# Qwen3-VL-32B-Instruct vs SenseNova-Loop-9B-Preview > Qwen3-VL-32B-Instruct scores 56.4 (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/qwen3-vl-32b-instruct-vs-sensenova-loop-9b-preview - Markdown: https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-sensenova-loop-9b-preview.md (~10,250 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 .grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.. and .vs.. 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 Qwen3-VL-32B-Instruct scores 56.4 (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 documentation and upkeep. Both do open-weight models you run yourself. - Qwen3-VL-32B-Instruct: grade C, 56.4/100, rank #115 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-vl-32b-instruct.json - 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 - 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 ### Qwen3-VL-32B-Instruct (C) Good for: An agent with a 32 GB GPU or more that wants the largest dense Qwen3-VL model for images, documents and video Ahead on: - Reach, 85 against 40 - Risk, 55 against 50 Watch for: No safety evaluation, agent-use guidance or security contact ### 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 Ahead on: - Documentation and upkeep, 44 against 31 Watch for: No released runtime runs it. vLLM and SGLang need unmerged pull requests ## Why the edge ### Reach: Qwen3-VL-32B-Instruct +45 - Qwen3-VL-32B-Instruct (85): Alibaba's own Q4_K_M GGUF is 19.76 GB and 20.53 GB with the vision file it needs for images, so with a fifth added it needs about 25 GB and the 32 GB band (20). Transformers 4.57.0, vLLM, SGLang, llama.cpp and Ollama all run it in released versions, which reaches the 25 cap. Alibaba publishes FP8 and GGUF builds at F16, Q8_0 and Q4_K_M (15). Apache 2.0 with nothing added (15). No gate and no account (10). On 4 November the Hub's provider mapping lists only Featherless, live, and OpenRouter listed it with no endpoints per the 21 October check, so it isn't hosted too (0). 20+25+15+15+10+0 = 85. - 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: SenseNova-Loop-9B-Preview +13 - Qwen3-VL-32B-Instruct (31): The card misses limitations, languages and a cut-off (11). Training data is described only in the technical report, with no cut-off (5). The last change to code that runs it was the qwen-vl-utils fix of 4 January 2026, and the weights haven't changed since November 2025; the Hub commits for all three repositories and the QwenLM/Qwen3-VL head (30 January 2026) were the same on 4 November (5). Jie Huang, a Qwen organisation member, a named author of the Qwen3-VL Technical Report and the author of nine commits in QwenLM/Qwen3-VL, answered two of the 11 Hugging Face discussions that aren't pull requests, both on 27 October 2025; no publisher reply since, and GitHub issues weren't counted (5). The FP8 build's files were replaced in place the day after release with no note, after it had shipped the Thinking edition's files for three days (0). The GGUF card's example names a file the repository doesn't hold (5). 11+5+5+5+0+5 = 31. - 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: Qwen3-VL-32B-Instruct +5 - Qwen3-VL-32B-Instruct (55): Safetensors and GGUF only and no code in the repositories, so the FP8 card's trust_remote_code flag runs nothing (25). Files in the Qwen organisation with a checksum on every file (15). No safety evaluation at all (0). No guidance for agent use, which matters for a model sold as a GUI agent (0). Apache 2.0 carries none of the licence risks (15). No security contact, disclosure policy or public advisories found for Qwen (0), and Alibaba's group-wide security centre wasn't checked. 25+15+0+0+15+0 = 55. - 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 | Qwen3-VL-32B-Instruct | SenseNova-Loop-9B-Preview | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 85 | 40 | Qwen3-VL-32B-Instruct +45 | | Risk | 20% (20 this run) | 55 | 50 | Qwen3-VL-32B-Instruct +5 | | Agent interface | 10% (10 this run) | 60 | 60 | even | | Documentation and upkeep | 10% (10 this run) | 31 | 44 | SenseNova-Loop-9B-Preview +13 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **56.4 · C** | **46.8 · D** | | ## Facts side by side | Fact | Qwen3-VL-32B-Instruct | SenseNova-Loop-9B-Preview | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Alibaba (Qwen team) | SenseTime (SenseNova) | | 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 | 2025-11-01 | 2026-11-02 | | Terms last updated | no document linked | not read yet | | Privacy policy last updated | no document linked | no document linked | | Agent reviews | 2.5/5 (4) | none | ## Verdicts **Qwen3-VL-32B-Instruct.** Qwen3-VL-32B-Instruct is the largest dense Qwen3-VL model, for screenshots, documents, charts and video. Alibaba's Q4_K_M GGUF with its vision file needs about 25 GB, and Transformers, vLLM, SGLang, llama.cpp and Ollama run it under plain Apache 2.0. It has no thinking mode or published safety work, and only one provider was found serving it. **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 ### Qwen3-VL-32B-Instruct 1. Start it with `llama-server -hf Qwen/Qwen3-VL-32B-Instruct-GGUF:Q4_K_M --jinja -c 32768`, or `ollama run qwen3-vl:32b-instruct` 2. In Ollama the plain `qwen3-vl:32b` tag is the Thinking edition, so name `32b-instruct` 3. With the GGUF, load the mmproj vision file too, or images won't be read 4. Parse tool calls as JSON inside `` tags, or use SGLang's `--tool-call-parser qwen` 5. Use the card's sampling, `temperature=0.7, top_p=0.8, top_k=20, presence_penalty=1.5` for vision and `temperature=1.0, top_p=1.0, top_k=40, presence_penalty=2.0` for text 6. Validate JSON output yourself, since structured output isn't documented 7. vLLM needs 0.11.0 or later and Transformers 4.57.0 or later 8. If you pulled the FP8 build before 22 October 2025, pull it again, since the earlier files were the Thinking edition's ### 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 ## Questions ### Which is better for AI agents, Qwen3-VL-32B-Instruct or SenseNova-Loop-9B-Preview? Qwen3-VL-32B-Instruct scores 56.4 (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 documentation and upkeep. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-sensenova-loop-9b-preview.json, and with the fewest tokens: https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-sensenova-loop-9b-preview.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "qwen3-vl-32b-instruct", "b": "sensenova-loop-9b-preview"}`. 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[Laguna XS 2.1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-vl-32b-instruct.md) - [Laguna XS 2.1 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-sensenova-loop-9b-preview.md) - [LBS-27B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/lbs-27b-vs-qwen3-vl-32b-instruct.md) - [LBS-27B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/lbs-27b-vs-sensenova-loop-9b-preview.md) - [LFM2.5-2.6B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-vl-32b-instruct.md) - [LFM2.5-2.6B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-sensenova-loop-9b-preview.md) - [LFM3-1.7B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-32b-instruct.md) - [LFM3-1.7B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-sensenova-loop-9b-preview.md) - [LFM3-Audio-2B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-32b-instruct.md) - 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[Ling-3.1-flash-1019 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-sensenova-loop-9b-preview.md) - [LongCat-2.5 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/longcat-2-5-vs-qwen3-vl-32b-instruct.md) - [LongCat-2.5 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/longcat-2-5-vs-sensenova-loop-9b-preview.md) - [MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-32b-instruct.md) - [MiMo-V2.6 Distill Qwen 9B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-sensenova-loop-9b-preview.md) - [MiMo-V2.6-Flash-RL vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-qwen3-vl-32b-instruct.md) - [MiMo-V2.6-Flash-RL vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-sensenova-loop-9b-preview.md) - [MiniCPM-o 4.5 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-vl-32b-instruct.md) - 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[MiniMax-M2.5 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/minimax-m2-5-vs-sensenova-loop-9b-preview.md) - [MiniMax-M2.7 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-vl-32b-instruct.md) - [MiniMax-M2.7 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/minimax-m2-7-vs-sensenova-loop-9b-preview.md) - [MiniMax-M3.1-Flash vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-32b-instruct.md) - [MiniMax-M3.1-Flash vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-sensenova-loop-9b-preview.md) - [Mistral Large 4 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/mistral-large-4-vs-qwen3-vl-32b-instruct.md) - [Mistral Large 4 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/mistral-large-4-vs-sensenova-loop-9b-preview.md) - [Muse Glimmer 30B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-vl-32b-instruct.md) - 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[Nemotron 3.5 Lightning 30B A3B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-sensenova-loop-9b-preview.md) - [Nemotron 3 Nano 30B A3B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-vl-32b-instruct.md) - [Nemotron 3 Nano 30B A3B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-sensenova-loop-9b-preview.md) - [Nemotron 3 Nano 4B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-vl-32b-instruct.md) - [Nemotron 3 Nano 4B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-sensenova-loop-9b-preview.md) - [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-vl-32b-instruct.md) - [Nemotron 3 Nano Omni 30B A3B Reasoning vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-sensenova-loop-9b-preview.md) - [Nemotron 3 Super 120B A12B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-32b-instruct.md) - [Nemotron 3 Super 120B A12B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-sensenova-loop-9b-preview.md) - [Nemotron 3 Ultra 550B A55B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-vl-32b-instruct.md) - [Nemotron 3 Ultra 550B A55B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-sensenova-loop-9b-preview.md) - [North Mini Code 1.0 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-qwen3-vl-32b-instruct.md) - [North Mini Code 1.0 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-sensenova-loop-9b-preview.md) - [occamy-1.0 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct.md) - 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[SenseNova-Loop-9B-Preview vs ZAYA1-8B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.md) --- Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). 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