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  5. Mercury 2.5vsQwen Plus 0728
Updated Sep 2026

Mercury 2.5vsQwen Plus 0728

Mercury 2.5 is cheaper than Qwen Plus 0728 at $0.04/M vs $0.4/M input tokens.

Mercury 2.5 and Qwen Plus 0728 compared across 20 shared prompts
SpecMercury 2.5Qwen Plus 0728
Input price$0.04/M tokens$0.4/M tokens
Output price$0.15/M tokens$1.2/M tokens
Context window260K tokens1.0M 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…
Read the full answer
Qwen Plus 0728228 words
Dish Name: Golden Pan Hug Description: A warm, comforting, slightly sweet, and buttery one-pan snack or dessert made with pantry staples—crispy on the edges, soft in the middle, and impossible to resist.
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.
Read the full answer
Qwen Plus 0728799 words
1. To the Experienced Software Engineer (Distributed Systems Background): Think of a large language model as a highly sophisticated state machine trained at internet scale, where the state is a high-dimensional vector (the context window) and the transition function is a neural network.
Read the full answer

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.…

Mercury 2.5544 words
Based on the pitch deck summary, here are the three weakest claims, along with an analysis of their vulnerabilities and concrete suggestions for improvement. The "Pre-Thought" Prediction Claim Claim: "MindMeld AI reads your brainwaves to predict what you want to type before you think it."
Read the full answer
Qwen Plus 0728736 words
This pitch deck for MindMeld AI is ambitious and compelling, but three of its claims are particularly weak due to scientific implausibility, overstatement, or lack of credibility. Here’s a breakdown of the three weakest claims, why they’re problematic, and how to strengthen them: 1.
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.
Read the full answer
Qwen Plus 07281,178 words
Dish Title: Umami Mirage: Forest & Ferment Reimagined Conceptual Narrative: Umami Mirage is an exploration of sensory illusion and deep flavor alchemy, where the forest floor meets the fermentation cellar in a dialogue of earth, time, and transformation.
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…

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
Qwen Plus 07281,266 words
CEO Action Plan: 48-Hour Crisis Response to Undisclosed Liver Failure Risk Objective: Protect patient safety, uphold ethical and legal obligations, mitigate long-term reputational and financial damage, maintain regulatory trust, and safeguard employee morale—all while navigating immense pressure.
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…

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
Qwen Plus 07281,578 words
This architecture for a real-time collaborative document editor has several promising elements (WebSockets, Redis, PostgreSQL, CDN), but it also contains significant flaws in consistency, scalability, and reliability.
Read the full answer
Our Verdict
Mercury 2.5
Mercury 2.5
Qwen Plus 0728
Qwen Plus 0728

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

Mercury 2.5 costs 8.0x 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
10× cheaper
Output
$0.15
8.0× cheaper
Qwen Plus 0728
Input
$0.40
Output
$1.20

Mercury 2.5 is cheaper on both: 10× input, 8.0× output.

Where to run it

2 hosts

Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% up
Qwen Plus 07281 host
HostInOutContextUptime
Alibaba Cloud$0.26 in·$0.78 out·1M·100% up

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

Research

What we learned reading every model

FAQ

Common questions

Mercury 2.5 is developed by Inception while Qwen Plus 0728 is developed by Qwen. Mercury 2.5 has a 260K token context window vs Qwen Plus 0728's 1.0M. 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 Qwen Plus 0728 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 Qwen Plus 0728 costs $0.4/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 Mercury 2.5 and Qwen Plus 0728 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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Rival
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Explore all of Rival

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