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  5. GPT-6 AstravsMercury 2.5
Updated Sep 2026

GPT-6 AstravsMercury 2.5

Mercury 2.5 is cheaper than GPT-6 Astra at $0.04/M vs $10/M input tokens.

GPT-6 Astra and Mercury 2.5 compared across 20 shared prompts
SpecGPT-6 AstraMercury 2.5
Input price$10/M tokens$0.04/M tokens
Output price$50/M tokens$0.15/M tokens
Context window1.1M tokens260K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedSep 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…

GPT-6 Astra200 words
Cinnamon Hug Cookies Buttery cookies with crisp edges, soft centers, and a cozy cinnamon flavor. Makes: About 20 cookies Prep: 10 minutes Cook: 10–12 minutes per batch Ingredients — exactly 7 1½ cups all-purpose flour ¾ cup granulated sugar, divided ½ cup salted butter, softened 1 large egg 1 teaspoon vanilla extract ½…
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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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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…

GPT-6 Astra989 words
For an experienced software engineer Think of a large language model as a program with an enormous array of tunable parameters rather than explicitly written rules. Training text is broken into tokens—word fragments, punctuation, and other units—and the model learns to predict each token from the preceding ones.
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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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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…

GPT-6 Astra1,553 words
Between Tide and Orchard Seared scallop, celeriac silk, blackcurrant–kombu gel, coffee beurre blanc, and buckwheat lace A four-person tasting-menu course, designed around the surprising affinity between scallops, blackcurrants, and coffee.
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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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Historical Counterfactual Analysis

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

GPT-6 Astra1,967 words
A transistor invented in 1920 would probably bring the electronics age forward—but not uniformly by 27 years. The first gains would be smaller, more reliable radios and control systems. Computers, integrated circuits, and space systems would follow only when other prerequisites caught up.
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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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Mini LBO Underwrite

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

GPT-6 Astra560 words
Entry capitalization and operating model All figures in $m. Interest is calculated on beginning-of-year debt balances. Term Loan amortization is 1% of its original principal, or $4.8m annually; remaining cash flow is swept to the Term Loan at year-end. Mezzanine PIK accrues annually.
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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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Advanced Investment Memo (IC Memo)

You are writing an internal investment committee memo for a long/short equity fund. Company (fictional): LedgerLift (ticker: LLLT) – B2B…

GPT-6 Astra1,000 words
LedgerLift (LLLT): Internal IC Memo Fictional exercise; not investment advice. Dollar figures in millions unless noted. Recommendation: PASS 12-month valuation/PT range: $30–$46, versus $46 currently; bear-case downside reference approximately $18.
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Mercury 2.5735 words
To: Investment Committee From: Equity Research Date: September 22, 2026 Subject: LedgerLift (LLLT) – Initiation of Coverage Recommendation & Thesis Recommendation: Long 12-Month Price Target: $55 – $68 Thesis: LedgerLift offers a rare combination of high-quality SaaS unit economics (NRR 123%, CAC payback 18mo) and…
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Our Verdict
GPT-6 Astra
GPT-6 Astra
Mercury 2.5
Mercury 2.5Runner-up

Not enough votes to call it. On the specs, GPT-6 Astra has the edge: bigger model tier, bigger context window, major provider backing.

Mercury 2.5 costs 333x less per token.

Slight edge

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GPT-6 Astra
Input
$10.00
Output
$50.00
Mercury 2.5
Input
$0.04
250× cheaper
Output
$0.15
333× cheaper

Mercury 2.5 is cheaper on both: 250× input, 333× output.

Where to run it

4 hosts, cheapest first

GPT-6 Astra3 hosts
HostInOutContextUptime
Azure AI Foundry$10.00 in·$50.00 out·1.1M·99.9% upOpenAI$10.00 in·$50.00 out·1.1M·100% upAmazon Bedrock$11.00 in·$55.00 out·1.1M—
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

GPT-6 Astra is developed by OpenAI while Mercury 2.5 is developed by Inception. GPT-6 Astra has a 1.1M 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. GPT-6 Astra 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.

GPT-6 Astra costs $10/M input tokens and Mercury 2.5 costs $0.04/M input tokens. Mercury 2.5 is $9.96/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 GPT-6 Astra 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.

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