Head to head · Open-weight models you run yourself · October 2026 research run
Ling-3.1-flash-1019 vs SenseNova-Loop-9B-Preview
Ling-3.1-flash-1019 scores 54.8 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 2 of 4 scored categories. SenseNova-Loop-9B-Preview leads on risk. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons
Which one, for what
Best for Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding
Ahead on
- Reach, 60 against 40
- Documentation and upkeep, 56 against 44
Watch for
574 GB in FP8 with no smaller build from inclusionAI, so no single machine under 690 GB of GPU memory runs it
Best for Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today
Ahead on
- Risk, 50 against 45
Watch for
No released runtime runs it. vLLM and SGLang need unmerged pull requests
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Reach Ling-3.1-flash-1019 +20
Ling-3.1-flash-1019 60
Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build. Runtimes 25, Released model code in Transformers 5.22.2 (bailing_hybrid), vLLM 0.33.0 (BailingMoeV3ForCausalLM, with ling3 tool and reasoning parsers), SGLang 0.5.23 (bailing_moe_v3.py, its bailing_hybrid config and MTP module) and llama.cpp b12242 (bailingmoe3), and Ollama, credited through its pinned llama.cpp as on the Ling-3.0-tiny listing: v0.40.16 sets LLAMA_CPP_VERSION to b12177. Builds 10, the release is FP8, the one quantised precision inclusionAI publishes for it. Terms 15, MIT in the card's metadata, with no use policy or other terms added on the card or in the repository. Download 10, the Hub API's model info gives gated false on 10 November 2026, so the files download with no account and no terms to accept. Hosted 0, the Hub API's provider mapping is empty for this repository on 10 November 2026. 0 + 25 + 10 + 15 + 10 + 0 = 60.
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.
Documentation and upkeep Ling-3.1-flash-1019 +12
Ling-3.1-flash-1019 56
Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claimed) are on the card. Training data 15, the training-content summary the card links names the source categories (Common Crawl and other public datasets, commercially licensed data, the Ant Spider crawler, synthetic data), the size band (over 10 trillion text tokens), data collected up to about July 2026 and the filtering, without listing datasets with sizes. Last change 20, the newest commit, on 4 November 2026, edited the card, six days before this check, and the files went up on 27 October. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (both opened on 27 October 2026) has a reply from an inclusionAI member. Version policy 5, the update went into a repository of its own and Ling-3.1-flash and Ling 3.0 stay in theirs. File health 5, the card states a 1M-token context while config.json gives 262,144 with no rope scaling, and its serve commands name the earlier repository as the model path. 11 + 15 + 20 + 0 + 5 + 5 = 56.
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.
Risk SenseNova-Loop-9B-Preview +5
Ling-3.1-flash-1019 45
File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the repository's configuration_bailing_moe_v3.py, since vLLM 0.33.0 registers no bailing_hybrid config of its own. Provenance 15, files in the inclusionAI organisation that inclusion-ai.org links to, per the Ling-3.0-tiny listing (10). Safety evaluation 0, no safety results for the model on its card or in the training-content summary. Agent guidance 0, the card has nothing on prompt injection, refusals or safeguards, and inclusionAI publishes no guardrail probe for this model as it did for Ling 3.0. Licence risk 15, MIT with no use policy, no field-of-use limits, no threshold and no clause letting inclusionAI change or revoke it. Security programme 0, www.inclusion-ai.org answers 404 for security.txt on 10 November 2026, and the Ling-3.0-tiny listing found no SECURITY.md or disclosure policy in the inclusionAI .github repository. 15 + 15 + 0 + 0 + 15 + 0 = 45.
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.
Score by category
| Category | Weight this run | Ling-3.1-flash-1019 | SenseNova-Loop-9B-Preview | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 60 | 40 | Ling-3.1-flash-1019 +20 |
| Risk | 20%20 | 45 | 50 | SenseNova-Loop-9B-Preview +5 |
| Agent interface | 10%10 | 60 | 60 | even |
| Documentation and upkeep | 10%10 | 56 | 44 | Ling-3.1-flash-1019 +12 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 54.8/100 | D 46.8/100 |
Facts side by side
| Fact | Ling-3.1-flash-1019 | SenseNova-Loop-9B-Preview |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | inclusionAI (Ant Group) | SenseTime (SenseNova) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-04 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| Privacy policy last updated | no document linked | no document linked |
Verdicts
Ling-3.1-flash-1019
inclusionAI's newest flagship, a 560B hybrid mixture of experts under plain MIT that vLLM, SGLang, Transformers and llama.cpp run in released versions. It ships only as 574 GB of FP8, so it needs a multi-GPU server. The card overstates the context, documents little about tool calls, and has no safety results.
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.
Before you call either
Ling-3.1-flash-1019
- Serve it with SGLang 0.5.23 or later on 8 H200 or 4 GB300 GPUs, per the card, and use this repository's name as the model path, not the earlier one the card's command shows
- With vLLM pass
--trust-remote-code,--tool-call-parser ling3and--reasoning-parser ling3 - Set
chat_template_kwargsenable_thinkingfalse for direct answers. Reasoning comes back inreasoning_contentper SGLang's cookbook - Plan on 262,144 tokens of context. The 1M figure needs the YaRN override in SGLang's cookbook
- Use temperature 1.0, top_p 0.95 and top_k 20, per the card
- Validate JSON output yourself, since structured output isn't documented
SenseNova-Loop-9B-Preview
- Read modeling_sensenova_loop.py before you load it. trust_remote_code runs it
- Pin transformers 5.18.0, the version the card checked
- Load with dtype=torch.bfloat16 as the card does, or the 38 GB of F32 weights stay at full size
- Pass enable_thinking=False to apply_chat_template for a direct answer
- Tool calls come back as tool_call blocks with function and parameter tags. Parse them yourself, since no runtime ships a parser
- Wait for the vLLM or SGLang pull request to land in a release before putting it behind an API
Questions
Which is better for AI agents, Ling-3.1-flash-1019 or SenseNova-Loop-9B-Preview?
Ling-3.1-flash-1019 scores 54.8 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 2 of 4 scored categories. SenseNova-Loop-9B-Preview leads on risk.
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Machine-readable
- This page as Markdown
/compare/ling-3-1-flash-1019-vs-sensenova-loop-9b-preview.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/ling-3-1-flash-1019.json·/api/v1/tools/sensenova-loop-9b-preview.json - From a terminal
anchor compare ling-3-1-flash-1019 sensenova-loop-9b-preview(the CLI) - Over MCP
compare_tools {"a": "ling-3-1-flash-1019", "b": "sensenova-loop-9b-preview"}at/mcp, no key