Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed
  1. Home
  2. /
  3. Compare
  4. /
  5. Ling 2.6 FlashvsMercury 2.5
Updated Sep 2026

Ling 2.6 FlashvsMercury 2.5

Ling 2.6 Flash is cheaper than Mercury 2.5 at $0/M vs $0.04/M input tokens.

Ling 2.6 Flash and Mercury 2.5 compared across 20 shared prompts
SpecLing 2.6 FlashMercury 2.5
Input priceFree$0.04/M tokens
Output priceFree$0.15/M tokens
Context window262K tokens260K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 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…

Ling 2.6 Flash181 words
Dish: Sunshine Skillet Cakes Ingredients (7 total): 1 cup rolled oats (not instant) 1/2 cup canned corn (drained) 1/4 cup canned black beans (rinsed & drained) 1 large egg 1/4 cup shredded cheddar cheese 1 tsp chili powder Salt to taste Estimated Time: Prep: 5 minutes Cook: 15 minutes Total: 20 minutes Instructions…
Read the full answer
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

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…

Ling 2.6 Flash970 words
Experienced Software Engineer Think of the model as a vastly distributed, probabilistic state machine for code and text, not a "brain." Instead of explicit rules for "if user sends X, do Y," it learns a massive distribution over next-token completions from data, storing those dependencies as weights across many…
Read the full answer
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

Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

Ling 2.6 Flash921 words
Excellent question. Shifting the invention of the transistor from 1947 to 1920 is a profound "Great Divergence" scenario. A working, mass-producible transistor in 1920 would trigger a cascade of acceleration, fundamentally rewriting the 20th century. Here’s a trace of the implications through 1980.
Read the full answer
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.
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) –…

Ling 2.6 Flash957 words
Below is a concise, math-forward underwriting package for HarborTech Services (HTS) LBO. Simplified 5-year cash flow (FY2026–FY30) Key inputs Entry EV = 12.0× FY25 EBITDA = 12.0×120 = $1,440m Transaction fees (2% of EV) = $28.8m → funded 100% by equity at close Starting cash = $0 Total leverage at close = 5.5× EBITDA =…
Read the full answer
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…
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.…

Ling 2.6 Flash609 words
Here are the three weakest claims in the pitch, along with the reasoning and suggested improvements: Weak Claim #1: "94% accuracy." Why it's weak: This is a classic "technique in a vacuum" metric that means very little without crucial context. It is highly likely inflated and lacks transparency.
Read the full answer
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

Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

Ling 2.6 Flash736 words
Comprehensive 3-Month Longevity Plan for a Biohacker Month 1: Foundation and Baseline Assessment 1. Supplement Stack: Vitamin D3 + K2: 5000 IU D3 + 100 mcg K2 daily. Omega-3 (Fish Oil): 1-2 grams of EPA/DHA daily. Magnesium Glycinate: 200-400 mg before bed. NAD+ Precursors (NMN or NR): 250-500 mg daily.
Read the full answer
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
Our Verdict
Ling 2.6 Flash
Ling 2.6 Flash
Mercury 2.5
Mercury 2.5

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

Ling 2.6 Flash
Input
$0.000
Output
$0.000
Mercury 2.5
Input
$0.04
Output
$0.15
Where to run it

1 host

Ling 2.6 Flash

No hosts listed on OpenRouter.

Mercury 2.51 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% up

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

Research

What we learned reading every model

FAQ

Common questions

Ling 2.6 Flash is developed by inclusionAI while Mercury 2.5 is developed by Inception. Ling 2.6 Flash has a 262K token context window vs Mercury 2.5's 260K. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.

It depends on your use case. Ling 2.6 Flash and Mercury 2.5 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.

Ling 2.6 Flash costs $0/M input tokens and Mercury 2.5 costs $0.04/M input tokens. Ling 2.6 Flash 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 Ling 2.6 Flash and Mercury 2.5 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.

Keep exploring

More comparisons

Against the newest arrivals

Ling 2.6 Flash logoDeepSeek V4 Flash Vision Exp logo
Ling 2.6 Flash vs DeepSeek V4 Flash Vision ExpLanded Sep 2026
Mercury 2.5 logoSolar Pro 4 logo
Mercury 2.5 vs Solar Pro 4Landed Sep 2026
Ling 2.6 Flash logoHy3 logo
Ling 2.6 Flash vs Hy3Landed Sep 2026
Mercury 2.5 logoQwen3.7 Flash logo
Mercury 2.5 vs Qwen3.7 FlashLanded Sep 2026
Ling 2.6 Flash logoLing 3.0 Flash logo
Ling 2.6 Flash vs Ling 3.0 FlashLanded Sep 2026
Mercury 2.5 logoMuse Glimmer 30B logo
Mercury 2.5 vs Muse Glimmer 30BLanded Sep 2026
Ling 2.6 Flash logoGLM 5.3 logo
Ling 2.6 Flash vs GLM 5.3Landed Sep 2026
Mercury 2.5 logoTernary Bonsai 2 27B logo
Mercury 2.5 vs Ternary Bonsai 2 27BLanded Sep 2026

Same lab, same size, long tail

Ling 2.6 Flash logoLing 3.0 Flash Fin (free) logo
Ling 2.6 Flash vs Ling 3.0 Flash Fin (free)Same lab
Ling 2.6 Flash logoLing 3.0 Flash Sante (free) logo
Ling 2.6 Flash vs Ling 3.0 Flash Sante (free)Same lab
Mercury 2.5 logoMercury 2.5 Preview logo
Mercury 2.5 vs Mercury 2.5 PreviewSame lab
Mercury 2.5 logoMercury logo
Mercury 2.5 vs MercurySame lab
Ling 2.6 Flash logoQwen3.6 35B A3B logo
Ling 2.6 Flash vs Qwen3.6 35B A3BNew provider
Ling 2.6 Flash logoQwen3.6 Flash logo
Ling 2.6 Flash vs Qwen3.6 FlashNew provider
Ling 2.6 Flash logoQwen3.6 Max Preview logo
Ling 2.6 Flash vs Qwen3.6 Max PreviewNew provider
Mercury 2.5 logoQwen3.6 Plus Preview (free) logo
Mercury 2.5 vs Qwen3.6 Plus Preview (free)Same size

Model pages

Ling 2.6 Flash logo
Ling 2.6 Flash58 outputs, specs and price
Mercury 2.5 logo
Mercury 2.520 outputs, specs and price
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed