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  5. Mercury 2.5vsQwen3 Next 80B A3B Instruct
Updated Sep 2026

Mercury 2.5vsQwen3 Next 80B A3B Instruct

Mercury 2.5 is cheaper than Qwen3 Next 80B A3B Instruct at $0.04/M vs $0.15/M input tokens.

Mercury 2.5 and Qwen3 Next 80B A3B Instruct compared across 20 shared prompts
SpecMercury 2.5Qwen3 Next 80B A3B Instruct
Input price$0.04/M tokens$0.15/M tokens
Output price$0.15/M tokens$1.5/M tokens
Context window260K tokens66K tokens
Weights—Open
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 Next 80B A3B Instruct269 words
Recipe Name: Golden Honey-Sesame Toast Bites A crunchy, sweet-savory snack that’s warm, glossy, and addictive—perfect for breakfast, dessert, or a quick treat. Ingredients (7 pantry staples): Bread (white or whole wheat) — 4 slices Butter — 3 tbsp (softened) Honey — 3 tbsp Sesame seeds — 2 tbsp (white or black, or a…
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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 Next 80B A3B Instruct917 words
1. To the Experienced Software Engineer You’re right to be skeptical. “Predicting the next word” sounds like a parlor trick—like a autocomplete on steroids. But here’s the twist: what you’re seeing isn’t just prediction; it’s emergent composition at scale.
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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 Next 80B A3B Instruct1,493 words
This is a fascinating counterfactual: What if the transistor had been invented in 1920 instead of 1947? Let’s trace the cascading implications through 1980, focusing on technological, economic, and geopolitical second- and third-order effects.
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Adversarial Contract Review

Here is a contract for a software consulting engagement: --- SOFTWARE CONSULTING AGREEMENT This Agreement is entered into between TechCorp…

Mercury 2.5501 words
Here is an analysis of the contract clauses that pose significant risk to the contractor, along with suggested modifications and legal reasoning. Scope and Compensation (Clause 1) Risk: The client can expand the project indefinitely without paying extra.
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Qwen3 Next 80B A3B Instruct2,159 words
This contract is heavily skewed in favor of the Client and contains multiple clauses that are legally problematic, exploitative, and potentially unenforceable under U.S. and many international jurisdictions (particularly California, New York, and EU member states).
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Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

Mercury 2.5403 words
1. Simplified Year-by-Year LBO Model (FY2026–FY2030) Entry Assumptions: Enterprise Value (EV): $120m × 12.0x = $1,440m Transaction Fees: $1,440m × 2.0% = $28.8m Total Debt at Close: $120m × 5.5x = $660m Term Loan: $120m × 4.0x = $480m Mezzanine: $120m × 1.5x = $180m Equity Required: $1,440m (EV) + $28.8m (Fees) − $660m…
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Qwen3 Next 80B A3B Instruct980 words
HarborTech Services (HTS) – 5-Year LBO Underwriting (FY2026–FY2030) All figures in $ millions. Rounded to 1 decimal for clarity. 1. Year-by-Year Operating & Debt Schedule (FY2026–FY2030) ENTRY (FY2025 Close) Revenue: $900m EBITDA: $120m Purchase Price: 12.0x $120m = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m…
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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 Next 80B A3B Instruct1,368 words
Dish Name: “The Whisper of the Forest Floor” Conceptual Narrative: This dish is a poetic homage to the hidden ecosystems beneath ancient temperate forests — where moss, fungi, and decaying leaf litter transform into nutrient-rich humus, sustaining life in quiet, profound cycles.
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Our Verdict
Mercury 2.5
Mercury 2.5
Qwen3 Next 80B A3B Instruct
Qwen3 Next 80B A3B InstructRunner-up

Not enough votes to call it. On the specs, Mercury 2.5 has the edge: newer, bigger context window.

Mercury 2.5 costs 10x 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
3.8× cheaper
Output
$0.15
10× cheaper
Qwen3 Next 80B A3B Instruct
Input
$0.15
Output
$1.50

Mercury 2.5 is cheaper on both: 3.8× input, 10× output.

Where to run it

6 hosts, cheapest first

Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% up
Qwen3 Next 80B A3B Instruct5 hosts
HostInOutContextUptime
DDeepInfrafp8$0.09 in·$1.10 out·262k·99.8% upAlibaba Cloud$0.10 in·$0.78 out·131k·100% upPParasailfp8$0.10 in·$1.10 out·262k·100% upGoogle Vertex AI$0.15 in·$1.20 out·262k·100% upNNovitabf16$0.15 in·$1.50 out·131k·99.5% 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 Next 80B A3B Instruct is developed by Qwen. Mercury 2.5 has a 260K token context window vs Qwen3 Next 80B A3B Instruct's 66K. 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 Next 80B A3B Instruct 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 Next 80B A3B Instruct costs $0.15/M input tokens. Mercury 2.5 is $0.11/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 Next 80B A3B 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

Mercury 2.5 logo
Mercury 2.520 outputs, specs and price
Qwen3 Next 80B A3B Instruct logo
Qwen3 Next 80B A3B Instruct59 outputs, specs and price
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