Head to head · LLM inference · October 2026 research run

Azure OpenAI in Foundry Models vs Eden AI

Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on payments & pricing. Both do llm inference.

Best model APIs and inference for AI agents · All 830 models comparisons

Which one, for what

Azure OpenAI in Foundry Models A

Best for Teams on Azure that need OpenAI models with Entra ID, private networking, EU or US data zones or FedRAMP scope, and one resource that also serves DeepSeek, Llama, Mistral and Grok models.

Ahead on

  • Reliability, 80 against 33
  • Schema & documentation, 87 against 81
  • Agent ergonomics, 98 against 75
  • Security & auth, 95 against 82
  • Maintenance & community, 86 against 58
  • Transparency & trust, 83 against 55

Also in its favour

  • Agent-ready, a grade of BB or better

Watch for

Intermittent failures and 5xx errors in Sweden Central for about six hours on 29 September 2026

Eden AI C

Best for Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing.

Ahead on

  • Payments & pricing, 30 against 20

Watch for

No public status page, incident history or SLA found

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Reliability Azure OpenAI in Foundry Models +47

Azure OpenAI in Foundry Models 80

Azure status page with post-incident reviews, listing Azure OpenAI Service, Foundry Models and Foundry Agent Service as components (20). One incident in the 90 days to 6 November 2026 names Azure OpenAI, and no review after it does, intermittent request failures, higher latency and HTTP 5xx errors in Sweden Central from 10:03 to 15:58 UTC on 29 September 2026 (tracking 7QL5-Z50), counted as one major outage as in the Foundry fine-tuning dossier. The 23 July West US review and the 30 September gateway incident don't name it (10). Quota tiers from Free to Tier 6 with TPM and RPM per model and deployment type, 1,000 RPM and 1,000,000 TPM for each GPT-6 model on Global Standard at Tier 1 (15). 429 responses carry retry-after-ms, every response carries x-ratelimit-* headers, and the quota guide gives exponential backoff with jitter and SDK retry settings (15). The models page says models sold by Azure are covered by Azure service-level agreements and links the Online Services SLA. The consolidated SLA document wouldn't download on 6 October and wasn't retried on 6 November, so the clause rests on Microsoft's docs, read the same way as the 5 October Azure Speech check (10). The v1 API is GA and the GPT-6 models carry no preview label (10).

Eden AI 33

Router, read on the hosted lines. No status page is linked from the site or docs, and status.edenai.co didn't resolve for us on 6 November 2026 (0). No incident history to read (5). The rate-limits page gives 10 requests a second per account, shared across keys, while the plans page gives 7 a second, raisable to 15, so the figure is documented but inconsistent (10). Fallback retries the next model or provider on a 429 or error inside one request, but no client-facing 429 or Retry-After guidance was found (8). No SLA published; 'Dedicated support & SLA' is listed only for the custom Advanced plan, and the pricing page's '99.99%' uptime is a claim without a status page behind it (0). The v3 API is GA (10). 0+5+10+8+0+10 = 33.

Maintenance & community Azure OpenAI in Foundry Models +28

Azure OpenAI in Foundry Models 86

Model reading. GPT-6.1 Terra released on Azure on 26 October 2026 and a gpt-chat-latest preview of 7 October was added, after GPT-6.1 Sol on 29 September (30). GA models get a retirement date 18 months after launch, set at release and readable through the Models API, with at least 60 days' email and Service Health notice, and previews at least 30 days, so a GA retirement is known more than six months ahead (12 of 12). Many shutdown dates in the 90 days to 6 November, most of them previews or partner models, among them DeepSeek-R1 (13 August), MAI-Image-2 and 2e (15 August), model-router previews (30 August), MAI-Transcribe-1 (15 September), MAI-Image-2.5 previews (1 October), the 2025-03-20 audio models and sora-2 (15 October), a Cohere Command A Plus preview (16 October) and gpt-image-1 (23 October), each in the schedule with a replacement where one exists (4 of 8). The Foundry what's new page, still on August when read on 6 November, plus Microsoft Q&A and paid support; no Azure OpenAI what's new was found (10 of 15). The SDKs are OpenAI's repositories, replies not sampled (5 of 10). Current official SDKs, openai 3.46.0 on PyPI (5 November) and 7.53.0 on npm, plus Microsoft's @azure/openai 2.0.0 companion (15). Supported runtimes stated, Python 3.9 or later and Node.js 20 or later, though openai 3.46.0 requires Python 3.10 (10).

Eden AI 58

Closed service, read on the model lines. The docs repository changed on 5 and 6 November 2026, including retiring Nova Reel and Veo from video generation, and the terms were updated 22 October (30). No public changelog, so dated API changes in the last 90 days come only from docs commits (12 of 20). Chat support within 48 working hours, no public changelog (8). No SDK of its own, and the MCP server isn't in the official MCP registry (5). Nothing to judge package health by beyond the docs repository (3). 30+12+8+5+3 = 58.

Transparency & trust Azure OpenAI in Foundry Models +28

Azure OpenAI in Foundry Models 83

Closed service under the Microsoft Product Terms, with the v1 spec under MIT and the OpenAI SDKs under Apache-2.0 (15). The data privacy page agrees with the product terms on no training and states where data is processed and stored by deployment type, but gives no retention period for the human-review store and sits beside a 30-day default for Responses data (24 of 30). A published lifecycle policy and a retirement schedule with dates and replacements, but on 6 November the schedule listed gpt-realtime-mini 2025-10-06 and 2025-12-15 twice each with different retirement dates, and no GPT-6 model yet (18 of 20, down from 20). Data locations stated for Standard, Data Zone and Global deployments, and a public sub-processor list per the 5 October Azure Speech check, not re-read (20).

Eden AI 55

Editorial half only. Closed service under terms last updated 22 October 2026, naming Eden AI SAS and French law with courts in Lyon (15). The data retention page, terms and DPA agree that content isn't stored by default, and the docs carry a per-provider table of training, retention and ZDR (27). No deprecation policy found; models are dropped in docs updates without dated notice that we found (5). The DPA's Annex 2 names operational subprocessors (AWS EMEA, ClickHouse, Sentry, Metabase, Stripe, Brevo and others) with their roles, and the EU endpoint keeps routing in the EU (18). 15+27+5+18 = 65.

Agent ergonomics Azure OpenAI in Foundry Models +23

Azure OpenAI in Foundry Models 98

Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). Tool use with parallel calls and a forced call by naming the function in tool_choice, 18 of 20 because gpt-6.1-sol calls tools only through the Responses API (18). Strict structured outputs (15). Prompt caching from 1,024 tokens, cached input at 0.1x on GPT-6 ($1 per million on Astra) and cache writes at 1.25x from GPT-5.6 on, with explicit breakpoints (15). 1,050,000-token context on GPT-6 and GPT-6.1, input capped at 922,000 (15). Batch at 50% off Global Standard with a 24-hour target (10). The docs use OpenAI's own SDKs for Python, JavaScript, C#, Go and Java against the v1 endpoint (10). 429 and quota errors documented with retry headers (15). Calls name a deployment rather than a model, so each model must be deployed in the resource first, which the model checklist doesn't score.

Eden AI 75

Router, read on the model lines. Chat completions, Responses and an Anthropic Messages route in the OpenAI shape, with tool calling depending on the routed model (14 of 20) and structured output likewise (10 of 15). Caching is named in the terms as part of the service, without a per-model price table we read (8 of 15). Context depends on the model; the keyless /v3/models catalogue lists capabilities, prices and regions per model so an agent can choose (12 of 15). A Batches API (10 of 10). No SDK of its own; the docs use the OpenAI Python and TypeScript SDKs, and a hosted MCP server exposes about 40 expert-model tools plus upload_file, check_job and list_models (21 of 25). 14+10+8+12+10+21 = 75.

Security & auth Azure OpenAI in Foundry Models +13

Azure OpenAI in Foundry Models 95

Model reading. Microsoft Entra ID tokens with Azure roles (the Cognitive Services OpenAI User role for calls), managed identities, and key authentication that can be disabled per resource, or two regenerable resource keys in the api-key header. No documented route puts the key in a URL query string (30). Prompts, completions, embeddings and training data aren't used to train foundation models without the customer's permission or instruction, per the data privacy page updated 4 August 2026 (20). Flagged prompts and completions may be stored in the customer's geography for human abuse review, with no retention period stated, and approved customers can turn that storage off through modified abuse monitoring. Responses API data is kept 30 days by default unless store is false (12 of 15). Azure Monitor resource logs and the subscription activity log, as read in the Foundry fine-tuning dossier (15). MSRC coordinated disclosure policy and Microsoft's bounty programme, both named in microsoft.com's security.txt, and Azure OpenAI is listed in FedRAMP High and DoD IL2 scope in Azure public regions. The security.txt passed its Expires date on 2026-09-23 and was still expired on 6 November, which the Bedrock and S3 dossiers mark down by 2, applied here too (18 of 20, down from 20 on 6 October for consistency).

Eden AI 82

Router, read on the model lines. Bearer keys with per-key budgets, expiry and attribution, a key management API, and deny-by-default guardrails that limit models per member, role or key (25). The data retention page says request and response content isn't stored and data isn't used to train models by default (18). Content logging is opt-in, async results are deleted after 7 days, and an organisation can enforce Zero Data Retention and region rules; the EU endpoint refuses non-EU models with 451 (13). Cost and provider per response, and a monitoring dashboard by key (12). The security page says Eden AI is SOC 2 and ISO 27001 certified and links a trust centre; /.well-known/security.txt returns 404 and no disclosure policy was found (14). 25+18+13+12+14 = 82.

Payments & pricing Eden AI +10

Azure OpenAI in Foundry Models 20

No x402, MPP or L402 (0). Per-1M-token prices are public in the Azure Retail Prices API without a login, while the pricing page fills its table with JavaScript and showed GPT-6 prices as pending on 6 October (20). The quota tiers include a Free tier, but an Azure subscription needs a payment method (0). A person signs up for Azure in a browser and creates a resource and a deployment before the first call (0).

Eden AI 30

No x402, MPP or L402 (0). Provider prices with no markup plus a 5.5% platform fee, published per model in the keyless catalogue (20). llms.txt says some models are billed $0 for tests, but whether a new account can call them without buying credits isn't stated (10). A person signs up in a browser and buys credits through Stripe (0). 0+20+10+0 = 30.

Score by category

CategoryWeight this runAzure OpenAI in Foundry ModelsEden AIEdge
Reliability16%208033Azure OpenAI in Foundry Models +47
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28781Azure OpenAI in Foundry Models +6
Agent ergonomics13%16.29875Azure OpenAI in Foundry Models +23
Security & auth14%17.59582Azure OpenAI in Foundry Models +13
Payments & pricing10%12.52030Eden AI +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88658Azure OpenAI in Foundry Models +28
Transparency & trust7%8.88355Azure OpenAI in Foundry Models +28
Negative events≤1500
TotalA 80/100C 59.9/100

Facts side by side

FactAzure OpenAI in Foundry ModelsEden AI
KindModel APIModel router
VendorMicrosoftEden AI SAS
Hosted endpointhttps://<resource>.openai.azure.com/openai/v1https://mcp.edenai.run/mcp
TransportsHTTPHTTP, Streamable HTTP
AuthOAuth or keyAPI key
PricingPay per usePay per use
x402nono
LicenceProprietary service under the Microsoft Product Terms. The v1 OpenAPI spec is MIT, and the OpenAI SDKs the docs use are Apache-2.0none
Read-only variant documentednono
llms.txtnoyes
Last release2026-10-262026-11-05
Terms last updatedno date given2026-10-22
Privacy policy last updated2026-09-012026-10-22
Customer content may train modelsyesnot found in the text
Terms restrict automated accessyesnot found in the text
Terms restrict benchmarkingyesnot found in the text
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textnot found in the text
Popularity454k npm/wknone

Verdicts

Azure OpenAI in Foundry Models

An OpenAI-compatible v1 API with a public OpenAPI spec, Entra ID roles in place of shared keys and FedRAMP High scope, with GPT-6 and GPT-6.1 at OpenAI's list prices on Global Standard. Access needs an Azure subscription with a card and a deployment per model, and a 29 September 2026 incident caused about six hours of failures in Sweden Central.

Eden AI

Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.

Before you call either

Azure OpenAI in Foundry Models

  1. Point the OpenAI SDK at https://<resource>.openai.azure.com/openai/v1/ and pass the deployment name as model, not the model id
  2. Prefer Entra ID with the Cognitive Services OpenAI User role over the resource key, which opens the whole data plane
  3. On 429 wait for retry-after-ms, then back off with jitter. The OpenAI SDK retries twice by default
  4. Set store: false on Responses calls you don't need kept. Stored responses persist 30 days by default
  5. Keep remote MCP approvals on for servers you don't control. They're required by default

Eden AI

  1. Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them
  2. Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed
  3. Set max_tokens to 500 or more for reasoning models, or the answer can come back empty
  4. Pass a fallbacks list so a provider 429 or error retries inside one request
  5. Poll check_job for MCP tools marked long-running instead of calling them again

Questions

Which is better for AI agents, Azure OpenAI in Foundry Models or Eden AI?

Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on payments & pricing.

Do Azure OpenAI in Foundry Models and Eden AI need an API key?

Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Eden AI needs an API key.

Can an agent call Azure OpenAI in Foundry Models and Eden AI without installing anything?

Yes. Azure OpenAI in Foundry Models has a hosted endpoint at https://<resource>.openai.azure.com/openai/v1 and Eden AI at https://mcp.edenai.run/mcp.

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