What Is Eden AI and What Does It Do?
Eden AI is a unified AI API aggregator that routes requests across multiple AI providers and models through a single integration point. A developer connects once and gains access to providers spanning large language models, image generation, and document AI. No rebuilding of authentication or parsing logic for each vendor is required.
Eden AI supports 3 broad modality categories: text and LLM inference, image generation, and document/PDF processing including OCR and data extraction. Each category draws from multiple underlying providers, so a single API call dispatches to whichever model the routing logic selects.
In an AI stack, Eden AI sits at the aggregation layer — above raw provider APIs and below application logic. Teams use it to avoid vendor lock-in. It also enables provider fallbacks and lets teams compare outputs across models without rewriting integration code.
Why Teams Look for Eden AI Alternatives
Teams leave Eden AI for 4 recurring reasons: per-request markups on provider costs, incomplete model rosters, limited routing control, and EU data-residency requirements.
Eden AI adds a margin on top of each underlying provider's published rate. For cost-sensitive workloads running millions of requests per month, that markup compounds into a meaningful budget line that direct provider access eliminates.
Eden AI's model coverage is the second trigger. Eden AI supports a curated set of providers, and teams that need a specific fine-tuned or newly released model find it absent from the catalog, forcing a parallel integration anyway.
Eden AI's routing control is the third pressure point. Eden AI offers provider fallback. But teams that need deterministic routing rules — send latency-sensitive calls to Provider A, send batch jobs to Provider B — report that the platform's logic is too coarse for production traffic shaping. A team routing real-time chat calls separately from overnight batch jobs, for instance, cannot enforce that split natively.
Eden AI's EU data residency is the fourth driver. Regulated industries in Europe require data to stay within EU infrastructure. Teams with EU-residency requirements should verify the selected Eden AI endpoint, upstream provider, and contractual data-processing terms.
Eden AI teams also cite 2 missing operational features beyond those 4 reasons:
Prompt versioning and management — no native prompt registry for tracking prompt iterations across environments
Observability depth — token-level cost attribution and latency tracing per model require third-party tooling rather than built-in dashboards
How We Evaluated These Eden AI Alternatives
This comparison reviews published product documentation and pricing. It does not present controlled API, latency, or throughput benchmarks.
Each Eden AI alternative was assessed against 4 criteria. These are routing control (how precisely a developer can direct traffic across providers), model breadth (the range of foundation models accessible through a single endpoint), developer experience (documentation clarity, OpenAI-compatible API availability, and onboarding friction), and governance features (BYOK support, self-hosting options, and free tier accessibility).
Pricing and specification data for these Eden AI alternatives came from each provider's official pricing pages and documentation in 2026. Where pricing varies by plan or requires a sales quote, the applicable tier should be checked directly with the provider.
11 Eden AI Alternatives Compared by Use Case
These 11 Eden AI alternatives cover three overlapping needs: unified model access, AI gateway management, and hosted inference. OpenRouter, LiteLLM, Portkey AI, Orq.ai, and Merge Gateway emphasize model access and routing; Together AI, Replicate, Hugging Face, Baseten, and Modal provide inference services or deployment infrastructure; GPT Proto combines access to text, image, and video models through one API key and shared balance.
| Product |
Starting price |
Model coverage |
Primary modalities |
BYOK support |
Self-hosting |
Free tier |
| OpenRouter |
Free for eligible models; paid models use usage-based pricing (pricing) |
500+ models across paid plans; 25+ free models |
LLMs and multimodal models, depending on the model |
Yes, subject to plan and provider support |
No self-hosted gateway offered |
Yes, with free-model rate limits |
| LiteLLM |
Free for the open-source version; infrastructure and provider usage cost extra (pricing) |
100+ LLMs, according to its getting-started documentation; coverage depends on integrations |
LLMs, embeddings, images, and audio through supported providers |
Yes, using provider credentials |
Yes, open-source proxy |
Yes, free software; model usage is billed separately |
| Portkey AI |
Free Developer plan; Production starts at $49/month, excluding provider usage (pricing) |
1,600+ LLMs advertised across integrations |
LLMs, vision, audio, and image generation |
Yes, through provider key management |
Yes, open-source gateway and enterprise deployment options |
Yes, with Developer-plan limits; provider usage is separate |
| Orq.ai |
Free within included platform allowances; provider usage and applicable fees are separate (pricing) |
500+ models across 30+ providers |
LLMs and supported multimodal models |
Yes; 1M BYOK requests/month included before gateway fees apply |
Yes, Enterprise VPC or on-premises deployment |
Yes, platform allowances; not unlimited free model inference |
| Together AI |
$5 minimum credit purchase for standard paid access; inference rates vary by model (billing, pricing) |
200+ models in the official catalog |
LLMs, vision, images, audio, video, embeddings, and reranking |
Not documented as a third-party provider-key gateway |
No self-hosted platform offered; dedicated inference is available |
No standard signup credit grant; selected zero-priced models may be listed separately (billing, pricing) |
| Replicate |
$0.000025/sec for CPU Small; GPU and output-based model rates vary (pricing) |
Thousands of public models, plus custom deployments |
Text, images, video, and audio, depending on the model |
Not documented as a third-party provider-key gateway |
No self-hosted Replicate service; model packaging tools are separate |
Limited free trials on selected models, rather than a recurring general API allowance |
| Hugging Face Inference Providers |
Free within included credits; additional usage is pay as you go (pricing) |
200+ models advertised for Inference Providers; the full Hub catalog is larger and is not equivalent to API availability |
LLMs, images, video, audio, embeddings, and other supported inference tasks |
Yes, through custom provider keys |
No self-hosted Inference Providers service; compatible open models can be hosted separately |
Yes, $0.10/month for free accounts, subject to change |
| Merge Gateway |
Free for free-model access; Pro charges model cost plus a 5% fee (pricing) |
All major models on Pro; no exact catalog count published on the pricing page |
LLMs and supported model capabilities |
Yes, on Pro and Enterprise |
Yes, Enterprise VPC or on-premises deployment |
Yes, free-model access; Pro also includes $10/month in expiring credits |
| Baseten |
$0.10/1M input tokens and $0.50/1M output tokens for GPT OSS 120B; other APIs and deployments have separate rates (pricing) |
Curated Model APIs plus custom model deployments; no fixed overall model maximum published |
LLMs and custom multimodal inference |
Not documented as a third-party provider-key gateway |
Yes, self-hosting available by arrangement |
Trial credits for new accounts; amount not specified on the pricing page |
| Modal |
$0/month Starter plan, plus metered compute beyond included credits (pricing) |
User-deployed models; no fixed catalog limit comparable to an API aggregator |
Text, images, video, and audio through user-deployed code |
Provider keys can be used in application code; this is not a native model-routing BYOK plan |
No self-hosted Modal platform offered |
Yes, $30/month in compute credits on Starter |
| GPT Proto |
$10 minimum top-up, with model-specific pay-as-you-go rates and no subscription (pricing) |
200+ models, accessed through one API key and shared balance |
LLMs, vision, image generation, and video generation |
Not publicly documented; published setup uses a GPT Proto API key |
No publicly documented self-hosted deployment |
Free web tools are advertised; a recurring free API allowance is not publicly confirmed (source, pricing) |
How to read this table: Model coverage describes advertised integrations, available inference models, or custom deployment support—not a guaranteed maximum or free-plan entitlement. BYOK means using your own upstream provider credentials, rather than simply creating an API key for the platform itself. Self-hosting means deploying the platform or gateway on infrastructure you control; deploying a custom model on a vendor's cloud is a different capability. Free software, recurring credits, and limited trials are identified separately because each carries different usage costs.
| Product |
Editorial assessment |
| OpenRouter |
Fastest path from zero to multi-provider LLM calls; routing logic is transparent but limited to model selection rather than deep observability |
| LiteLLM |
Requires real engineering investment to deploy and maintain; the payoff is full control with no per-token markup |
| Portkey AI |
|
| Orq.ai |
Governance controls stand out for regulated environments; the BYOK gateway model keeps costs predictable |
| Together AI |
OpenAI-compatible endpoint made integration trivial; fine-tuning pipeline is a meaningful differentiator over pure aggregators |
| Replicate |
Version-pinned model deployments are reliable for reproducible pipelines; billing by the second suits bursty workloads |
| Hugging Face Inference API |
Catalog breadth is unmatched; cold-start latency on shared endpoints is noticeable for latency-sensitive production use |
| Merge Gateway |
Tenant-level routing controls are well-suited to multi-customer SaaS; the product surface is narrower than full-featured gateways |
| Baseten |
Token-priced Model APIs behave predictably; dedicated GPU replicas require upfront capacity planning |
| Modal |
Serverless GPU execution is genuinely scale-to-zero; the platform demands more infrastructure code than a prebuilt aggregator |
| GPT Proto |
OpenAI-compatible drop-in with strong model breadth; suited to teams that want aggregator convenience without self-hosting overhead |
1. OpenRouter
OpenRouter is a routing layer that delivers access to 500+ models through a single OpenAI-compatible endpoint. The free tier provides access to 25+ free models and 4 free providers at 50 requests per day. Basic OpenAI-compatible calls can often reuse an SDK after configuration and model-ID changes. OpenRouter fits teams that primarily need broad LLM access with minimal integration friction. For other options in this category, see these OpenRouter alternatives.
2. LiteLLM
LiteLLM is an open-source gateway. It is free forever to self-host and supports 100+ providers through one OpenAI-compatible interface. The configuration is YAML-driven and straightforward for engineers comfortable with infrastructure tooling. Teams without dedicated DevOps capacity find the operational overhead significant. LiteLLM fits engineering-heavy teams that want to own their AI gateway and eliminate per-token markups entirely.
3. Portkey AI
Portkey AI is an LLM gateway with observability, guardrails, and prompt management layered on top of existing model providers. The Free Forever plan includes 10,000 recorded logs per month with 3-day log retention and 30-day metrics retention. Prompt versioning adds workflow overhead for small teams whose primary need is routing rather than governance. Portkey AI fits product teams that treat observability and prompt lifecycle management as first-class requirements.
4. Orq.ai
Orq.ai is a gateway that routes requests across 500+ models with VPC and on-premises deployment options that address data-residency requirements. The free tier includes 1,000,000 BYOK gateway requests per month, after which a 4% fee applies. The BYOK model means Orq.ai never holds provider credentials in a shared environment. Orq.ai fits privacy-sensitive or EU-focused teams that require sovereign hosting alongside multi-provider routing.
5. Together AI
Together AI is a model-hosting platform that exposes 200+ open-source models through an OpenAI-compatible API, with serverless token pricing starting at $0.05 per 1M tokens. Migration time depends on the application's use of model-specific features. The fine-tuning pipeline is a meaningful differentiator: teams can move from serverless inference to a custom fine-tuned model without changing providers. Together AI fits builders who want open-source LLM access today and a clear upgrade path to fine-tuning and dedicated GPU clusters.
6. Replicate
Replicate is a hosted-inference platform with 1,000+ versioned models and compute billed by the second, starting at $0.000025/sec for CPU-small and $0.001525/sec for H100. Replicate offers limited trials for selected models; continuing usage is billed under the selected model's terms. Replicate fits teams that primarily need hosted open-source models — especially generative media — with reproducible versioning and granular compute billing.
7. Hugging Face Inference API
Hugging Face Inference API is a hosted-inference service that serves a supported subset of the much larger Hub catalog with a free shared tier, a PRO plan at $9/month, and dedicated inference endpoints starting at $0.033/hour. Dedicated endpoints can avoid some shared-capacity constraints, but latency still depends on the model, hardware, and workload. Hugging Face Inference API fits teams evaluating supported open models, from quick experiments to dedicated production endpoints.
8. Merge Gateway
Merge Gateway is an LLM routing product with built-in fallback logic and tenant-level governance, targeting B2B SaaS vendors embedding AI features for multiple customers. The free plan covers prototyping and testing with access to free LLMs and fallback routing. The product surface is narrower than full-featured gateways: observability and prompt management are limited compared to dedicated platforms. Merge Gateway fits B2B SaaS vendors who need per-tenant routing governance more than broad model aggregation.
9. Baseten
Baseten prices hosted Model APIs per token — for example, GLM-5.3 Fast input tokens at $2.10 per 1M tokens — and dedicated GPU replicas such as H100 at approximately $6.50/hr. Workspace creation carries no monthly platform fee on the pay-as-you-go tier. Dedicated GPU replicas require upfront capacity decisions that add planning overhead compared to fully serverless alternatives. Baseten fits teams ready to promote a defined set of models into stable production serving rather than dynamically routing across many providers.
10. Modal
Modal executes user-defined inference code on serverless GPUs with billing by the second and scale-to-zero semantics that eliminate idle costs. Current GPU rates vary by hardware and are published on Modal's pricing page. Modal demands more infrastructure code than a prebuilt aggregator — teams write Python functions, not configuration files. Modal fits engineering teams that want to run proprietary models and custom pipelines on serverless GPUs with tight cost control.
11. GPT Proto
GPT Proto is an OpenAI-compatible API gateway that aggregates access to multiple leading models under a single endpoint, eliminating the need to manage separate provider accounts or self-host routing infrastructure. Basic OpenAI-compatible calls can often start with a new base URL and API key; model IDs and feature behavior still require validation. GPT Proto fits teams that want the model breadth of an aggregator with the operational simplicity of a managed service and no self-hosting overhead. Browse GPT Proto models to verify the models available for your workload.
Eden AI Alternatives: Pricing, Free Tiers & Specs Compared
The table below compares 11 Eden AI alternatives across six practical criteria: entry cost, model coverage, modalities, BYOK support, self-hosting, and free access. These platforms range from open-source gateways to managed model aggregators and infrastructure for custom inference.
| Product |
Starting price |
Model coverage |
Primary modalities |
BYOK support |
Self-hosting |
Free tier |
Our take |
| OpenRouter |
Free for eligible models; paid models use usage-based pricing (pricing) |
500+ models on paid plans; 25+ free models |
LLMs and supported multimodal models |
Yes, subject to plan and provider support |
No self-hosted gateway offered |
Yes; the Free plan lists 25+ models and 50 requests/day |
A strong starting point for broad model evaluation through one API. Free-model access helps with prototyping, while production selection still depends on provider availability, pricing, and limits. |
| LiteLLM |
Free open-source software; infrastructure and provider usage cost extra (pricing) |
100+ LLMs advertised in its documentation; integrations determine actual coverage |
LLMs, embeddings, images, and audio through supported providers |
Yes, using provider credentials |
Yes, self-hosted proxy |
Yes, free open-source gateway; no bundled inference credits |
Best suited to engineering teams that want control over routing, budgets, and deployment. The tradeoff is operating the gateway and paying upstream inference costs separately. |
| Portkey AI |
Free Developer plan; Production starts at $49/month, excluding provider usage (pricing) |
1,600+ LLMs advertised across integrations |
LLMs, vision, audio, and image generation |
Yes, through provider key management |
Yes, open-source gateway and enterprise deployment options |
Yes; Developer includes 10,000 recorded logs/month, with provider usage billed separately |
A strong fit when observability, guardrails, and prompt management matter alongside routing. The free Developer plan supports evaluation; Portkey explicitly recommends paid plans for production workloads. |
| Merge Gateway |
Free for free-model access; Pro charges model cost plus a 5% fee (pricing) |
All major models on Pro; no exact count published on the pricing page |
LLMs and supported model capabilities |
Yes, on Pro and Enterprise |
Yes, Enterprise VPC or on-premises deployment |
Yes, free-model access without a credit card; Pro includes $10/month in expiring credits |
Worth considering for SaaS teams that need customer-level model control, consolidated billing, and routing policies. Compare the Pro fee and enterprise deployment terms against your governance needs. |
| Replicate |
$0.000025/sec for CPU Small; GPU and output-based rates vary (pricing) |
Thousands of public models, plus custom deployments |
LLMs, images, video, and audio |
Not documented as a third-party provider-key gateway |
No self-hosted Replicate service offered |
Limited free trials on selected models; billing is required for continued use |
A practical choice for generative media and community models. Check each model's billing basis because hardware-time pricing and output-based pricing produce different costs. |
| Together AI |
$5 minimum credit purchase for standard paid access; inference rates vary by model (billing, pricing) |
200+ models in the official catalog |
LLMs, vision, images, audio, video, embeddings, and reranking |
Not documented as a third-party provider-key gateway |
No self-hosted platform offered; dedicated inference is available |
No standard signup credits; selected zero-priced models may be listed separately (billing, pricing) |
A good fit for teams moving from serverless open-model inference toward fine-tuning or dedicated deployments. Compare the rates and availability of your chosen models rather than relying on one platform-wide token price. |
| Hugging Face Inference Providers |
Free within included credits; additional usage is pay as you go (pricing) |
200+ inference models advertised; the full Hub catalog is not equivalent to API availability |
LLMs, images, video, audio, embeddings, and other supported tasks |
Yes, through custom provider keys |
No self-hosted Inference Providers service; compatible open models can be hosted separately |
Yes, $0.10/month for free accounts, subject to change |
Useful for exploring open models through the Hugging Face ecosystem and multiple inference partners. Confirm that each required model and task is served by an available provider before planning a migration. |
| Orq.ai |
Free within included platform allowances; provider usage and applicable fees are separate (pricing) |
500+ models across 30+ providers |
LLMs and supported multimodal models |
Yes, with 1M BYOK requests/month included before gateway fees apply |
Yes, Enterprise VPC or on-premises deployment |
Yes, included platform allowances; upstream model usage remains separate |
A strong candidate for teams seeking EU hosting, governance, and enterprise deployment flexibility. Validate residency requirements across both the gateway and the upstream model providers. |
| Modal |
$0/month Starter plan, plus metered compute beyond included credits (pricing) |
User-deployed models; no fixed catalog count comparable to an aggregator |
LLMs and custom image, video, audio, or multimodal pipelines |
Provider keys can be used in application code; no native gateway BYOK plan |
No, workloads run on Modal's managed infrastructure |
Yes, $30/month in compute credits on Starter |
Best for engineering teams building custom inference pipelines with serverless compute. Budget for the CPU, GPU, memory, and storage resources your application uses. |
| Baseten |
$0.10/1M input tokens and $0.50/1M output tokens for GPT OSS 120B; other models and deployments have separate rates (pricing) |
Curated Model APIs plus custom deployments; no fixed overall model maximum published |
LLMs and custom multimodal inference |
Not documented as a third-party provider-key gateway |
Yes, self-hosting available by arrangement |
Trial credits for new accounts; the public pricing page does not specify the amount |
A good fit for production inference on selected models, including custom deployments. Compare token-priced Model APIs with dedicated compute based on your traffic and deployment requirements. |
| GPT Proto |
$10 minimum top-up, with model-specific pay-as-you-go rates and no subscription (pricing) |
200+ models, accessed through one API key and shared balance |
LLMs, vision, image generation, and video generation |
Not publicly documented; published integration uses a GPT Proto API key |
No publicly documented self-hosted deployment |
Free web tools are advertised; a recurring free API allowance is not publicly confirmed (source, pricing) |
A practical option for teams seeking managed text, image, and video model access under one balance. OpenAI-compatible integrations can begin by updating the base URL and API key, then validating model IDs and endpoint-specific behavior. |
Comparison notes: Model coverage reflects advertised integrations or inference availability, not a guaranteed maximum or free-plan entitlement. BYOK means supplying your own upstream provider credentials. Self-hosting means deploying the gateway or platform on infrastructure you control; running a custom model on a vendor's cloud does not qualify. Free software, recurring credits, and limited trials are listed separately because they do not provide equivalent access.
Free and Open-Source Eden AI Alternatives
LiteLLM, Portkey AI's open-source gateway, Hugging Face Inference API, and OpenRouter's free-model tier are the 4 genuinely free or self-hostable alternatives to Eden AI available today.
Eden AI's free and open-source alternatives break down into 4 options worth examining:
LiteLLM — a fully open-source LLM proxy published on GitHub that teams deploy on their own infrastructure, paying no per-token markup to a third party
Portkey AI OSS — the open-source core of Portkey's gateway, self-hostable for teams that want routing and observability without a SaaS subscription
Hugging Face Inference Providers — limited free credits for selected supported models, with usage limits suited to experimentation before evaluating a paid Inference Endpoint
OpenRouter free models — a subset of OpenRouter's catalog served at zero cost, covering several capable open-source LLMs with no credit card required
Each Eden AI alternative in this free tier carries a real operational catch. LiteLLM hands teams full control, but running it in production means owning uptime, authentication, and upgrades. The ops burden is non-trivial for small engineering teams. Portkey's OSS layer removes the SaaS markup, yet the advanced guardrails and analytics that make Portkey compelling are cloud-only features.
Hugging Face's free tier imposes rate limits that make it unsuitable for sustained production traffic; teams that outgrow it move to paid Inference Endpoints. OpenRouter's free models rotate and carry lower rate ceilings than paid routes, so availability is not guaranteed for any specific model.
Choosing a free, open-source Eden AI alternative makes sense when the team has infrastructure experience, traffic is low or bursty, and avoiding vendor lock-in outweighs operational convenience. Teams running consistent production volume or needing SLA guarantees find that the engineering cost of self-hosting exceeds the markup savings within weeks.
Matching an Eden AI Alternative to Your Use Case
Choosing an Eden AI alternative starts with the primary workload: LLM access, image and media generation, document AI, or agentic orchestration. With the platforms compared, the strongest fit depends on that use case.
LLM Access Across Providers
Eden AI users seeking a single endpoint routing across multiple open-source and proprietary LLMs find Together AI a fit for hosted inference and fine-tuning, though not a like-for-like replacement for every cross-provider or document-AI workflow. Its OpenAI-compatible API offers a direct upgrade path to fine-tuning and dedicated GPU clusters. GPT Proto covers the same routing pattern with an OpenAI-compatible gateway, making it a low-friction option for basic calls from teams using the OpenAI SDK, subject to model and feature checks.
Image and Media Generation API
Among Eden AI alternatives, Replicate is the purpose-built choice for generative media workloads. Replicate hosts versioned open-source models — including image, video, and audio generators — and bills at granular compute increments, so teams pay only for the exact GPU time consumed.
PDF and Document AI
Eden AI's document AI workloads — extraction, classification, OCR, and structured output from PDFs — are best matched by providers that expose dedicated document-processing endpoints rather than general-purpose LLM completions. Eden AI itself targets this niche directly. A vision-capable model may help with image-based document inputs, but OCR and PDF workflows should be validated separately. GPT Proto's GPT-4o file-analysis API is a model-level route to assess for file inputs.
Agentic AI Workflows
Eden AI users building agentic pipelines that chain tool calls, memory, and multi-step reasoning across models benefit most from a unified API gateway rather than a single-provider SDK. GPT Proto's OpenAI-compatible layer can simplify model changes in an agent framework, but tool-call behavior and parameters must be tested for each model. The overview of AI gateways for developers provides a wider comparison of this integration pattern.
How to Choose the Right Eden AI Alternative
Choosing the right Eden AI alternative requires weighing 5 criteria in order: pricing model, model breadth, routing control, hosting and data location, and OpenAI-compatibility.
Before committing to an Eden AI alternative, work through this numbered checklist covering 5 steps:
Define your primary cost constraint. Platforms that charge a markup on every token add cost at scale; self-hosted or BYOK options eliminate that markup entirely, at the expense of infrastructure overhead.
Audit the model coverage you actually need. A platform with broad multi-modal coverage suits teams running text, image, and speech workloads together; a narrower gateway suffices for pure-text pipelines.
Assess routing control requirements. Fallback routing, load balancing, and latency-based model selection are non-negotiable for production workloads; verify whether the platform exposes these as configurable rules or hides them behind opaque automation.
Confirm data residency and hosting options. Regulated industries require on-premise or private-cloud deployment; a SaaS-only gateway disqualifies itself for those use cases regardless of price.
Verify the OpenAI-compatible API surface. Basic calls may reuse an existing SDK after changing the base URL, API key, and model ID; parameters, tool calls, streaming, errors, and media endpoints still need validation.
For Eden AI alternatives, the markup-versus-self-host trade-off is the single most decisive split. Teams with low volume and no compliance constraints accept a managed markup in exchange for zero DevOps burden. Teams with high token throughput or strict data governance self-host or use a BYOK gateway to retain full cost and data control.
Start by identifying the primary modality, then apply the five criteria above. Document and OCR workloads narrow the field to platforms with dedicated extraction capabilities; agentic pipelines call for checking API compatibility and configurable fallback behavior.
