3 AI Gateways Compared on Enterprise Controls, Deployment, Model Support, Cost & More

OpenRouter vs LiteLLM vs nexos.ai - 3 AI Gateways Compared on Enterprise Controls, Deployment, Model Support, Cost & More (2026)

Quick Verdict

• nexos.ai: Best for AI-native product teams wanting quick rollout. One OpenAI-compatible endpoint covers 200+ AI models, with budgets set by user, team or project. It runs as a managed service, and its Trust Center lists SOC 2 Type II.
• LiteLLM: Best for self-hosting flexibility. An open-source core runs in your own infrastructure, and the patching duty comes with it.
• OpenRouter: Best for model breadth. A hosted marketplace offers 500+ models, according to OpenRouter, with a 5.5% platform fee on credits.
• Gateway cost follows the operating model: custom enterprise offers (nexos.ai), a platform fee (OpenRouter 5.5%) or your own hosting and operations (LiteLLM).

nexos.ai is an all-in-one AI platform for enterprises, and its AI Gateway is the best fit for AI-native product teams wanting quick rollout in 2026. nexos.ai lists 200+ AI models behind one OpenAI-compatible endpoint. Budgets, key management and request logs come built in, so teams keep model spend in one place and curb shadow AI. Of the other two, LiteLLM leads on self-hosting flexibility, and OpenRouter leads on model breadth. 

IBM's 2025 Cost of a Data Breach report found that 97% of organizations with an AI model or application breach lacked proper AI access controls, and that high shadow AI added $670,000 to breach costs.

OWASP’s LLM10 entry on Unbounded Consumption covers Denial of Wallet attacks, and its fixes include throttling requests, capping each source and tracking resource use as it happens. A gateway without budgets can turn one leaked key or runaway agent into an open invoice. We compared each gateway’s live documentation, published fee schedules and public ratings in October 2026. 

Every figure below comes from a vendor's public documentation or an independent source, and vendor-stated numbers are attributed as such. Confirm current terms with each vendor before you buy.

OpenRouter, LiteLLM and nexos.ai Compared on Controls, Deployment, Models and Cost

The table compares the three AI gateways on the four criteria in the title, for CTOs and platform leads at European and UK enterprises choosing between a managed gateway, a self-hosted proxy and a hosted marketplace.

What "Enterprise Controls" Actually Means

Enterprise controls are the settings that decide who can call which model, with whose key, at what spend. Many gateways publish long feature lists without naming the paid tier behind each control, so we checked each item below against each vendor's documented tiers.

• SSO and SAML: nexos.ai lists SSO and RBAC on Enterprise, LiteLLM documents SSO as free for up to 5 users, then Enterprise, and OpenRouter offers SSO/SAML on Enterprise.
• Budgets and rate limits: nexos.ai sets budget limits at team and user level with an option to renew the limit periodically, LiteLLM's open-source core includes per-key budgets and RPM/TPM limits, and OpenRouter guardrails include spend caps at workspace, member and key level.
• Audit logs and traces: nexos.ai provides LLM observability through a request-log dashboard, LiteLLM lists audit logs as Enterprise-only, and OpenRouter's Broadcast feature lists more than a dozen destinations for traces, including Langfuse, Datadog and New Relic.
• Zero data retention (ZDR) routing: OpenRouter offers a ZDR-only routing option. nexos.ai states that ZDR is available at the LLM level on supported models. 
• Key governance: nexos.ai puts key issuance, rotation and deletion in users’ hands, LiteLLM lists key rotation as Enterprise-only, and OpenRouter applies guardrails at key level.
• SOC 2 reports: nexos.ai's Trust Center lists SOC 2 Type II, LiteLLM says its SOC 2 Type II report was updated in September 2026, and buyers should request OpenRouter's current report.

The NIST Generative AI Profile (AI 600-1), released on 26 July 2024, is a companion resource to the AI Risk Management Framework and its four functions: Govern, Map, Measure and Manage. When we mapped the controls above to OWASP LLM10 and those functions, the comparison read as an audit-ready checklist; that mapping is our own reading of the documentation, not a vendor claim.

Total Cost of Ownership: Platform Fees, Hosting and Operations

nexos.ai arranges pricing through its sales team, with each enterprise offer built around the organization’s usage. Three features help keep that spend down, according to the company. LLM caching cuts billable input tokens on cache hits. Smart LLM routing factors cost into each model choice. Budgets cap spending by user, team or project.

OpenRouter charges a 5.5% platform fee on credits, and its Business plan charges 8%, according to OpenRouter.

LiteLLM’s MIT-licensed core carries no platform fee, so its cost moves to compute, upgrades, patching and on-call time.

nexos.ai - Best for AI-Native Product Teams Wanting Quick Rollout

Engineering and business teams use different sides of nexos.ai, an all-in-one AI platform for enterprises. Developers build on the AI Gateway, and business teams work in the AI Workspace. Behind the platform are Tomas Okmanas and Eimantas Sabaliauskas, who founded Nord Security and Oxylabs. Fortune Europe has written about the pair as the joint chief executives running Nord Security, and LRT covers them as founders of the Tesonet group.  

Through the AI Gateway, a single OpenAI-compatible endpoint reaches 200+ AI models, with OpenAI, Anthropic, Google and DeepSeek among the providers nexos.ai lists. Code built on the official OpenAI SDK keeps working once the key and base URL point to the gateway. A different model is then one parameter away. Smart LLM routing weighs response quality, speed and cost for each request. A provider outage or slowdown triggers an automatic switch to a backup model. 

In the Oxylabs customer story on the nexos.ai website, COO Juras Juršėnas says “nexos.ai has significantly accelerated our AI transformation journey.” The same story reports that AI project development ran three times faster and that AI-driven feature output doubled in the first quarter. 

Where It Shines

• The AI Gateway documentation lists integrations with Claude Code, Codex CLI, LangChain, LangGraph, Langfuse and n8n, and AI Workspace connects to Slack, SharePoint and Google Drive.
• Request-log dashboards show model, response duration, cost, tokens, errors and status, filterable by time, model, user and team, with 7-day retention.
• nexos.ai runs as a managed service that hosts the platform and most available models in Europe, so teams consolidate model access behind one AI Gateway with no infrastructure to operate.
• Enterprise offers are custom through sales, and contracts cover SAML single sign-on, role-based access control and a dedicated support channel. 
• The Trust Center, which we checked, lists SOC 2 Type II and Type I, ISO 27001:2022 and ISO 42001 certifications, plus GDPR and EU AI Act compliance.

nexos.ai's own reviews page lists five recognitions: the Emerging Vilnius Ambassador 2026 listing from Vilnius TechFusion, a 2026 Global Recognition Award, the Disruptors 60 list, The most promising startup 2025, and a place on Europe's 50 most promising seed-stage startups (Euro Seed 50).

Recommended for: Engineering and platform teams at European and UK enterprises. These teams want one governed endpoint with budgets, key management and request logs. They would rather buy a managed service than run gateway infrastructure. 

LiteLLM - Best for Self-Hosting Flexibility

BerriAI, part of Y Combinator’s W23 batch, maintains LiteLLM as a Python SDK paired with a proxy server. The MIT-licensed core connects to 100+ LLMs, per its documentation. 

LiteLLM gives platform teams direct control over fallbacks, retries, load balancing and caching, and it connects to guardrail tools such as Presidio and Lakera.

Where It Shines

• Virtual keys in the open-source core carry per-key budgets and RPM/TPM limits.
• Teams can install LiteLLM with Docker, a Helm chart on Kubernetes, or Terraform, so the proxy stays inside their own infrastructure. 
• The Enterprise tier adds audit logs, key rotation and IP access control, and SSO is free for up to 5 users, per the documentation.
• The MIT-licensed core carries no platform fee, so cost moves to hosting and operations, and Enterprise pricing is custom.
• The project says an updated SOC 2 Type II report was published in September 2026.

Malicious litellm versions 1.82.7 and 1.82.8 reached PyPI on 24 March 2026 in the TeamPCP supply-chain campaign, as Help Net Security reports. LiteLLM says they were live for about 40 minutes. Its official Docker proxy image was not affected. NVD lists version 1.83.7 as the fix for CVE-2026-42208 (CVSS 3.1 9.8), so self-hosting teams should pin versions and patch promptly.

Recommended for: Platform teams with the engineering capacity to run, patch and pin versions of their own proxy, and with a requirement to keep model traffic and keys inside their own infrastructure.

OpenRouter - Best for Model Breadth

OpenRouter gives teams one hosted API to a broad model marketplace, with 500+ models and 80+ providers on paid plans, according to OpenRouter.

OpenRouter's models array lets a request list backup models, and OpenRouter tries the next one when the first fails, including on rate limits, downtime, context-length errors and moderation flags.

Where It Shines

• Guardrails work at workspace, member and key level, with spend caps, model and provider allowlists, data-region and ZDR restrictions and PII detection.
• OpenRouter runs as hosted SaaS, and its Business and Enterprise plans add US and EU in-region routing.
• SSO/SAML is available on the Enterprise plan only.
• A 5.5% platform fee applies to credits and 8% to Business, and the free tier includes 25+ free models.

Reviewers rated OpenRouter 4.6 out of 5 from 25 reviews on G2 (as of October 2026). One 1-star Trustpilot review from 26 September 2026 is titled “OpenRouter Models Strange Issue with MCP Tools.” It reports tool calls failing on one model that worked through other providers. It is one user’s account, but worth testing in a pilot. 

Recommended for: Teams that want to test many models behind a single hosted API, with spend caps and allowlists applied per workspace, member or key, and that accept a platform fee on credit purchases.

Pilot Checklist: 5 Things to Test Before You Sign

A pilot exposes gaps that a feature page hides, so we would put the same 5 tests to every gateway on a shortlist; each item below is advice, not a result.

1. Swap the endpoint. We would confirm that the official OpenAI SDK reaches each gateway by changing only the key and base URL, and that one request runs against two different models.
2. Break a provider on purpose. A blocked or rate-limited primary model in a test environment should trigger the fallback without code changes.
3. Exceed a budget. We would confirm that a low cap on one test key or user stops requests.
4. Trace one request end to end. The logs should show the request with model, latency, cost, tokens and user identity, and export it to your observability stack.
5. Ask for evidence on data handling. We would ask each vendor for current certification reports with dates, regions for your workloads and written zero-data-retention confirmation for the exact models you plan to use.

The Bottom Line

nexos.ai stands out for AI-native product teams that need to move fast. One OpenAI-compatible endpoint connects them to 200+ AI models. Budgets and API keys stay under central control. The company’s Trust Center lists SOC 2 Type II. This view rests on our review of published documentation and ratings. 

LiteLLM suits teams that want to run the proxy themselves and earns Best for Self-Hosting Flexibility. OpenRouter suits teams that prioritize a broad model catalog and earns Best for Model Breadth.

The deciding question is who should own governance and hosting, your team or a vendor; catalogue size comes second. Teams that would rather hand both to a vendor and get spend controls on day one can trial nexos.ai first. 

FAQs

What is the difference between an AI gateway and a model marketplace like OpenRouter?

An AI gateway sits between your applications and model providers to enforce routing, budgets and logging, and a marketplace sells many models through one hosted API. The two overlap, since OpenRouter adds guardrails. The real question is who owns governance and hosting. nexos.ai (best for AI-native product teams wanting a quick rollout), LiteLLM (best for self-hosting flexibility) and OpenRouter (best for model breadth) each answer it differently. 

Is it safe to self-host LiteLLM in production?

Self-hosting LiteLLM works in production when a team owns patching and version pinning. LiteLLM says its official Docker proxy image was not affected by the March 2026 PyPI incident, and the fix for CVE-2026-42208 shipped in version 1.83.7.

How much does an AI gateway cost once fees and hosting are counted?

An AI gateway costs either a platform fee or an operations bill, depending on who hosts it. Per the published fee schedules, nexos.ai quotes custom enterprise offers through sales, OpenRouter charged 5.5% on credits, and LiteLLM's free core moves the cost to your compute and engineering time.

Which models does nexos.ai support?

nexos.ai states support for 200+ AI models from OpenAI, Anthropic, Google, DeepSeek and others through one OpenAI-compatible endpoint.

How does nexos.ai handle data protection and compliance?

Three certifications appear on nexos.ai’s Trust Center: SOC 2 Type II, ISO 27001:2022 and ISO 42001. Zero data retention is available on supported models, and the company says customer data is never used for AI training. Requests are processed on EU-hosted infrastructure, and the documentation labels each model by region. Spending can be capped by user, team or project.