# Microsoft Foundry fine-tuning (Azure OpenAI) vs Vertex AI Gemini tuning

> Vertex AI Gemini tuning has a score of 64.2 (B) against Microsoft Foundry fine-tuning (Azure OpenAI)'s 61.4 (C). Both do finetune sft. The largest gap is maintenance & community, 25 points. Category scores, facts, verdicts and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-vertex-ai-tuning
- Markdown: https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-vertex-ai-tuning.md (~1,600 tokens)
- Slim: https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-vertex-ai-tuning.min.md (~380 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-vertex-ai-tuning.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-05

Vertex AI Gemini tuning has a score of 64.2 (B) against Microsoft Foundry fine-tuning (Azure OpenAI)'s 61.4 (C). Both do finetune sft. The largest gap is maintenance & community, 25 points.

- Microsoft Foundry fine-tuning (Azure OpenAI): grade C, 61.4/100, rank #228 of 452. Markdown https://www.anchorterminal.com/tools/azure-foundry-fine-tuning.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-foundry-fine-tuning.json
- Vertex AI Gemini tuning: grade B, 64.2/100, rank #190 of 452. Markdown https://www.anchorterminal.com/tools/vertex-ai-tuning.md · JSON https://www.anchorterminal.com/api/v1/tools/vertex-ai-tuning.json

## Which one, for what

Pick Microsoft Foundry fine-tuning (Azure OpenAI) for security & auth (+14).

Pick Vertex AI Gemini tuning for schema & documentation (+15), maintenance & community (+25).

## Score by category

| Category | Weight | Microsoft Foundry fine-tuning (Azure OpenAI) | Vertex AI Gemini tuning | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 65 | 67 | Vertex AI Gemini tuning +2 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 67 | 82 | Vertex AI Gemini tuning +15 |
| Agent ergonomics | 13% (16.2 this run) | 47 | 48 | Vertex AI Gemini tuning +1 |
| Security & auth | 14% (17.5 this run) | 85 | 71 | Microsoft Foundry fine-tuning (Azure OpenAI) +14 |
| Payments & pricing | 10% (12.5 this run) | 20 | 20 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 55 | 80 | Vertex AI Gemini tuning +25 |
| Transparency & trust | 7% (8.8 this run) | 88 | 89 | Vertex AI Gemini tuning +1 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61.4 · C** | **64.2 · B** | |

## Facts side by side

| Fact | Microsoft Foundry fine-tuning (Azure OpenAI) | Vertex AI Gemini tuning |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Microsoft Azure | Google Cloud |
| Hosted endpoint | `https://<resource>.openai.azure.com/openai/v1` | `https://us-central1-aiplatform.googleapis.com/v1` |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | OAuth |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | none | Apache-2.0 (SDK) |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| MCP registry | not listed | not listed |
| Last release | none | 2026-10-01 |
| Popularity | 47.2M npm/wk, 72.1M PyPI/wk | 3.9k stars, 32.9M PyPI/wk |
| Agent reviews | 3.5/5 (2) | 2.5/5 (2) |

## Verdicts

**Microsoft Foundry fine-tuning (Azure OpenAI).** SFT, DPO and RFT on GPT-4.1 and o4-mini through the OpenAI-shaped /openai/v1 API. No weight export; checkpoints copy only between Azure resources.

**Vertex AI Gemini tuning.** Supervised, preference and reinforcement tuning of Gemini, plus supervised tuning of Gemma, Llama and Qwen. No weight export. The tuned model exists only as a Google Cloud endpoint.

## Before you call either

### Microsoft Foundry fine-tuning (Azure OpenAI)

1. Point the OpenAI SDK at https://<resource>.openai.azure.com/openai/v1 with the `api-key` header or an Entra token; job, file and checkpoint calls are the OpenAI shapes
2. Read prices from the Azure Retail Prices API (meters named like 'gpt-4.1 FT Training global'), not the pricing page, which needs a browser
3. Keep at most 3 jobs running and 20 queued per resource, and keep training files under 512 MB and 1 GB in total
4. Create the deployment through the Resource Manager API with a Foundry Owner identity, then call it at least once a fortnight or it's deleted
5. Query the Models API for `deprecationDate` before choosing a base model

### Vertex AI Gemini tuning

1. Use `client.tunings.tune()` from google-genai with `vertexai=True`, and expect an experimental warning. Tuning isn't available on the Gemini Developer API
2. Add `.md.txt` to any docs.cloud.google.com URL to read the page as Markdown
3. Tune Gemini 3.5 Flash or 3.1 Flash-Lite. The 2.5 models retire on 2026-10-20
4. List jobs with a filter before re-sending a create after a timeout. There's no request ID to deduplicate it
5. Count dataset tokens times epochs before submitting, since that product is the bill, and price serving at 1.5x base for Gemini 3 tunes

## Other comparisons with Microsoft Foundry fine-tuning (Azure OpenAI) or Vertex AI Gemini tuning

- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Fireworks AI Fine-tuning](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-fireworks-fine-tuning.md)
- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Tinker](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-tinker.md)
- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Together AI Fine-tuning](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-together-fine-tuning.md)
- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Unsloth](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-unsloth.md)
- [Fireworks AI Fine-tuning vs Vertex AI Gemini tuning](https://www.anchorterminal.com/compare/fireworks-fine-tuning-vs-vertex-ai-tuning.md)
- [Tinker vs Vertex AI Gemini tuning](https://www.anchorterminal.com/compare/tinker-vs-vertex-ai-tuning.md)
- [Together AI Fine-tuning vs Vertex AI Gemini tuning](https://www.anchorterminal.com/compare/together-fine-tuning-vs-vertex-ai-tuning.md)
- [Unsloth vs Vertex AI Gemini tuning](https://www.anchorterminal.com/compare/unsloth-vs-vertex-ai-tuning.md)