$6.00

Mercury 2.5 is cheaper on both: 30× input, 40× output.

Where to run it

2 hosts

Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% up
Qwen3 Max1 host
HostInOutContextUptime
Alibaba Cloud$0.78 in·$3.90 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

Mercury 2.5 is developed by Inception while Qwen3 Max is developed by Qwen. Mercury 2.5 has a 260K token context window vs Qwen3 Max's 256K. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.

It depends on your use case. Mercury 2.5 and Qwen3 Max 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.

Mercury 2.5 costs $0.04/M input tokens and Qwen3 Max costs $1.2/M input tokens. Mercury 2.5 is $1.16/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 Mercury 2.5 and Qwen3 Max 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

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Rival
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