AI Gateway Pricing Comparison 2026: Vercel AI, OpenRouter vs NeuralRouting
The AI gateway market has matured fast. We break down the real costs of Vercel AI, OpenRouter, and NeuralRouting — including what happens to your LLM bill at scale.
NR
NeuralRouting Team
April 10, 2026
The AI gateway market has matured fast. What started as a handful of open-source proxies has become a critical infrastructure decision — one that can make or break your LLM budget at scale.
This guide compares the three most-evaluated AI gateway options in 2026 across the dimensions that actually matter for production teams: pricing model, cost impact, and feature depth.
What Is an AI Gateway (and Why Pricing Gets Complicated)
An AI gateway sits between your application and the underlying LLM providers. It handles routing, authentication, rate limiting, cost tracking, and — increasingly — intelligent model selection.
The pricing models across providers are radically different, which makes apples-to-apples comparison difficult. You're not just buying API access. You're buying infrastructure behavior that directly affects your token spend.
The key question to ask: does this gateway reduce my costs, or add to them?
Vercel's offering is primarily a developer SDK rather than a standalone gateway. It abstracts multiple model providers under a unified interface, with deployment tied to Vercel's infrastructure.
Pricing model:
SDK is open source and free
No markup on underlying LLM tokens
Compute costs apply for Vercel Functions handling server-side requests
What it does well:
Exceptional developer experience for Next.js teams
First-class streaming support
Strong TypeScript types across providers
Where it falls short:
No built-in cost optimization or intelligent model routing
Vendor lock-in to Vercel's deployment model
No semantic caching or fallback routing logic
Cost visibility requires third-party tooling
Best for: Teams already on Vercel who want quick LLM integration and aren't yet worried about cost at scale.
OpenRouter
OpenRouter is a unified API that aggregates 100+ LLM providers under a single endpoint. Their business model is a markup on top of provider costs.
Pricing model:
5–15% markup above provider pricing, depending on the model
Pay-as-you-go, no subscription required
Volume discounts available at higher tiers
What it does well:
Massive model selection — the broadest in the market
Single API key for all providers
Automatic fallback routing on provider downtime
Where it falls short:
The markup compounds at scale. 10% on $50k/month = $5,000/month in overhead
No intelligent routing based on prompt complexity
No semantic caching
Limited per-request observability and cost attribution
Best for: Prototypes, early-stage products, or teams that need access to many models without caring about cost optimization yet.
NeuralRouting
NeuralRouting takes a fundamentally different approach: instead of aggregating models at a fixed markup, it actively routes each prompt to the cheapest model capable of handling it — without degrading output quality.
Pricing model:
Plan
Price
Included Routing Volume
Overage
Free
$0/mo
100K tokens/mo
—
Starter
$29/mo
5M tokens/mo
$0.006/1K
Growth
$79/mo
20M tokens/mo
$0.004/1K
Business
$199/mo
100M tokens/mo
$0.002/1K
Important: these credits represent routing-managed volume, not the underlying model cost. Your LLM provider costs go directly to your own API accounts.
What it does well:
Intelligent routing reduces average cost per request by 70–97%
Semantic caching for repeated or similar prompts
OpenAI SDK-compatible — works as a drop-in replacement
Full cost observability per request, per user, per endpoint
Automatic fallback routing on provider errors
Where it falls short:
Requires trust in routing decisions (though manual overrides are always available)
Newer platform compared to OpenRouter's established track record
Best for: Teams spending $500+/month on LLM APIs who want to reduce costs without rewriting their stack.
Real Cost Comparison at Scale
Let's run the numbers for a team processing 10 million tokens per month, with a realistic distribution of request complexity.
Assumptions
70% simple tasks (classification, summaries, short Q&A)
That's a 68% reduction versus going direct — and an 82% reduction versus OpenRouter at that volume.
With semantic caching enabled (20–40% cache hit rate on repeat queries), effective costs drop further without any additional routing overhead.
Feature Comparison Matrix
Feature
Vercel AI
OpenRouter
NeuralRouting
Intelligent model routing
❌
❌
✅
Semantic caching
❌
❌
✅
OpenAI SDK compatible
✅
✅
✅
Markup on tokens
0%
5–15%
0%
Per-request cost analytics
Limited
Basic
Full
Automatic fallback routing
Manual
✅
✅
Free tier
✅ (SDK)
✅
✅
Cost reduction vs baseline
0%
−10% (worse)
70–97%
Which Gateway Is Right for You?
Choose Vercel AI SDK if your team lives in the Next.js/Vercel ecosystem, you need quick integration, and your LLM spend is under $500/month.
Choose OpenRouter if you need access to many models simultaneously, you're in early prototyping, and cost optimization isn't yet a priority.
Choose NeuralRouting if you're spending meaningfully on LLM APIs, want automatic cost reduction without changing your codebase, and need per-request observability that scales with your product.
The Bottom Line
Gateway pricing is only part of the equation. The more important question is: what does the gateway do to your underlying LLM spend?
Vercel doesn't touch it. OpenRouter adds to it. NeuralRouting actively reduces it.
At meaningful LLM usage volumes — typically $1,000+/month in API costs — the routing intelligence pays for the subscription cost within the first week.