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  5. Mercury 2.5vsQwen3.6 35B A3B
Updated Sep 2026

Mercury 2.5vsQwen3.6 35B A3B

Mercury 2.5 is cheaper than Qwen3.6 35B A3B at $0.04/M vs $0.1612/M input tokens.

Mercury 2.5 and Qwen3.6 35B A3B compared across 20 shared prompts
SpecMercury 2.5Qwen3.6 35B A3B
Input price$0.04/M tokens$0.1612/M tokens
Output price$0.15/M tokens$0.9653/M tokens
Context window260K tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedSep 2026Apr 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 prompts both answered. Formatting stripped, words untouched.

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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Qwen3.6 35B A3B1,149 words
To trace this counterfactual plausibly, we must first acknowledge a critical constraint: invention ≠ adoption. In 1920, semiconductor physics, crystal growth, doping techniques, photolithography, and clean-room manufacturing did not exist.
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Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

Mercury 2.5325 words
Here is a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. This guide focuses on three foundational pillars: Nutrition, Movement, and Sleep. Week 1: Awareness & Small Wins Goal: Build habits without overwhelming yourself.
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Qwen3.6 35B A3B788 words
Here is a simple, actionable 1-month plan designed for beginners. The focus is on consistency over intensity. For longevity, small, sustainable habits compound over time. The Golden Rule: If you miss a day, don't quit. Just get back on track the next day. Aim for progress, not perfection.
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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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Qwen3.6 35B A3B1,632 words
Disclaimer: I am an AI assistant, not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contract law varies significantly by jurisdiction (e.g., California vs. New York vs. EU).
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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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Qwen3.6 35B A3B236 words
🍜 Golden Honey-Garlic Snap Noodles A quick, sticky-yet-chewy noodle dish that balances sweet, salty, and spicy flavors. It's comforting, fast, and uses ingredients you likely already have.
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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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Qwen3.6 35B A3B538 words
Simplified Year-by-Year Model (FY2026–FY2030) All figures in $m. Assumptions: TL amort = 1.0% of beginning balance; Mezz PIK compounds to principal; ΔNWC = 0.5% of incremental revenue; Cash Tax = 25% × max(0, EBITDA – Cash Interest).
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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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Qwen3.6 35B A3B775 words
For the Experienced Software Engineer Training an LLM is essentially a massively parallelized optimization job. You feed billions of text tokens into a transformer architecture, which computes a differentiable function across ~100B parameters.
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Our Verdict
Mercury 2.5
Mercury 2.5
Qwen3.6 35B A3B
Qwen3.6 35B A3BRunner-up

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

Mercury 2.5 costs 6.4x 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
4.0× cheaper
Output
$0.15
6.4× cheaper
Qwen3.6 35B A3B
Input
$0.16
Output
$0.97

Mercury 2.5 is cheaper on both: 4.0× input, 6.4× output.

Where to run it

10 hosts, cheapest first

Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·99.9% up
Qwen3.6 35B A3B9 hosts
HostInOutContextUptime
DDarkbloomfp4$0.05 in·$0.70 out·262k·100% upAAkashMLfp8$0.10 in·$0.90 out·262k·100% upVVenicefp8$0.10 in·$1.00 out·256k·99.3% upPParasailfp8$0.15 in·$1.00 out·262k·99.9% upAAtlasCloudfp8$0.19 in·$1.11 out·262k·99.5% upPPhala$0.20 in·$1.27 out·262k·99.7% up
3 more hostsFewer hosts
SSiliconFlowfp8$0.24 in·$1.80 out·262k·99.7% upCCoreWeavefp8$0.25 in·$1.25 out·262k·99.6% upDDeepInfrafp8degraded$0.10 in·$0.95 out·262k·96.5% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

Mercury 2.5 is developed by Inception while Qwen3.6 35B A3B is developed by Qwen. Mercury 2.5 has a 260K token context window vs Qwen3.6 35B A3B's 262K. 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 Qwen3.6 35B A3B 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 Qwen3.6 35B A3B costs $0.1612/M input tokens. Mercury 2.5 is $0.12/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 Qwen3.6 35B A3B 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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