Best Portkey Alternatives in 2026: 7 AI Gateways Compared

Comparison Table

Why Teams Are Looking for Portkey Alternatives

Portkey was a popular choice for AI gateway and observability. Then Palo Alto Networks announced the acquisition on April 30, 2026, and closed the deal on May 29, 2026. Portkey now sits inside the Prisma AIRS platform. This raised three concerns for existing users.

First, roadmap independence. Will Portkey stay a standalone developer tool, or become a feature inside a larger security product? The open-source gateway moved to Apache 2.0 in March 2026, but the managed platform remains proprietary.

Second, pricing risk. Portkey Production plan costs $49 per month plus $9 per 100K log entries. Teams with high traffic see observability costs scale linearly. After an acquisition, pricing changes are common within 12 to 18 months.

Third, data handling. Portkey logs every request for observability. Under new ownership, teams want to know where data is stored, who can access it, and whether it trains models. These questions matter for compliance-heavy industries.

The 7 Best Portkey Alternatives in 2026

1. Eden AI: Best for Multi-Modal AI Gateway

Eden AI is the only gateway that unifies LLM, vision, speech, OCR, and translation APIs through a single endpoint. With 500+ models from 80+ providers, it offers the broadest coverage of any AI gateway on this list.

The OpenAI-compatible chat endpoint at /v3/chat/completions handles all LLM calls. Non-LLM tasks like OCR and image generation go through /v3/universal-ai. Both use the same API key and the same billing.

Eden AI charges pay-per-use. You pay only for the API calls you make. There is no log-based pricing or per-seat fee. This makes costs predictable even as traffic grows.

The fallback system is built-in. You pass a fallbacks array in your request. If the primary model fails, Eden AI tries the next one automatically. No extra infrastructure needed.

Here is how a call to Eden AI looks:

import urllib.request
import json
import os

headers = {
    "Authorization": "Bearer " + os.environ["EDENAI_API_KEY"],
    "Content-Type": "application/json",
}

data = json.dumps({
    "model": "anthropic/claude-sonnet-4-6",
    "messages": [{"role": "user", "content": "Summarize this document."}],
    "max_tokens": 500,
    "fallbacks": ["openai/gpt-4o", "google/gemini-2.5-flash"]
}).encode()

req = urllib.request.Request(
    "https://api.edenai""" + '.run"""' + """/v3/chat/completions",
    data=data,
    headers=headers,
    method="POST",
)

with urllib.request.urlopen(req, timeout=30) as resp:
    result = json.loads(resp.read())
    print(result["choices"][0]["message"]["content"])

Eden AI also supports the full feature catalog: text moderation, named entity recognition, object detection, face detection, deepfake detection, background removal, and more. All through the same API.

2. OpenRouter: Best for LLM Model Selection

OpenRouter provides access to 300+ LLMs with automatic routing to the cheapest or fastest model. Its pay-per-token pricing adds a small markup on top of each provider base rate. The OpenAI-compatible API makes migration straightforward.

OpenRouter works best for teams that need many language models but do not need vision, speech, or OCR. It is LLM-only. If your stack includes image analysis or document parsing, you need a separate service.

One concern: OpenRouter holds your API key for every provider. If their infrastructure is compromised, all your provider accounts are at risk. Teams with strict security requirements often prefer bring-your-own-key setups.

3. LiteLLM: Best for Self-Hosted Deployments

LiteLLM is an open-source proxy (MIT license) that translates requests to 100+ provider formats into OpenAI-compatible calls. It is free to self-host and includes basic load balancing, budget tracking, and virtual keys.

The trade-off is operational burden. You manage the server, handle updates, and debug issues yourself. LiteLLM works well for teams that want full control and have DevOps capacity. For teams without that capacity, a managed gateway like Eden AI saves time.

4. Bifrost: Best for Enterprise Governance

Bifrost is an open-source gateway (Apache 2.0) focused on policy-based routing, RBAC (Role-Based Access Control, a way to limit access based on user roles), and compliance auditing. Its governance engine lets you define rules like route EU traffic to EU-hosted models only.

Bifrost is self-hosted, so all traffic stays within your network. Provider billing remains direct. This makes it a strong fit for regulated industries that need audit trails and data sovereignty guarantees.

5. Helicone: Best for Observability

Helicone is an observability-first gateway with detailed request logging, cost tracking, and latency analytics. It works as a proxy in front of your existing provider calls. Note that Helicone entered maintenance mode after being acquired by Mintlify in 2026. New features may be limited going forward.

Per-log pricing can get expensive at high volumes. If you send millions of requests per month, observability costs can rival your inference costs. Teams on a budget often combine a lightweight gateway with a separate analytics tool.

6. Cloudflare AI Gateway: Best for Edge Caching

Cloudflare AI Gateway runs at the edge, offering caching, rate limiting, and analytics with zero additional infrastructure. It is free with all Cloudflare plans. The added latency is under 10 milliseconds because requests are processed at the nearest edge node.

The limitation is model coverage. Cloudflare supports roughly 20 providers, which is enough for most LLM workloads but not for multi-modal AI. If you need OCR, speech-to-text, or image generation, you will need a second gateway.

7. Kong AI Gateway: Best for Full API Lifecycle

Kong AI extends Kong API management platform with AI-specific features: authentication, rate limiting, request transformation, semantic caching, and cost controls. Enterprise licensing applies, and the free tier on Kong Konnect covers basic needs.

Kong AI is best for organizations that already run Kong Gateway for their general API management. Adding AI features to an existing Kong deployment is simpler than running a separate AI gateway.

How to Choose the Right Portkey Alternative

Evaluate gateways on five criteria:

1. Model coverage: Do you need LLM-only or multi-modal (LLM, vision, speech, OCR)? Eden AI covers all categories. OpenRouter and LiteLLM are LLM-focused.

2. Pricing model: Per-token (OpenRouter), per-request (Eden AI), per-log (Portkey, Helicone), or free/self-hosted (LiteLLM, Bifrost)? Log-based pricing scales with traffic. Per-use pricing is more predictable.

3. Latency overhead: How much latency does the gateway add? Cloudflare adds under 10ms at the edge. Managed gateways typically add 20 to 80ms. Self-hosted options depend on your infrastructure.

4. Deployment flexibility: Can you self-host? Bifrost and LiteLLM are fully self-hosted. Eden AI and OpenRouter are cloud-only. Kong offers both.

5. MCP support: Model Context Protocol (MCP, a standard for connecting AI models to external tools) is becoming essential. Check whether the gateway supports MCP server connections for tool use and context management.

Migrating from Portkey: Step-by-Step

Migration typically involves four steps:

1. Audit your current Portkey configuration: models, routing rules, fallback chains, and virtual keys.

2. Map providers to the new gateway supported list. Most OpenAI-compatible gateways support the same providers.

3. Update your base URL and API key. If your code uses the OpenAI SDK format, migration to Eden AI, OpenRouter, or LiteLLM is often a two-line change.

4. Test in staging with production traffic patterns. Verify fallback chains, latency, and cost before switching production.

For Eden AI, the migration looks like this:

from openai import OpenAI

client = OpenAI(
    api_key="your-edenai-key",
    base_url="https://api.edenai""" + '.run"""' + """/v3",
)

response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Hello"}],
)

That is the entire migration for OpenAI SDK users. Change the base URL and API key. Everything else stays the same.

Last updated: 2026-07-31

Conclusion

Portkey acquisition by Palo Alto Networks and its log-based pricing model have made 2026 the year teams re-evaluate their AI gateway. Whether you need multi-modal coverage with Eden AI, LLM-only routing with OpenRouter, or self-hosted control with LiteLLM, there is a strong alternative for every use case.

The key is matching the gateway to your actual needs. If you use LLM plus vision plus OCR, a multi-modal gateway like Eden AI avoids running three separate services. If you only use LLMs, an open-source proxy like LiteLLM gives you full control at zero cost.

You can find them at Eden AI.

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