# Microsoft-Decision-1 vs SPEV

> SPEV scores 51.1 (D) to Microsoft-Decision-1's 38.8 (E) for decision models. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev
- Markdown: https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.md (~2,750 tokens)
- Slim: https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.min.md (~730 tokens, same facts, less prose, for token-sensitive contexts)
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- 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
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- Updated: 2026-10-15

SPEV scores 51.1 (D) on agent readiness against Microsoft-Decision-1's 38.8 (E), and leads in 6 of 7 scored categories. Microsoft-Decision-1 leads on security & auth. Both do decision models.

- Microsoft-Decision-1: grade E, 38.8/100, rank #1008 of 1094. Markdown https://www.anchorterminal.com/tools/microsoft-decision-1.md · JSON https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json
- SPEV: grade D, 51.1/100, rank #819 of 1094. Markdown https://www.anchorterminal.com/tools/sprag-spev.md · JSON https://www.anchorterminal.com/api/v1/tools/sprag-spev.json
- Best decision models for AI agents: https://www.anchorterminal.com/best/decision-models/index.md
- All 136 decisions comparisons: https://www.anchorterminal.com/compare/decision-models/index.md

## Which one, for what

### Microsoft-Decision-1 (E)

Good for: Routing, classification, prioritisation and rubric checks over text, where a fixed set of options and a low price per token matter more than generated text.

Ahead on:
- Security & auth, 52 against 33

Watch for: Public preview only. Microsoft's post gives no general availability date and states no licence for the hosted model

### SPEV (D)

Good for: Typed decisions over raw audio, such as end-of-turn detection, call triage and flagging, plus text and single images, hosted or self-hosted.

Ahead on:
- Reliability, 45 against 30
- Schema & documentation, 81 against 43
- Agent ergonomics, 76 against 50
- Payments & pricing, 30 against 20
- Maintenance & community, 49 against 40
- Transparency & trust, 54 against 29

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: Published on 14 October 2026, with no service record, no status page and no API changelog


## Score by category

| Category | Weight | Microsoft-Decision-1 | SPEV | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 30 | 45 | SPEV +15 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 43 | 81 | SPEV +38 |
| Agent ergonomics | 13% (16.2 this run) | 50 | 76 | SPEV +26 |
| Security & auth | 14% (17.5 this run) | 52 | 33 | Microsoft-Decision-1 +19 |
| Payments & pricing | 10% (12.5 this run) | 20 | 30 | SPEV +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 40 | 49 | SPEV +9 |
| Transparency & trust | 7% (8.8 this run) | 29 | 54 | SPEV +25 |
| Negative events | ≤15 | 0 | -2 | |
| **Total** | | **38.8 · E** | **51.1 · D** | |

## Facts side by side

| Fact | Microsoft-Decision-1 | SPEV |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Microsoft | Sprag |
| Hosted endpoint | no (local only) | `https://api.sprag.ai/v1/decisions` |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | API key |
| Pricing | Pay per use | Pay per use |
| Price for decision models | free | not published |
| x402 | no | no |
| Licence | Not stated. The announcement and OpenRouter's model page name no licence, and no weights repository was found. | Apache-2.0 (weights and inference code, following the Qwen3-Omni base). Training code and data aren't published |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| Last release | 2026-10-09 | 2026-10-14 |
| Terms last updated | no document linked | 2026-09-01 |
| Privacy policy last updated | no date given | 2026-08-01 |
| Customer content may train models |  | yes, with an opt-out |
| Terms restrict automated access |  | not found in the text |
| Terms restrict benchmarking |  | not found in the text |
| Terms or service can change without notice |  | not found in the text |
| Arbitration or class-action waiver |  | not found in the text |

## Verdicts

**Microsoft-Decision-1.** Microsoft publishes $0.042 per million input tokens, with output free, and the model is callable through Microsoft Foundry and OpenRouter. It is in public preview. No licence, model-specific retention statement, rate limit or deprecation policy was found, and the Foundry route needs an Azure deployment and an Entra token. Latency and accuracy figures are Microsoft's claims.

**SPEV.** SPEV answers typed questions over text, audio or an image in one call, with a public OpenAPI schema and Apache-2.0 weights on Hugging Face. It is a day old, has an 8,192-token context, no status page or changelog, and Sprag's terms let it train on API content unless the customer opts out by email.

## Before you call either

### Microsoft-Decision-1

1. Use OpenRouter's Decisions method, not an OpenAI chat-completions SDK. OpenRouter says chat completions SDKs will not work with this model
2. On Foundry, send the request to the deployment's /providers/microsoft/v1/systemone path with a Microsoft Entra token for https://cognitiveservices.azure.com/.default, not an API key
3. Take the deployment name from the Foundry quickstart before the first call. Microsoft says to confirm the route and authentication header, and the pages reviewed do not give the name
4. Keep each request within OpenRouter's 32,768-token context and send only fixed options, since the model is not intended for open-ended generation
5. Measure latency and calibration on your own labelled cases before relying on Microsoft's latency and 'nine times out of 10' statements

### SPEV

1. Send `model: "spev"` to `POST https://api.sprag.ai/v1/decisions` with a bearer key. `/v1/systemone` returns 410
2. Ask every question about one piece of evidence in one request. Answers come back in question order
3. Send audio as base64 in `input_audio` with `format`, not as a data URL, and at most one image across all messages
4. Keep evidence and questions under 8,192 tokens. Over the limit returns 400 `model_limit_exceeded`
5. Back off on 429 and 503 for `Retry-After` seconds. Limits are 60 requests a minute per organisation by default
6. Handle an answer of type `refusal`, which carries no probabilities

## Questions

### Which is better for AI agents, Microsoft-Decision-1 or SPEV?

SPEV scores 51.1 (D) on agent readiness against Microsoft-Decision-1's 38.8 (E), and leads in 6 of 7 scored categories. Microsoft-Decision-1 leads on security & auth.

### Do Microsoft-Decision-1 and SPEV need an API key?

Microsoft-Decision-1 takes an API key or an OAuth sign-in. SPEV needs an API key.

### Can an agent call Microsoft-Decision-1 and SPEV without installing anything?

No hosted endpoint is listed for Microsoft-Decision-1. SPEV has a hosted endpoint at https://api.sprag.ai/v1/decisions.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.json, and with the fewest tokens: https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "microsoft-decision-1", "b": "sprag-spev"}`. From a terminal: `anchor compare microsoft-decision-1 sprag-spev`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/microsoft-decision-1.json and https://www.anchorterminal.com/api/v1/tools/sprag-spev.json

## Other comparisons with Microsoft-Decision-1 or SPEV

- [Celeris-1 Decision vs Microsoft-Decision-1](https://www.anchorterminal.com/compare/celeris-1-decision-vs-microsoft-decision-1.md)
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