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  5. Mercury 2.5vsNemotron 3.5 Lightning
Updated Sep 2026

Mercury 2.5vsNemotron 3.5 Lightning

Mercury 2.5 is cheaper than Nemotron 3.5 Lightning at $0.04/M vs $0.08/M input tokens.

Mercury 2.5 and Nemotron 3.5 Lightning compared across 20 shared prompts
SpecMercury 2.5Nemotron 3.5 Lightning
Input price$0.04/M tokens$0.08/M tokens
Output price$0.15/M tokens$0.2/M tokens
Context window260K tokens1.0M tokens
Weights—Open
Free API (OpenRouter)NoYes (1 provider)
ReleasedSep 2026Aug 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…

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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Nemotron 3.5 Lightning316 words
Dish Name: The "Lazy" 5-Minute Crispy Pancake Pizza Concept: A quick, savory breakfast or snack that feels like a gourmet pizza but uses pantry staples. It relies on the magic of a simple batter to create a crispy base.
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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Nemotron 3.5 Lightning1,103 words
For the Experienced Software Engineer You’re used to debugging race conditions and optimizing latency; the idea that an LLM is "just predicting the next word" feels like a cop-out, especially when the output can be eerily coherent.
Read the full answer

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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Nemotron 3.5 Lightning588 words
Year-by-Year Financial Model (FY2026–FY2030) Assumptions & Calculations Logic: Interest: Calculated on beginning debt balance. Term Loan amortizes 1.0% annually (cash). Mezzanine accrues 2.0% PIK annually. Taxes: 25% of (EBITDA - Cash Interest). Tax shields applied to cash interest only.
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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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Nemotron 3.5 Lightning1,273 words
This architecture is a classic "Google Docs clone" design. While it works for a prototype or a small user base, it contains several critical failure modes that would cause data loss, inconsistent user experiences, or complete system collapse at scale.
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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Nemotron 3.5 Lightning869 words
Dish Name: The Alchemy of the Tundra: A Study in Contrasts Conceptual Narrative: This dish is a meditation on the extremes of the Arctic landscape and the human desire to tame it. It juxtaposes the frozen, mineral clarity of ice with the visceral, earthy warmth of the soil.
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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…

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
Nemotron 3.5 Lightning2,164 words
CEO Action Plan: 48-Hour Crisis Resolution Framework Guiding Principle: Patient safety and regulatory compliance are non-negotiable. Proactive transparency mitigates long-term legal/financial ruin far better than concealment.
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Our Verdict
Mercury 2.5
Mercury 2.5
Nemotron 3.5 Lightning
Nemotron 3.5 Lightning

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

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
2.0× cheaper
Output
$0.15
1.3× cheaper
Nemotron 3.5 Lightning
Input
$0.08
Output
$0.20

Mercury 2.5 is cheaper on both: 2.0× input, 1.3× output.

Where to run it

5 hosts, cheapest first

Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% up
Nemotron 3.5 Lightning4 hosts
HostInOutContextUptime
DDarkbloomint4$0.07 in·$0.18 out·262k·99.9% upCCoreWeavebf16$0.07 in·$0.20 out·262k·99.2% upPPhala$0.07 in·$0.20 out·262k·99.8% upDDeepInfrabf16$0.08 in·$0.20 out·262k·99.9% 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 Nemotron 3.5 Lightning is developed by NVIDIA. Mercury 2.5 has a 260K token context window vs Nemotron 3.5 Lightning'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 Nemotron 3.5 Lightning 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 Nemotron 3.5 Lightning costs $0.08/M input tokens. Mercury 2.5 is $0.04/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 Nemotron 3.5 Lightning 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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Mercury 2.520 outputs, specs and price
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