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  5. Grok 4.1 FastvsMercury 2.5
Updated Sep 2026

Grok 4.1 FastvsMercury 2.5

Mercury 2.5 is the newer model, released after Grok 4.1 Fast.

Grok 4.1 Fast and Mercury 2.5 compared across 20 shared prompts
SpecGrok 4.1 FastMercury 2.5
Input price—$0.04/M tokens
Output price—$0.15/M tokens
Context window—260K tokens
Free API (OpenRouter)NoNo
ReleasedNov 2025Sep 2026
Side by side

Same prompt, both answers

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

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.…

Grok 4.1 Fast501 words
Solution Claim: "94% accuracy" for decoding neural patterns into text via EEG headband Why it's weak: This is by far the most exaggerated technical claim, as current non-invasive EEG-based brain-computer interfaces (BCIs) for text generation achieve nowhere near 94% accuracy in real-world conditions.
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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."
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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) –…

Grok 4.1 Fast385 words
Simplified LBO Model (FY2026–FY2030, $m) Year Revenue EBITDA TL Cash Int. Mezz Cash Int. Cash Taxes Capex ΔNWC FCF After Debt Service* End TL End Mezz End Total Debt FY26 972.0 136.1 43.2 21.6 17.8 29.2 0.4 19.1 456.1 183.6 639.7 FY27 1,040.0 156.0 41.1 22.0 23.2 31.2 0.3 33.6 417.9 187.3 605.2 FY28 1,102.4 176.4 37.6…
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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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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…

Grok 4.1 Fast874 words
Explanation for the Experienced Software Engineer Think of a large language model (LLM) like GPT as an enormous, distributed autocomplete engine built on a transformer architecture—imagine a system where every API endpoint you've ever queried is distilled into a single, massively parallelizable service that handles…
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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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Historical Counterfactual Analysis

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

Grok 4.1 Fast922 words
Technological Implications Immediate Advancements (1920s-1930s): Transistors replace bulky, power-hungry vacuum tubes by mid-1920s. Radios become pocket-sized and cheap by 1925 (vs. 1954 historically), accelerating mass media.
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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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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…

Grok 4.1 Fast208 words
Pantry Raid Garlic Tomato Pasta A savory, garlicky one-pan wonder that's ready in under 20 minutes—perfect for when hunger strikes and the fridge is empty! Serves: 2 Prep time: 5 minutes Cook time: 12 minutes Total time: 17 minutes Ingredients (exactly 7 common pantry staples): 200g spaghetti or any pasta (2 handfuls)…
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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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Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

Grok 4.1 Fast346 words
No Sticky Sessions for WebSockets (Scaling Bottleneck & Failure Mode) Issue: Round-robin load balancer doesn't guarantee client WebSocket connections stick to the same API server.
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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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Our Verdict
Grok 4.1 Fast
Grok 4.1 Fast
Mercury 2.5
Mercury 2.5Runner-up

Not enough votes to call it. On the specs, Grok 4.1 Fast has the edge: bigger model tier, major provider backing.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Grok 4.1 Fast
Input
—
Output
—
Mercury 2.5
Input
$0.04
Output
$0.15
Where to run it

1 host

Grok 4.1 Fast

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

Grok 4.1 Fast is developed by xAI while Mercury 2.5 is developed by Inception. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.

It depends on your use case. Grok 4.1 Fast 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.

This page shows a side-by-side comparison of Grok 4.1 Fast 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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Model pages

Grok 4.1 Fast logo
Grok 4.1 Fast59 outputs, specs and price
Mercury 2.5 logo
Mercury 2.520 outputs, specs and price
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