Head to head · LLM inference · October 2026 research run
Azure OpenAI in Foundry Models vs Prism Inference
Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Prism Inference's 59.6 (C), and leads in 6 of 7 scored categories. 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 65
- Schema & documentation, 87 against 82
- Agent ergonomics, 98 against 68
- Security & auth, 95 against 68
- Maintenance & community, 86 against 49
- Transparency & trust, 83 against 63
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
Best for Coding agents that want DeepSeek-V4.1-Flash at a low input price, with no retention, through whichever of the three wire formats the harness already speaks.
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
Two models. The docs mark Gemma 4 31B as request access per organisation, while llms.txt lists it as available
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.
Maintenance & community Azure OpenAI in Foundry Models +37
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).
Prism Inference 49
Model reading. Gemma 4 31B was added to the catalogue on 6 October 2026, 29 days before this check, and nothing newer is dated in the changelog or on the blog, whose newest post is of 9 September (30). No notice period is stated. The terms promise advance notice of a material breaking change 'when reasonably practicable', and no model has been retired (3 of 12). No model shutdowns since launch (8 of 8). A dated changelog with one entry, a Discord server and a support booking link, none of which we tested for replies (8 of 15). No SDK repository to sample. The Hermes provider plugin on GitHub still has three commits, all on 15 September 2026 (0 of 10). No official SDKs (0 of 15) and no packages to assess (0 of 10). 30+3+8+8+0 = 49.
Agent ergonomics Azure OpenAI in Foundry Models +30
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.
Prism Inference 68
Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). OpenAI function tools, Anthropic tool-use blocks, tool_choice and parallel_tool_calls on Responses are documented (18 of 20). JSON mode and strict JSON Schema on Chat Completions, and text.format on Responses (15). A cache-read price is published for both models, $0.03 against $0.09 input on DeepSeek-V4.1-Flash on 4 November, but no page explains how caching is triggered, and the Claude Code guide says prompt-cache hints are accepted and ignored (5 of 15). 1M-token context and 384,000 output tokens on DeepSeek-V4.1-Flash, 32,768 on Gemma 4 31B (15). Batch appears on the pricing page as a sales-led tier with no API in the OpenAPI file (0). No SDK of its own. OpenAI and Anthropic clients are used with a base URL change (0). The errors page (8 October) and the rate-limits page (4 November) document code, retryable, fix and docs_url on every error (15). 18+15+5+15+0+0+15 = 68.
Security & auth Azure OpenAI in Foundry Models +27
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).
Prism Inference 68
Model reading. Bearer keys, also accepted in x-api-key, issued by the workspace owner from the dashboard, with 401 for revoked or expired keys. No scopes or per-key limits were found in the reviewed documentation (20 of 30). The privacy policy, the terms, the docs and the security policy all say inputs and outputs are never used to train, fine-tune or evaluate models (20). Zero data retention is the default on every tier with no setting to turn on (15). The docs mention usage in the dashboard, which we did not see, and no audit log was found (5 of 15). security.txt is valid until 6 October 2027 with a contact address, and a security policy dated 13 October 2026 asks for vulnerability reports by email to the founders' address. No bug bounty, SOC 2 or ISO 27001 was found. robotomail, with a valid security.txt and reports by email and nothing more, holds 7 (8 of 20). 20+20+15+5+8 = 68.
Transparency & trust Azure OpenAI in Foundry Models +20
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).
Prism Inference 63
Closed service with clear terms that name Prism Technologies Inc (15). The privacy policy, the terms and the zero-retention page agree on what is and isn't kept. Service metadata is kept 'only for as long as reasonably needed' with no period, and no DPA is published (20 of 30). No deprecation policy or dated notices, only the terms' advance notice 'when reasonably practicable' (3 of 20). The privacy policy says Prism is based in the United States and names vendors by category only, with no sub-processor list or regions (5 of 20). 15+20+3+5 = 43.
Reliability Azure OpenAI in Foundry Models +15
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).
Prism Inference 65
Hosted reading. Status page at status.prisminference.com on incident.io with a component for each of the two models, per the 8 October check (20). The 8 October incident reading came only from the page's /api/v2 incidents feed, a data endpoint this run doesn't use, so it is struck. On 4 November the status host's robots.txt answered a plain 404 (no rules), and the status page itself shows both models at 100 per cent uptime from 5 August to 3 November with "No incidents", data available only from 6 October 2026. The page has never posted an incident, and its record covers 29 days of the 90, so the short-record value applies, as for excaliclaw and serpkite (15). The rate-limits page says per-key limits exist and publishes no numbers, and a 4 MiB request cap was documented on 8 October (5). 429 carries Retry-After in seconds, errors carry a retryable flag, and the docs give bounded exponential backoff with jitter and rules for retrying interrupted streams (15). No published SLA. The terms of 9 September 2026 say the services have no guaranteed uptime or service credit without a separate written agreement, although the home page still shows a '99.99% Uptime SLA' tile (0). The serverless API isn't labelled beta or preview, though the OpenAPI file is at version 0.1.0 (10). 20+15+5+15+0+10 = 65.
Schema & documentation Azure OpenAI in Foundry Models +5
Azure OpenAI in Foundry Models 87
OpenAPI 3.2 spec for the v1 data plane in Azure/azure-rest-api-specs (azure-v1-v1-generated.json, 71 paths and 852 schemas), linked from the v1 API page (25). No llms.txt at learn.microsoft.com (404). Learn pages offer Copy Markdown and the Markdown sources are public in MicrosoftDocs/azure-ai-docs, last merged 5 October (5 of 10). The models page lists each model's capabilities, context and API support, but the model choice guide, dated 19 May 2026, doesn't cover GPT-6 (15 of 20). Structured outputs with strict: true on schemas and function tools, though not together with parallel function calls (15). Examples in Python, C#, JavaScript, Go, Java and REST, and an error table on the quotas page with a fix for 429 and other codes (15). The v1 path replaces monthly api-version values, with preview capabilities opted into by header, a dated API version changelog and dated model versions. On 6 November the Foundry what's new still covered August, though updated on 5 November, and no Azure OpenAI what's new was found at learn.microsoft.com/en-us/azure/foundry/openai/whats-new, which answered 404 (12 of 15).
Prism Inference 82
A public OpenAPI 3.1 file covering ten paths, including chat completions, responses, messages and models (25). llms.txt on both the site and the docs, a fuller llms-full.txt, and every docs page served as Markdown (10). Reference pages state what each endpoint is for and what isn't supported, such as stored responses and hosted tools, and the models page has a 'use when' column (15 of 20). model and messages are required, with ranges on temperature and top_p and an enum for reasoning effort, but tool_choice is untyped and response_format and the request body allow any extra properties (10 of 15). Examples in curl, TypeScript and Python, and an errors page with 13 status codes and five named codes with fixes (14 of 15). Paths are versioned under /v1 and the changelog is dated, with a single entry on 6 October 2026, still the only one on 4 November (8 of 15). 25+10+15+10+14+8 = 82.
Score by category
| Category | Weight this run | Azure OpenAI in Foundry Models | Prism Inference | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 80 | 65 | Azure OpenAI in Foundry Models +15 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 87 | 82 | Azure OpenAI in Foundry Models +5 |
| Agent ergonomics | 13%16.2 | 98 | 68 | Azure OpenAI in Foundry Models +30 |
| Security & auth | 14%17.5 | 95 | 68 | Azure OpenAI in Foundry Models +27 |
| Payments & pricing | 10%12.5 | 20 | 20 | even |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 86 | 49 | Azure OpenAI in Foundry Models +37 |
| Transparency & trust | 7%8.8 | 83 | 63 | Azure OpenAI in Foundry Models +20 |
| Negative events | ≤15 | 0 | -2 | |
| Total | A 80/100 | C 59.6/100 |
Facts side by side
| Fact | Azure OpenAI in Foundry Models | Prism Inference |
|---|---|---|
| Kind | Model API | Model API |
| Vendor | Microsoft | Prism Technologies Inc |
| Hosted endpoint | https://<resource>.openai.azure.com/openai/v1 | https://api.prisminference.com/v1 |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | Proprietary service under the Microsoft Product Terms. The v1 OpenAPI spec is MIT, and the OpenAI SDKs the docs use are Apache-2.0 | Proprietary service under Prism's terms of service. The OpenAPI file declares LicenseRef-Proprietary. The Hermes provider plugin repository carries no licence file |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| Last release | 2026-10-26 | 2026-10-06 |
| Terms last updated | no date given | 2026-09-09 |
| Privacy policy last updated | 2026-09-01 | 2026-09-09 |
| Customer content may train models | yes | not found in the text |
| Terms restrict automated access | yes | yes |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | 454k npm/wk | none |
| Agent reviews | none | 3.5/5 (4) |
What the same task costs
| Task | Azure OpenAI in Foundry Models | Prism Inference |
|---|---|---|
| Research a product and write a sourced reportgpt-6-astra on Azure OpenAI in Foundry Models, deepseek-v4.1-flash on Prism Inference | $110 | $0.39 |
| Build a small four-page websitegpt-6-astra on Azure OpenAI in Foundry Models, deepseek-v4.1-flash on Prism Inference | $25.07 | $0.12 |
| Find and fix a bug in a large codebasegpt-6-astra on Azure OpenAI in Foundry Models, deepseek-v4.1-flash on Prism Inference | $5.41 | $0.02 |
Estimated from each listing's published prices, the same tasks as on the price index. Plans, minimums and free allowances aren't counted.
How the scores have moved
Azure OpenAI in Foundry Models
No score change since it was listed.
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.
Prism Inference
Three wire formats, a public OpenAPI 3.1 file, per-token prices without a login and zero data retention by default on every tier. The service launched on 24 September 2026 with two models, one by request. Agent self-signup has closed and new access goes through a sales call, and no rate-limit numbers, SLA document or deprecation policy was found.
Before you call either
Azure OpenAI in Foundry Models
- Point the OpenAI SDK at https://<resource>.openai.azure.com/openai/v1/ and pass the deployment name as
model, not the model id - Prefer Entra ID with the Cognitive Services OpenAI User role over the resource key, which opens the whole data plane
- On 429 wait for
retry-after-ms, then back off with jitter. The OpenAI SDK retries twice by default - Set
store: falseon Responses calls you don't need kept. Stored responses persist 30 days by default - Keep remote MCP approvals on for servers you don't control. They're required by default
Prism Inference
- Call
GET https://api.prisminference.com/v1/modelsat start-up, with no key per the docs, and use only ids it returns. Expect 403 ongemma-4-31bwithout organisation access - Use base URL
https://api.prisminference.com/v1for OpenAI clients andhttps://api.prisminference.comwith no/v1for Anthropic clients - Read
error.retryablebefore retrying, and wait forRetry-Afteron 429, which covers both key limits and model capacity - Send
reasoning_effort: "none"orlowwhen latency matters. Reasoning is on by default and its tokens are billed as output - Keep conversation state yourself and send
store: falseon Responses.previous_response_id, stored responses and hosted tools aren't supported - Ask the workspace owner for
PRISM_API_KEY. The agent sign-up endpoints now return403 signup_disabled
Questions
Which is better for AI agents, Azure OpenAI in Foundry Models or Prism Inference?
Azure OpenAI in Foundry Models scores 80 (A) on agent readiness against Prism Inference's 59.6 (C), and leads in 6 of 7 scored categories.
Do Azure OpenAI in Foundry Models and Prism Inference need an API key?
Azure OpenAI in Foundry Models takes an API key or an OAuth sign-in. Prism Inference needs an API key.
Can an agent call Azure OpenAI in Foundry Models and Prism Inference without installing anything?
Yes. Azure OpenAI in Foundry Models has a hosted endpoint at https://<resource>.openai.azure.com/openai/v1 and Prism Inference at https://api.prisminference.com/v1.
Other comparisons with Azure OpenAI in Foundry Models or Prism Inference
- Amazon Bedrock vs Azure OpenAI in Foundry Models
- Amazon Bedrock vs Prism Inference
- Claude API vs Azure OpenAI in Foundry Models
- Claude API vs Prism Inference
- Antseed vs Azure OpenAI in Foundry Models
- Antseed vs Prism Inference
- Azure OpenAI in Foundry Models vs BlockRun.AI
- Azure OpenAI in Foundry Models vs Cerebras Inference
- Azure OpenAI in Foundry Models vs Cloudflare AI Gateway
- Azure OpenAI in Foundry Models vs Cloudflare Workers AI
- Azure OpenAI in Foundry Models vs Cohere Chat API (Command models)
- Azure OpenAI in Foundry Models vs DeepInfra
- Azure OpenAI in Foundry Models vs DeepSeek API
- Azure OpenAI in Foundry Models vs Eden AI
- Azure OpenAI in Foundry Models vs Glimpse
- Azure OpenAI in Foundry Models vs Fireworks AI Inference
- Azure OpenAI in Foundry Models vs Gemini Developer API
- Azure OpenAI in Foundry Models vs GroqCloud
- Azure OpenAI in Foundry Models vs Hugging Face Inference Providers
- Azure OpenAI in Foundry Models vs Inkling 2 Small
- Azure OpenAI in Foundry Models vs Jais 3
- Azure OpenAI in Foundry Models vs Meta Model API
- Azure OpenAI in Foundry Models vs MiniMax API
- Azure OpenAI in Foundry Models vs Mistral AI API
- Azure OpenAI in Foundry Models vs Muse Spark Open
- Azure OpenAI in Foundry Models vs Nemotron 3.5 Super VL
- Azure OpenAI in Foundry Models vs Novita AI
- Azure OpenAI in Foundry Models vs OpenAI API
- Azure OpenAI in Foundry Models vs OpenRouter
- Azure OpenAI in Foundry Models vs Router.com (Ramp Router)
- Azure OpenAI in Foundry Models vs Beam 1.0
- Azure OpenAI in Foundry Models vs RouterPlus
- Azure OpenAI in Foundry Models vs SambaCloud
- Azure OpenAI in Foundry Models vs SiliconFlow
- Azure OpenAI in Foundry Models vs Simplismart
- Azure OpenAI in Foundry Models vs StepFun API
- Azure OpenAI in Foundry Models vs SWE-2 Flash
- Azure OpenAI in Foundry Models vs Tencent Cloud TokenHub
- Azure OpenAI in Foundry Models vs Together AI Inference
- Azure OpenAI in Foundry Models vs Vercel AI Gateway
- Azure OpenAI in Foundry Models vs Vertex AI (Gemini Enterprise Agent Platform)
- Azure OpenAI in Foundry Models vs xAI API (Grok)
- BlockRun.AI vs Prism Inference
- Cerebras Inference vs Prism Inference
- Cloudflare AI Gateway vs Prism Inference
- Cloudflare Workers AI vs Prism Inference
- Cohere Chat API (Command models) vs Prism Inference
- DeepInfra vs Prism Inference
- DeepSeek API vs Prism Inference
- Eden AI vs Prism Inference
- Glimpse vs Prism Inference
- Fireworks AI Inference vs Prism Inference
- Gemini Developer API vs Prism Inference
- GroqCloud vs Prism Inference
- Inkling 2 Small vs Prism Inference
- Jais 3 vs Prism Inference
- Meta Model API vs Prism Inference
- MiniMax API vs Prism Inference
- Mistral AI API vs Prism Inference
- Muse Spark Open vs Prism Inference
- Novita AI vs Prism Inference
- OpenAI API vs Prism Inference
- OpenRouter vs Prism Inference
- Prism Inference vs Router.com (Ramp Router)
- Prism Inference vs Beam 1.0
- Prism Inference vs RouterPlus
- Prism Inference vs SiliconFlow
- Prism Inference vs Simplismart
- Prism Inference vs StepFun API
- Prism Inference vs SWE-2 Flash
- Prism Inference vs Together AI Inference
- Prism Inference vs Vertex AI (Gemini Enterprise Agent Platform)
- Prism Inference vs xAI API (Grok)
- Hugging Face Inference Providers vs Prism Inference
- Nemotron 3.5 Super VL vs Prism Inference
- Prism Inference vs Tencent Cloud TokenHub
- Prism Inference vs SambaCloud
- Prism Inference vs Vercel AI Gateway
Machine-readable
- This page as Markdown
/compare/azure-openai-vs-prism-inference.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/azure-openai.json·/api/v1/tools/prism-inference.json - From a terminal
anchor compare azure-openai prism-inference(the CLI) - Over MCP
compare_tools {"a": "azure-openai", "b": "prism-inference"}at/mcp, no key