# SenseNova-Loop-9B-Preview vs ZAYA1-8B

> ZAYA1-8B scores 61 (C) to SenseNova-Loop-9B-Preview's 46.8 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b
- Markdown: https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.md (~9,350 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-10

ZAYA1-8B scores 61 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- SenseNova-Loop-9B-Preview: grade D, 46.8/100, rank #155 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/sensenova-loop-9b-preview.md · JSON https://www.anchorterminal.com/api/v1/tools/sensenova-loop-9b-preview.json
- ZAYA1-8B: grade C, 61/100, rank #85 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/zaya1-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### SenseNova-Loop-9B-Preview (D)

Good for: Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today

Watch for: No released runtime runs it. vLLM and SGLang need unmerged pull requests

### ZAYA1-8B (C)

Good for: People who want a small, fast reasoning model for maths and code and can live without tool calling

Ahead on:
- Reach, 80 against 40
- Risk, 55 against 50
- Documentation and upkeep, 50 against 44

Watch for: Tool calling needs a parser that only Zyphra's vLLM fork has


## Why the edge

### Reach: ZAYA1-8B +40

- SenseNova-Loop-9B-Preview (40): Memory 15, the only build is the safetensors set, 38.14 GB with its MTP head, since the Hub counts 9.41B of its parameters in F32. Runtimes 0, none of the six runs it in a released version. Builds 0, SenseNova publishes one set of weights and no quantised build. Terms 15, Apache 2.0 in the card's metadata and on the card, which links the LICENSE in the GitHub repository, and nothing added. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API that serves it. 15 + 0 + 0 + 15 + 10 + 0 = 40.
- ZAYA1-8B (80): Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80.

### Documentation and upkeep: ZAYA1-8B +6

- SenseNova-Loop-9B-Preview (44): Model card 14, Intended use, the architecture, the parameter counts, the training context and the languages (in the metadata) are on the card. Training data 5, one general sentence on the recipes, with no sources, sizes or cut-off. Last change 20, the last commit, on 2 November 2026, reworked the speculative decoding section of the card, 8 days before this check. Responsiveness 0, none of the 5 discussions that aren't pull requests (30 October to 9 November 2026) has a reply from a sensenova member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, labelled a preview, with dated news on the card. File health 0, the files contradict the card on precision. 14 + 5 + 20 + 0 + 5 + 0 = 44.
- ZAYA1-8B (50): Model card 5, Intended use and the parameter counts are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the main repository last changed on 26 June 2026 (the checkpoint reshaped for Transformers), 137 days before this check, and the quantised repositories on 2 July, 131 days. Responsiveness 20, Of the 16 most recent discussions that aren't pull requests (7 May to 14 August 2026), 10 have a reply from a Zyphra member, which is most. Version policy 5, the original checkpoint is kept as ZAYA1-8B-legacy and the card says so at the top, without a date. File health 10, Config, template and card agree on the architecture after the reshape. 5 + 0 + 10 + 20 + 5 + 10 = 50.

### Risk: ZAYA1-8B +5

- SenseNova-Loop-9B-Preview (50): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the sensenova organisation, which the GitHub repository for the model links to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on instructions inside tool results or images. Licence risk 15, Apache 2.0 with no use policy, no threshold and no right to change the terms. Security programme 5, SenseTime's about page gives a security contact (5). 15 + 15 + 0 + 0 + 15 + 5 = 50.
- ZAYA1-8B (55): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55.

## Score by category

| Category | Weight | SenseNova-Loop-9B-Preview | ZAYA1-8B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 40 | 80 | ZAYA1-8B +40 |
| Risk | 20% (20 this run) | 50 | 55 | ZAYA1-8B +5 |
| Agent interface | 10% (10 this run) | 60 | 60 | even |
| Documentation and upkeep | 10% (10 this run) | 44 | 50 | ZAYA1-8B +6 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **46.8 · D** | **61 · C** | |

## Facts side by side

| Fact | SenseNova-Loop-9B-Preview | ZAYA1-8B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | SenseTime (SenseNova) | Zyphra |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-02 | 2026-07-02 |
| Terms last updated | not read yet | no document linked |
| Privacy policy last updated | no document linked | no document linked |

## Verdicts

**SenseNova-Loop-9B-Preview.** An unusual architecture under Apache 2.0, with a 256K training context, a thinking switch and tool calling in the template. It's a preview in practice too: no released runtime runs it, loading it runs the repository's code, the files are twice the size the card implies, and nobody from SenseNova has answered a question yet.

**ZAYA1-8B.** A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.

## Before you call either

### SenseNova-Loop-9B-Preview

1. Read modeling_sensenova_loop.py before you load it. trust_remote_code runs it
2. Pin transformers 5.18.0, the version the card checked
3. Load with dtype=torch.bfloat16 as the card does, or the 38 GB of F32 weights stay at full size
4. Pass enable_thinking=False to apply_chat_template for a direct answer
5. Tool calls come back as tool_call blocks with function and parameter tags. Parse them yourself, since no runtime ships a parser
6. Wait for the vLLM or SGLang pull request to land in a release before putting it behind an API

### ZAYA1-8B

1. Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork
2. Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in
3. Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work
4. Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes
5. The quantised repositories have no licence tag. The main one is Apache 2.0

## Questions

### Which is better for AI agents, SenseNova-Loop-9B-Preview or ZAYA1-8B?

ZAYA1-8B scores 61 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 3 of 4 scored categories.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "sensenova-loop-9b-preview", "b": "zaya1-8b"}`. From a terminal: `anchor compare sensenova-loop-9b-preview zaya1-8b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/sensenova-loop-9b-preview.json and https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json

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- [Qwen3.5-397B-A17B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-sensenova-loop-9b-preview.md)
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- [Qwen3.6-27B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-sensenova-loop-9b-preview.md)
- [Qwen3.6-27B vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-6-27b-vs-zaya1-8b.md)
- [Qwen3.6-35B-A3B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-sensenova-loop-9b-preview.md)
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- [Qwen3-Coder-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-sensenova-loop-9b-preview.md)
- [Qwen3-Coder-30B-A3B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-zaya1-8b.md)
- [Qwen3-Coder-Next vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-coder-next-vs-sensenova-loop-9b-preview.md)
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- [Qwen3-Omni-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-sensenova-loop-9b-preview.md)
- [Qwen3-Omni-30B-A3B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-zaya1-8b.md)
- [Qwen3-VL-2B-Instruct vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-sensenova-loop-9b-preview.md)
- [Qwen3-VL-2B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-zaya1-8b.md)
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- [Qwen3-VL-30B-A3B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-zaya1-8b.md)
- [Qwen3-VL-32B-Instruct vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-sensenova-loop-9b-preview.md)
- [Qwen3-VL-32B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-zaya1-8b.md)
- [Qwen3-VL-4B-Instruct vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-sensenova-loop-9b-preview.md)
- [Qwen3-VL-4B-Instruct vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-zaya1-8b.md)
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- [Qwopus3.8-27B-Flash-V2 vs ZAYA1-8B](https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-zaya1-8b.md)
- [Recursive Flint vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/recursive-flint-vs-sensenova-loop-9b-preview.md)
- [Recursive Flint vs ZAYA1-8B](https://www.anchorterminal.com/compare/recursive-flint-vs-zaya1-8b.md)
- [Ripple-65B Preview vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/ripple-65b-preview-vs-sensenova-loop-9b-preview.md)
- [Ripple-65B Preview vs ZAYA1-8B](https://www.anchorterminal.com/compare/ripple-65b-preview-vs-zaya1-8b.md)
- [SenseNova-Loop-9B-Preview vs SmolLM3-3B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-smollm3-3b.md)
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- [SenseNova-Loop-9B-Preview vs Step 3.7 Flash](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash.md)
- [SenseNova-Loop-9B-Preview vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-swift-1-5-qwen3-8-27b.md)
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- [SenseNova-Loop-9B-Preview vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-unlimited-ocr-2.md)
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- [Spark-X2.6-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b.md)
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- [ThinkingCap (Qwen3.8 27B) vs ZAYA1-8B](https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-zaya1-8b.md)
- [Baidu Unlimited-OCR-2 vs ZAYA1-8B](https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-zaya1-8b.md)
- [WeVisOne-VL-2B vs ZAYA1-8B](https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-zaya1-8b.md)
- [WeVisOne-VL-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b.md)

---

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