SenseNova · llm model

SenseNova-Loop-9B-Preview

SenseNova-Loop-9B-Preview is SenseNova's latest language model in our dataset (public preview), released Oct 30, 2026. Open weights (Apache-2.0). SenseNova's 9B open-weights looped-transformer preview that reuses shared-weight layers for extra depth; takes text and images, trained with sequences up to 262,144 tokens; Apache 2.0. Verified against vendor sources on Oct 31, 2026.

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Primary source: https://huggingface.co/sensenova/SenseNova-Loop-9B-Preview. We are the fast, independent index; the vendor’s own page is the source of record for these model facts.

SenseNova-Loop-9B-Preview at a glance: 262,144-token context window; takes text, image in; returns text.

  • ReleasedOct 30, 2026
  • Context window262K262,144 tokens
  • LicenceOpen weightsApache-2.0
InTextImageOutText

Key facts

Vendor-reported facts are read from the linked vendor page on the date shown above; we did not run the model. Independently tested means we ran it; no fact on this page is. Editorial is our own classification, not a vendor claim. Where a linked page does not itself state a value, the row says so. How to read provenance.

SenseNova-Loop-9B-Preview: key facts with sources
FactValueLabelSource
VendorSenseNovaEditorialn/a
ReleasedOct 30, 2026 Last update of the public Hugging Face repository (Oct 30 UTC); the repository was created Oct 28 and no announcement date is stated.Vendor-reportedsource
Statuspublic previewEditorialn/a
Context window262,144 tokens (262K) Maximum training sequence length per the model card.Vendor-reportedsource
Inputtext, imageVendor-reportedsource
OutputtextVendor-reportedsource
Parameters9B total, Looped transformer: 32 distinct decoder layers, layers 4-27 run twice with shared weightsVendor-reportedsource
LicenceApache-2.0 (open weights)Vendor-reportedsource

Where SenseNova-Loop-9B-Preview sits in our data

Alternatives to SenseNova-Loop-9B-Preview

Language models from other vendors that share at least one of our groups with SenseNova-Loop-9B-Preview. Comparable on paper, from each model’s sourced facts; we have not run them.

  • LFM3-1.7BLiquid AI · Both in: Open weights, Runs on your own hardware · 256K context · released Oct 27, 2026
  • Nemotron 3.5 Bolt E4B (4GB)NVIDIA · Both in: Open weights, Runs on your own hardware · 64K context · released Oct 23, 2026
  • Qwen3.8-27BAlibaba · Both in: Open weights, Runs on your own hardware · 262K context · released Aug 14, 2026
  • North Mini CodeCohere · Both in: Open weights, Runs on your own hardware · 256K context · released Jun 9, 2026
  • Qwen3.6-27BAlibaba · Both in: Open weights, Runs on your own hardware · 262K context · released Apr 22, 2026
  • Gemma 4Google · Both in: Open weights, Runs on your own hardware · 256K context · released Mar 31, 2026

Side by side: Best open-weight LLMs: how to choose

What the sources say

These are claims from the linked pages, not our measurements.

  • SenseNova describes a 32-layer multimodal decoder that loops layers 4 to 27 twice with shared weights, for 56 decoder-layer executions per forward pass. Vendor description; we did not run it.

Notes

  • Serving instructions on the card use SGLang.

What we tested

Nothing yet. We have not run SenseNova-Loop-9B-Preview ourselves, so every fact on this page is Reported from the sources below. When we do test it, the scope will be stated here and in our test logs. See methodology.

Not verified, left out

We could not confirm these on a vendor page, so we do not state them.

  • Benchmark scores were not captured.
  • This is a preview release; no API or hosted pricing.

SenseNova-Loop-9B-Preview FAQ

When was SenseNova-Loop-9B-Preview released?

SenseNova released SenseNova-Loop-9B-Preview on Oct 30, 2026; it is listed as public preview. Source.

How large is the SenseNova-Loop-9B-Preview context window?

262,144 tokens. Source.

Is SenseNova-Loop-9B-Preview open weights?

Yes. The weights are published under Apache-2.0. Source.

Has Agentic Weekly tested SenseNova-Loop-9B-Preview?

Not yet. Every fact on this page is Reported: read from the linked vendor pages, not measured by us.

Sources

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