GILD verdict
Start from the models you need, because teams at scale buy by model, as Fin does across Vertex AI and Azure.
Fin runs Claude on Vertex AI and OpenAI models on Azure. Then choose the cloud where your identity, data and spend commitments already live, because procurement and security review go fastest there: Agent Platform for Gemini and Claude in one Google Cloud project, Foundry for OpenAI's GPT models sold by Azure. Price per token does not pick a winner. Claude Opus 5.5 costs US$4,800 a month on both at GILD's 60,000-task workload, and only Foundry sells its fast mode. At 1 billion input and 200 million output tokens a month, gpt-oss-120b costs US$162 on Agent Platform and US$270 on Foundry, while Llama 4 Maverick costs US$580 and US$450. Test EU capacity on Agent Platform before you commit an EU workload.
Teams that run at scale use both clouds by model: Fin serves Claude through Vertex AI beside Anthropic and Bedrock and OpenAI models through Azure, failing over between vendors (Aug 2025), while Grab ran its data classification on one shared Azure OpenAI quota of 240,000 tokens per minute (Jul 2024). The catalogs split the decision: Agent Platform carries Gemini and Claude, and Foundry sells OpenAI's GPT models directly. At GILD's workload of 60,000 Claude Opus 5.5 tasks a month, both bill US$4,800, and only Foundry offers Opus 5.5 fast mode. Requesty's gateway saw 96% of Gemini requests on Vertex complete in April 2026, against 78% on Azure.
What teams report
Run both 3
Fin (Intercom)
Fin keeps vendor redundancy for every model: Claude traffic can be served by Vertex AI, Anthropic's API or Bedrock, and OpenAI models by Azure or OpenAI, with automatic failover between them (Aug 8, 2025).
“For example, Anthropic models can be served by AWS Bedrock, GCP Vertex, or Anthropic’s own infrastructure; OpenAI models are served by either Azure or OpenAI itself.”
Fin AI research team, Authors of Fin's reliability write-up, Fin (Intercom)Fin AI Research, , write-up SlackOn Gemini Enterprise Agent Platform
Slack added Vertex AI beside Amazon Bedrock as a second serving cloud for Slack AI by early 2026, for redundancy and a wider model catalog, and reports about 67% lower latency on high-velocity, low-token workloads from matching models to features (May 28, 2026).
“By early-2026 we officially expanded our footprint to include Google Cloud Platform (GCP) Vertex AI, not just as a failover for redundancy, but as a strategic engine to accelerate product innovation through access to a broader catalog of state-of-the-art models.”
Shaurya Kethireddy, Lead Member of Technical Staff, SlackEngineering at Slack, , write-up ZalandoOn Gemini Enterprise Agent Platform
Zalando's ML platform team has run a LiteLLM proxy since January 2024 that serves engineers models from OpenAI, AWS Bedrock and Google Vertex (Aug 14, 2026).
“…our ML platform team deployed in January 2024 a LiteLLM based API proxy with access to models from different providers (now: OpenAI, AWS Bedrock, and Google Vertex).”
Bartosz Ocytko, Executive Principal Engineer, ZalandoZalando Engineering, , write-up
Adopted 1
GrabOn Microsoft Foundry
Grab's data classification on Azure OpenAI scanned more than 20,000 data entities in its first month, with every model deployment sharing one 240,000 tokens-per-minute quota under a single account (Jul 15, 2024).
“Currently, all Azure OpenAI model deployments share the same quota under one account, which is set at 240K tokens per minute.”
Hualin Liu and co-authors, Grab engineers, GrabGrab Tech Blog, , write-up
Choosing between Gemini Enterprise Agent Platform and Microsoft Foundry
Choose Gemini Enterprise Agent Platform if
- Your identity, data and spend commitments already sit in Google Cloud, as Slack's second model cloud and Zalando's gateway route do.
- You need Gemini 4 Argon or the Gemini Flash models next to Claude under one IAM policy.
- You want US or EU multi-region endpoints and Provisioned Throughput bought by the week, and you will test EU capacity first: one UK team saw up to 80% 429 errors outside the us endpoint in October 2026.
Choose Microsoft Foundry if
- Your identity sits in Microsoft Entra ID and your spend counts toward an Azure commitment.
- You need OpenAI's GPT models sold directly by Azure, as Fin and Grab do, with Data Zone deployments in the US, EU or Asia Pacific.
- You want Claude Opus 5.5 fast mode inside a cloud contract: it runs on Azure-hosted Foundry deployments and not on Google-managed Claude.
- You run Llama 4 Maverick at volume, where Azure's Global Standard rate is lower than Model Garden's.
Side by side
| Dimension | Gemini Enterprise Agent Platform | Microsoft Foundry |
|---|---|---|
| Choose it if | Choose Agent Platform if your workloads run on Google Cloud and you need Gemini and Claude in the same project1 | Choose Foundry if your identity sits in Microsoft Entra ID and you need OpenAI's GPT models sold by Azure9 |
| Model catalog | Model Garden: Gemini 4 Argon and the Gemini Flash models, Anthropic's Claude family, and open models such as Gemma, Llama, DeepSeek and gpt-oss-120b12 | More than 10,000 models from Microsoft, OpenAI, Anthropic, Meta and others; Azure OpenAI models are sold directly by Azure911 |
| Pay-per-token options | Standard, Priority, Flex and Batch PayGo; the global endpoint carries the list price, and non-global endpoints cost 10% more for Gemini 3 and later2 | Global Standard, Data Zone Standard and regional Standard; Global Standard launches first at the lowest price10 |
| Batch | Batch rows per model, such as gpt-oss-120b at US$0.045 input and US$0.18 output per million tokens against US$0.09 and US$0.36 on Standard2 | Global Batch and Data Zone Batch at a 50% discount, with a 24-hour window10 |
| Reserved capacity | Provisioned Throughput in GSUs: US$7.14 per GSU-hour on a 1-week term down to about US$2.74 on a 1-year term, global24 | Provisioned throughput units in Global, Data Zone and regional deployments, with spillover of excess traffic to a standard deployment1014 |
| Shared capacity | Standard PayGo tiers follow 30-day organization spend: 500,000 tokens per minute at Tier 1 up to 10,000,000 at Tier 4 for Gemini Pro and Argon. A UK team saw up to 80% 429 errors on London, EU and global endpoints at about 0.5 requests a second, and none on us (Oct 21, 2026)323 | Quota tiers that rise automatically with usage, from a Free Tier upward; Grab's Azure OpenAI deployments shared one 240,000 tokens-per-minute quota (Jul 2024)1321 |
| Cost at a stated workload: gpt-oss-120bGILD's calculation from published rates, fetched Oct 28, 2026: monthly tokens times each platform's published per-million rate, with no caching, batch or commitment discounts. | US$162 a month for 1 billion input and 200 million output tokens at US$0.09 and US$0.36 per million (GILD calculation from Google's list price, Oct 28, 2026)2 | US$270 a month for the same workload at Global Standard US$0.15 and US$0.60 per million (GILD calculation from Azure's retail price, East US 2, Oct 28, 2026)15 |
| Cost at a stated workload: Llama 4 MaverickGILD's calculation from published rates, with the same inputs as the row above. | US$580 a month for 1 billion input and 200 million output tokens at US$0.35 and US$1.15 per million (GILD calculation, Oct 28, 2026)2 | US$450 a month for the same workload at Global Standard US$0.25 and US$1.00 per million (GILD calculation, East US 2, Oct 28, 2026)16 |
| Monthly bill at one workload: Claude Opus 5.5GILD's calculation from published rates, fetched Oct 28, 2026: 2,000 tasks a day for 30 days, each with 10,000 input tokens and 2,000 output tokens and no caching, at Opus 5.5's list prices on each route, with the 10% regional premium both clouds charge on US and EU routes. Taxes, committed-spend discounts and negotiated rates are excluded. | US$4,800 a month on Google-managed Claude Opus 5.5 at US$4 input and US$20 output on the global endpoint; US$5,280 on the us or eu endpoints. No fast mode on this route224 | US$4,800 a month at the same list price on Global; US$5,280 on the US route; US$9,600 in fast mode on Azure-hosted deployments at US$8 and US$402425 |
| Claude Opus 5.5 fast mode | Not on Google-managed Claude in Agent Platform; Anthropic-managed Claude Models on Google Cloud offer it at US$8 input and US$40 output25 | Offered on Azure-hosted deployments as a separate claude-opus-5-5-fast model at US$8 input and US$40 output; not on Anthropic-hosted deployments25 |
| What teams run on each | Fin fails Claude traffic over across Vertex AI, Anthropic and Bedrock (Aug 2025); Slack added Vertex AI as Slack AI's second model cloud (May 2026); Zalando serves Vertex models through its LiteLLM gateway (Aug 2026)181920 | Fin serves OpenAI models through Azure or OpenAI (Aug 2025); Grab ran data classification on Azure OpenAI with one 240,000 tokens-per-minute quota shared across deployments (Jul 2024)1821 |
| Data handling | No training on customer data without permission; zero data retention requires opting out of abuse-monitoring prompt logging and caching6 | Prompts and completions are not available to OpenAI or other model vendors and are not used to train foundation models without permission12 |
| Data residency | Global endpoint, us or eu multi-region endpoints, or named regional endpoints5 | Global, Data Zone (US, EU or Asia Pacific), or regional deployments within a customer-specified geography10 |
| Agents | Agent Development Kit, Agent Runtime with Memory Bank for long-running agents, and Agent Identity, Registry and Gateway1 | Foundry Agent Service: declarative prompt agents and hosted agents that run your own code, extended with Foundry Toolbox tools9 |
| Identity and governance | Google Cloud IAM and service accounts, VPC Service Controls, CMEK, and Cloud Audit Logs78 | Microsoft Entra ID, role-based access control, network isolation and Azure Policy under one Azure resource9 |
| Measured success rate | 96% of Gemini requests through Vertex completed without an upstream error on Requesty's gateway in April 202617 | 78% on Azure in the same data, the lowest of the major routes Requesty measured17 |
What practitioners report, side by side
Each product's figures come from its own practitioners, for the group you pick.
Overall signal
Gemini Enterprise Agent Platform reads −27 and Microsoft Foundry −26, each from its own practitioners. Gemini Enterprise Agent Platform: 15 positive, 24 negative of 45. Microsoft Foundry: 9 positive, 20 negative of 36.
The score counts the authors from all practitioners that take a side, one vote each with their latest view, and is how far positive votes lead negative ones, per 100 votes, so Gemini Enterprise Agent Platform's −27 rests on votes split 12 positive, 6 mixed and 23 negative and Microsoft Foundry's −26 on 9, 7 and 18.
A lead of a fifth of the votes reads positive and a lead of half strong positive, with the same lines below zero. The dots show each source, positive, mixed, negative. Run a pilot on your own prompts to measure output quality and cost per task.
Footprint on the AI Application Platform stack
Both cover the same 9 layers at the same depth. Coverage is each product's placement on this stack, as its product page shows it. Core is a job the product owns; Supports and Touches are jobs it helps with. Coverage says nothing about how well a product does them.
| Stage | Gemini Enterprise Agent Platform | Microsoft Foundry |
|---|---|---|
| Model2 layers | Core 1, Supports 1 | Core 1, Supports 1 |
| Build2 layers | Supports 2 | Supports 2 |
| Data1 layer | Supports 1 | Supports 1 |
| Evaluate1 layer | Supports 1 | Supports 1 |
| Operate3 layers | Core 1, Supports 2 | Core 1, Supports 2 |
Show all 9 layers
| Layer | Gemini Enterprise Agent Platform | Microsoft Foundry |
|---|---|---|
| Model | ||
| Model APIs | Core | Core |
| Model gateway | Supports | Supports |
| Build | ||
| Orchestration | Supports | Supports |
| Tool use | Supports | Supports |
| Data | ||
| Retrieval | Supports | Supports |
| Evaluate | ||
| Evaluation | Supports | Supports |
| Operate | ||
| Observability | Supports | Supports |
| Cloud deployment | Core | Core |
| Guardrails | Supports | Supports |
What practitioners praise
Among all practitioners, Gemini Enterprise Agent Platform alone has four praise themes that reach 5 sources from 3 authors. Model Choice & Claude Access and Token Pricing lead, at 10 of 10 and 5 of 8. Microsoft Foundry alone has four praise themes that reach 5 sources from 3 authors. Model Catalog & Choice and Contracts, Data Terms & Identity lead, at 11 of 16 and 8 of 10.
| Praised for | Gemini Enterprise Agent Platform | Microsoft Foundry |
|---|---|---|
| Model Choice & Claude Access | 10 of 10 | Not a theme in its sources |
| Token Pricing | 5 of 8 | Not a theme in its sources |
| Reliability vs Direct APIs | 5 of 10 | Not a theme in its sources |
| Compliance & Data Residency | 4 of 7 | Not a theme in its sources |
| Model Catalog & Choice | Not a theme in its sources | 11 of 16 |
| Contracts, Data Terms & Identity | Not a theme in its sources | 8 of 10 |
| Cost | Not a theme in its sources | 3 of 5 |
| Developer Experience | Not a theme in its sources | 3 of 10 |
Each count is the sources that praise a theme, or raise it as a concern, out of those that discuss it. A row pairs the two products when both carry a theme under the same or an equivalent name.
A count ending in "so far" has under 5 sources from 3 authors among all practitioners. "Not a theme in its sources" means GILD found no theme of that name in that product's sources.
What practitioners raise as concerns
Among all practitioners, Gemini Enterprise Agent Platform alone has six concern themes that reach 5 sources from 3 authors. Quotas & 429 Errors and Naming & Product Sprawl lead, at 10 of 11 and 6 of 7. Microsoft Foundry alone has six concern themes that reach 5 sources from 3 authors. Agent Service & Tool Failures and Missing Models & Features lead, at 9 of 9 and 8 of 8.
| Raised as a concern | Gemini Enterprise Agent Platform | Microsoft Foundry |
|---|---|---|
| Quotas & 429 Errors | 10 of 11 | Not a theme in its sources |
| Naming & Product Sprawl | 6 of 7 | Not a theme in its sources |
| Setup & Region Configuration | 5 of 5 | Not a theme in its sources |
| Function Calling Failures | 5 of 5 | Not a theme in its sources |
| Latency | 5 of 6 | Not a theme in its sources |
| Surprise Bills & Billing Support | 4 of 5 | Not a theme in its sources |
| Agent Service & Tool Failures | Not a theme in its sources | 9 of 9 |
| Missing Models & Features | Not a theme in its sources | 8 of 8 |
| Reliability & Latency | Not a theme in its sources | 7 of 7 |
| Portal, Naming & Setup | Not a theme in its sources | 6 of 7 |
| Quotas, Capacity & Cost | Not a theme in its sources | 5 of 5 |
| Data Terms & Model Governance | Not a theme in its sources | 3 of 6 |
25 sources
- Google Cloud blog: Introducing Gemini Enterprise Agent Platform (Apr 22, 2026)
- Google Cloud: Agent Platform generative AI pricing
- Agent Platform documentation: Standard PayGo
- Agent Platform documentation: Provisioned Throughput
- Agent Platform documentation: Deployment and endpoint locations
- Agent Platform documentation: Agent Platform and zero data retention
- Agent Platform documentation: Security controls
- Google Cloud: Agent Platform audit logging
- Microsoft Learn: What is Microsoft Foundry?
- Microsoft Learn: Deployment types for Microsoft Foundry Models
- Microsoft Learn: Foundry Models sold directly by Azure
- Microsoft Learn: Data, privacy, and security for Foundry Models
- Microsoft Learn: Foundry Models quotas and limits
- Microsoft Learn: Manage traffic with spillover for provisioned deployments
- Azure retail prices: gpt-oss-120b meters, East US 2
- Azure retail prices: Llama 4 Maverick meters, East US 2
- Requesty: Operational metrics per provider, April 2026 (May 9, 2026)
- Fin AI Research: Running a reliable service over unreliable parts (Aug 8, 2025)
- Engineering at Slack: Slack AI, the path to multi-cloud (May 28, 2026)
- Zalando Engineering: Agentic engineering at Zalando, a snapshot (Aug 14, 2026)
- Grab Engineering: LLM-powered data classification for data entities at scale (Jul 15, 2024)
- Rajesh Beri: Bedrock vs Vertex AI vs Microsoft Foundry, commit drawdown in 2026 (Oct 25, 2026)
- r/googlecloud: Vertex Gemini has zero capacity outside of the US (Oct 21, 2026)
- OpenRouter: Claude Opus 5.5 endpoints, including Vertex and Azure (Oct 28, 2026)
- Claude API docs: Fast mode, where Opus 5.5 fast mode runs (as of Oct 28, 2026)