# ScaleDown vs SPEV

> SPEV scores 51.1 (D) to ScaleDown's 48.6 (D) for decision models. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev
- Markdown: https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev.md (~2,600 tokens)
- Slim: https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev.min.md (~680 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/scaledown-vs-sprag-spev.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
- Licence: CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.
- Updated: 2026-10-15

SPEV scores 51.1 (D) on agent readiness against ScaleDown's 48.6 (D), and leads in 2 of 7 scored categories. ScaleDown leads on security & auth, payments & pricing and maintenance & community. Both do decision models.

- ScaleDown: grade D, 48.6/100, rank #880 of 1094. Markdown https://www.anchorterminal.com/tools/scaledown.md · JSON https://www.anchorterminal.com/api/v1/tools/scaledown.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
- Best document parsing, OCR and extraction APIs for AI agents: https://www.anchorterminal.com/best/document-extraction/index.md
- All 125 documents comparisons: https://www.anchorterminal.com/compare/document-extraction/index.md

## Which one, for what

### ScaleDown (D)

Good for: Cheap, high-volume labelling, routing and yes or no checks where a probability is more useful than prose, and for pulling described fields with offsets from text, images or PDFs.

Ahead on:
- Security & auth, 48 against 33
- Payments & pricing, 40 against 30
- Maintenance & community, 56 against 49

Also in its favour:
- Free to start without a card

Watch for: No status page, no published rate limits and no SLA outside enterprise contracts

### 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 20
- Schema & documentation, 81 against 69

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


## Score by category

| Category | Weight | ScaleDown | SPEV | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 20 | 45 | SPEV +25 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 69 | 81 | SPEV +12 |
| Agent ergonomics | 13% (16.2 this run) | 76 | 76 | even |
| Security & auth | 14% (17.5 this run) | 48 | 33 | ScaleDown +15 |
| Payments & pricing | 10% (12.5 this run) | 40 | 30 | ScaleDown +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 56 | 49 | ScaleDown +7 |
| Transparency & trust | 7% (8.8 this run) | 54 | 54 | even |
| Negative events | ≤15 | -2 | -2 | |
| **Total** | | **48.6 · D** | **51.1 · D** | |

## Facts side by side

| Fact | ScaleDown | SPEV |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Carbon ScaleDown, Inc. | Sprag |
| Hosted endpoint | `https://api.scaledown.xyz` | `https://api.sprag.ai/v1/decisions` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| x402 | no | no |
| Licence | Proprietary hosted models under ScaleDown's Terms of Service. The langchain-scaledown integration is MIT | 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 | yes | yes |
| Last release | 2026-10-14 | 2026-10-14 |
| Terms last updated | couldn't be read | 2026-09-01 |
| Privacy policy last updated | couldn't be read | 2026-08-01 |
| Customer content may train models | couldn't be read | yes, with an opt-out |
| Terms restrict automated access | couldn't be read | not found in the text |
| Terms restrict benchmarking | couldn't be read | not found in the text |
| Terms or service can change without notice | couldn't be read | not found in the text |
| Arbitration or class-action waiver | couldn't be read | not found in the text |
| Popularity | 0 stars | none |

## Verdicts

**ScaleDown.** Classify answers Jev-shaped `choice`, `noul` and `score` questions with probabilities, and Extract returns values with confidences and character offsets, at $0.05 per million input tokens with output free. There is no status page, no published rate limit and no public changelog, and the site's compliance claims contradict each other.

**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

### ScaleDown

1. Send several questions about one item in one `/v1/scaledown` call. Each becomes its own Classify call and the usage is summed
2. Pin `classify-1`, `extract-1` or `summarize-1` once you've tuned thresholds on your own labelled cases
3. Set `context_chars` to 0 and use `top_n` on Extract unless you need the 500 characters of context each side
4. Set `reasoning: false` on /classify when you only need the label. The reasoning call bills its input at 2x
5. Back off and retry on 429, 502 and 504. No limits are published and calls have no side effects

### 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, ScaleDown or SPEV?

SPEV scores 51.1 (D) on agent readiness against ScaleDown's 48.6 (D), and leads in 2 of 7 scored categories. ScaleDown leads on security & auth, payments & pricing and maintenance & community.

### Do ScaleDown and SPEV need an API key?

Both need an API key.

### Can an agent call ScaleDown and SPEV without installing anything?

Yes. ScaleDown has a hosted endpoint at https://api.scaledown.xyz and SPEV at https://api.sprag.ai/v1/decisions.


## For agents

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

## Other comparisons with ScaleDown or SPEV

- [Celeris-1 Decision vs ScaleDown](https://www.anchorterminal.com/compare/celeris-1-decision-vs-scaledown.md)
- [Celeris-1 Decision vs SPEV](https://www.anchorterminal.com/compare/celeris-1-decision-vs-sprag-spev.md)
- [Clef vs ScaleDown](https://www.anchorterminal.com/compare/cloudflare-clef-vs-scaledown.md)
- [Clef vs SPEV](https://www.anchorterminal.com/compare/cloudflare-clef-vs-sprag-spev.md)
- [Laya vs ScaleDown](https://www.anchorterminal.com/compare/convai-laya-vs-scaledown.md)
- [Laya vs SPEV](https://www.anchorterminal.com/compare/convai-laya-vs-sprag-spev.md)
- [Decider vs ScaleDown](https://www.anchorterminal.com/compare/decider-vs-scaledown.md)
- [Decider vs SPEV](https://www.anchorterminal.com/compare/decider-vs-sprag-spev.md)
- [Decision 3.0 vs ScaleDown](https://www.anchorterminal.com/compare/decision-3-vs-scaledown.md)
- [Decision 3.0 vs SPEV](https://www.anchorterminal.com/compare/decision-3-vs-sprag-spev.md)
- [GLiClass vs ScaleDown](https://www.anchorterminal.com/compare/gliclass-vs-scaledown.md)
- [GLiClass vs SPEV](https://www.anchorterminal.com/compare/gliclass-vs-sprag-spev.md)
- [Kev vs ScaleDown](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-scaledown.md)
- [Kev vs SPEV](https://www.anchorterminal.com/compare/jaredpalmer-kev-vs-sprag-spev.md)
- [Liquid d1 vs ScaleDown](https://www.anchorterminal.com/compare/liquid-d1-vs-scaledown.md)
- [Liquid d1 vs SPEV](https://www.anchorterminal.com/compare/liquid-d1-vs-sprag-spev.md)
- [Microsoft-Decision-1 vs ScaleDown](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-scaledown.md)
- [Microsoft-Decision-1 vs SPEV](https://www.anchorterminal.com/compare/microsoft-decision-1-vs-sprag-spev.md)
- [Drex 1.5 vs ScaleDown](https://www.anchorterminal.com/compare/nace-drex-vs-scaledown.md)
- [Drex 1.5 vs SPEV](https://www.anchorterminal.com/compare/nace-drex-vs-sprag-spev.md)
- [OpenAI Decisions API vs ScaleDown](https://www.anchorterminal.com/compare/openai-decisions-api-vs-scaledown.md)
- [OpenAI Decisions API vs SPEV](https://www.anchorterminal.com/compare/openai-decisions-api-vs-sprag-spev.md)
- [pplx-decider vs ScaleDown](https://www.anchorterminal.com/compare/pplx-decider-vs-scaledown.md)
- [pplx-decider vs SPEV](https://www.anchorterminal.com/compare/pplx-decider-vs-sprag-spev.md)
- [ScaleDown vs Strands Decider 2B](https://www.anchorterminal.com/compare/scaledown-vs-strands-decider.md)
- [ScaleDown vs Jev](https://www.anchorterminal.com/compare/scaledown-vs-typesafe-jev.md)
- [ScaleDown vs Vela 2.0](https://www.anchorterminal.com/compare/scaledown-vs-vela.md)
- [SPEV vs Strands Decider 2B](https://www.anchorterminal.com/compare/sprag-spev-vs-strands-decider.md)
- [SPEV vs Jev](https://www.anchorterminal.com/compare/sprag-spev-vs-typesafe-jev.md)
- [SPEV vs Vela 2.0](https://www.anchorterminal.com/compare/sprag-spev-vs-vela.md)