Head to head · Open-weight models you run yourself · October 2026 research run
Qwen3-Coder-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview
Qwen3-Coder-30B-A3B-Instruct scores 55.7 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 3 of 4 scored categories. SenseNova-Loop-9B-Preview leads on documentation and upkeep. 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
Qwen3-Coder-30B-A3B-Instruct C
Best for Coding agents and local coding tools that want an open model on one 24 GB GPU or a 32 GB Mac, with a plain licence.
Ahead on
- Reach, 90 against 40
- Risk, 55 against 50
- Agent interface, 75 against 60
Watch for
No safety results, prompt-injection guidance or security contact, though it's meant to run commands
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
- Documentation and upkeep, 44 against 31
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 Qwen3-Coder-30B-A3B-Instruct +50
Qwen3-Coder-30B-A3B-Instruct 90
Memory 25 of 30, LM Studio's MLX 4-bit build is 17.2 GB and Ollama's 4-bit build 19 GB, 21 to 23 GB with a fifth added, which fits 24 GB. Runtimes 25, released Transformers, vLLM, SGLang and llama.cpp run the qwen3_moe architecture, vLLM and SGLang carry a qwen3_coder parser, Ollama's released build pins a llama.cpp that has qwen3moe, and LM Studio's catalogue carries it. Builds 10 of 15, Alibaba's only quantised build is FP8. Terms 15, Apache 2.0 with nothing added. Download 10, neither repository is gated. Hosted 5, Featherless AI on Hugging Face (live on 4 November 2026) plus SiliconFlow and Amazon Bedrock on OpenRouter (per 21 October, not re-read) serve it. 25 + 25 + 10 + 15 + 10 + 5 = 90.
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.
Agent interface Qwen3-Coder-30B-A3B-Instruct +15
Qwen3-Coder-30B-A3B-Instruct 75
Chat template 20, chat_template.jinja in the repository. Tool-calling format 25, the card shows how tools are declared, the README names the parser for SGLang and vLLM, and the repository ships it. Trained tool calling 20, the template renders several calls a turn and the training used agent reinforcement learning. Structured output 0, not documented. Reasoning control 0, the model has no thinking. Context 10, 262,144 tokens native, with the YaRN extension not counted. Template, parser and config unchanged on 4 November. 20 + 25 + 20 + 0 + 0 + 10 = 75.
SenseNova-Loop-9B-Preview 60
Chat template 20, chat_template.jinja in the repository (7,756 characters). Tool-calling format 10, only the template says it: a tools block, and calls written as tool_call blocks with function and parameter tags. Trained tool calling 10, the card says the training recipes include tool trajectories and that the model is for agentic workflows. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the card documents enable_thinking in the chat template call, on or off per request, and the template puts the reasoning in think tags ahead of the answer. Context 10, 262,144 tokens in training, per the card's specification table, and config.json gives the language model 262,144 positions. 20 + 10 + 10 + 0 + 10 + 10 = 60.
Documentation and upkeep SenseNova-Loop-9B-Preview +13
Qwen3-Coder-30B-A3B-Instruct 31
Model card 11 of 20, intended use, architecture, parameters and context are there, but limitations, languages and a knowledge cut-off aren't. Training data 5, the blog describes the mix in general terms without a cut-off. Last change 5, config.json was corrected on 3 December 2025, 336 days before the 4 November 2026 check. Responsiveness 0, counted by script on 4 November, none of 26 discussions has a reply from Alibaba's Qwen staff, and the one Hub-flagged member who replied is the independent quantiser bartowski. Version policy 5, a first release. File health 5, the files now agree with the card, but reports about the parser and an attention error wait without a reply. 11 + 5 + 5 + 0 + 5 + 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-Coder-30B-A3B-Instruct +5
Qwen3-Coder-30B-A3B-Instruct 55
File safety 25, safetensors weights, and the shipped parser script runs neither to load the model nor to build prompts. Provenance 15, the files are in the Qwen organisation that Qwen's GitHub links to, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 0, nothing on prompt injection, refusals or safeguards, though it's sold for agents that run commands. Licence risk 15, plain Apache 2.0 that hasn't changed. Security programme 0, no security.txt, disclosure policy or security contact for Qwen was found, and Alibaba's group security centre couldn't be checked, so it's scored as absent. Files unchanged on 4 November, and QwenLM/Qwen3-Coder still has no SECURITY.md. 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 this run | Qwen3-Coder-30B-A3B-Instruct | SenseNova-Loop-9B-Preview | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 90 | 40 | Qwen3-Coder-30B-A3B-Instruct +50 |
| Risk | 20%20 | 55 | 50 | Qwen3-Coder-30B-A3B-Instruct +5 |
| Agent interface | 10%10 | 75 | 60 | Qwen3-Coder-30B-A3B-Instruct +15 |
| Documentation and upkeep | 10%10 | 31 | 44 | SenseNova-Loop-9B-Preview +13 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 55.7/100 | D 46.8/100 |
Facts side by side
| Fact | Qwen3-Coder-30B-A3B-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 | 2025-12-03 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 2.8/5 (4) | none |
Verdicts
Qwen3-Coder-30B-A3B-Instruct
A coding model with 3.3B of 30.5B parameters active per token, for agentic coding tools, repository reading and fill-in-the-middle without a thinking step. It needs about 21 to 23 GB at 4 bits under Apache 2.0, and several providers host it. It runs commands for agents with no safety results or prompt-injection guidance, and Alibaba hasn't answered its discussions.
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-Coder-30B-A3B-Instruct
- Quickest start is
ollama run qwen3-coder:30b, 19 GB - On our reference machine use BF16 with
vllm serve Qwen/Qwen3-Coder-30B-A3B-Instruct --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser qwen3_coder, 61 GB of weights fits the GPU share - Use the qwen3_coder parser in vLLM or SGLang, not hermes, since calls come back as function and parameter blocks rather than JSON
- Pass tool-call arguments in the history as objects, the template iterates them as a mapping
- Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and repetition_penalty 1.05, with up to 65,536 output tokens
- For code completion use the fill-in-the-middle tokens
<|fim_prefix|>,<|fim_suffix|>and<|fim_middle|>from Qwen's README - Sandbox the commands and files it touches, since nothing from Alibaba covers prompt injection
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, Qwen3-Coder-30B-A3B-Instruct or SenseNova-Loop-9B-Preview?
Qwen3-Coder-30B-A3B-Instruct scores 55.7 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 3 of 4 scored categories. SenseNova-Loop-9B-Preview leads on documentation and upkeep.
Other comparisons with Qwen3-Coder-30B-A3B-Instruct or SenseNova-Loop-9B-Preview
- Agents-A1-4B vs Qwen3-Coder-30B-A3B-Instruct
- Agents-A1-4B vs SenseNova-Loop-9B-Preview
- Apertus v1.5 8B vs Qwen3-Coder-30B-A3B-Instruct
- Apertus v1.5 8B vs SenseNova-Loop-9B-Preview
- Apodex-1.1-mini vs Qwen3-Coder-30B-A3B-Instruct
- Apodex-1.1-mini vs SenseNova-Loop-9B-Preview
- Arete-27B vs Qwen3-Coder-30B-A3B-Instruct
- Arete-27B vs SenseNova-Loop-9B-Preview
- BigBang-v1 vs Qwen3-Coder-30B-A3B-Instruct
- BigBang-v1 vs SenseNova-Loop-9B-Preview
- Carbon-X vs Qwen3-Coder-30B-A3B-Instruct
- Carbon-X vs SenseNova-Loop-9B-Preview
- Cola2 vs Qwen3-Coder-30B-A3B-Instruct
- Cola2 vs SenseNova-Loop-9B-Preview
- Cosmos-Reason2-2B vs Qwen3-Coder-30B-A3B-Instruct
- Cosmos-Reason2-2B vs SenseNova-Loop-9B-Preview
- Darwin-36B-Opus vs Qwen3-Coder-30B-A3B-Instruct
- Darwin-36B-Opus vs SenseNova-Loop-9B-Preview
- DeepSeek-V3.2 vs Qwen3-Coder-30B-A3B-Instruct
- DeepSeek-V3.2 vs SenseNova-Loop-9B-Preview
- DeepSeek V4.1 Flash vs Qwen3-Coder-30B-A3B-Instruct
- DeepSeek V4.1 Flash vs SenseNova-Loop-9B-Preview
- DeepSeek-V4-Flash-0731 vs Qwen3-Coder-30B-A3B-Instruct
- DeepSeek-V4-Flash-0731 vs SenseNova-Loop-9B-Preview
- Devstral Small 2 vs Qwen3-Coder-30B-A3B-Instruct
- Devstral Small 2 vs SenseNova-Loop-9B-Preview
- DiffusionGemma 26B A4B IT vs Qwen3-Coder-30B-A3B-Instruct
- DiffusionGemma 26B A4B IT vs SenseNova-Loop-9B-Preview
- EXAONE 4.5 33B vs Qwen3-Coder-30B-A3B-Instruct
- EXAONE 4.5 33B vs SenseNova-Loop-9B-Preview
- Gemma 4 12B IT vs Qwen3-Coder-30B-A3B-Instruct
- Gemma 4 12B IT vs SenseNova-Loop-9B-Preview
- Gemma 4 26B A4B IT vs Qwen3-Coder-30B-A3B-Instruct
- Gemma 4 26B A4B IT vs SenseNova-Loop-9B-Preview
- Gemma 4 31B IT vs Qwen3-Coder-30B-A3B-Instruct
- Gemma 4 31B IT vs SenseNova-Loop-9B-Preview
- Gemma 4 E2B IT vs Qwen3-Coder-30B-A3B-Instruct
- Gemma 4 E2B IT vs SenseNova-Loop-9B-Preview
- Gemma 4 E4B IT vs Qwen3-Coder-30B-A3B-Instruct
- Gemma 4 E4B IT vs SenseNova-Loop-9B-Preview
- GLM-4.5-Air vs Qwen3-Coder-30B-A3B-Instruct
- GLM-4.5-Air vs SenseNova-Loop-9B-Preview
- GLM-4.7-Flash vs Qwen3-Coder-30B-A3B-Instruct
- GLM-4.7-Flash vs SenseNova-Loop-9B-Preview
- GLM-5.3-Flash vs Qwen3-Coder-30B-A3B-Instruct
- GLM-5.3-Flash vs SenseNova-Loop-9B-Preview
- GLM-5.3 vs Qwen3-Coder-30B-A3B-Instruct
- GLM-5.3 vs SenseNova-Loop-9B-Preview
- gpt-oss-120b vs Qwen3-Coder-30B-A3B-Instruct
- gpt-oss-120b vs SenseNova-Loop-9B-Preview
- gpt-oss-20b vs Qwen3-Coder-30B-A3B-Instruct
- gpt-oss-20b vs SenseNova-Loop-9B-Preview
- Granite 4.2 30B vs Qwen3-Coder-30B-A3B-Instruct
- Granite 4.2 30B vs SenseNova-Loop-9B-Preview
- Granite 4.2 3B vs Qwen3-Coder-30B-A3B-Instruct
- Granite 4.2 3B vs SenseNova-Loop-9B-Preview
- Granite 4.2 8B vs Qwen3-Coder-30B-A3B-Instruct
- Granite 4.2 8B vs SenseNova-Loop-9B-Preview
- Hy-Memory-30B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- Hy-Memory-30B-A3B vs SenseNova-Loop-9B-Preview
- Hy3 vs Qwen3-Coder-30B-A3B-Instruct
- Hy3 vs SenseNova-Loop-9B-Preview
- Inkling-Small vs Qwen3-Coder-30B-A3B-Instruct
- Inkling-Small vs SenseNova-Loop-9B-Preview
- Inkling vs Qwen3-Coder-30B-A3B-Instruct
- Inkling vs SenseNova-Loop-9B-Preview
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3-Coder-30B-A3B-Instruct
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs SenseNova-Loop-9B-Preview
- Kimi K3.1 Pro vs Qwen3-Coder-30B-A3B-Instruct
- Kimi K3.1 Pro vs SenseNova-Loop-9B-Preview
- Kimi K3 vs Qwen3-Coder-30B-A3B-Instruct
- Kimi K3 vs SenseNova-Loop-9B-Preview
- Kolibri-1 vs Qwen3-Coder-30B-A3B-Instruct
- Kolibri-1 vs SenseNova-Loop-9B-Preview
- Kronos vs Qwen3-Coder-30B-A3B-Instruct
- Kronos vs SenseNova-Loop-9B-Preview
- Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct
- Laguna M.1 vs SenseNova-Loop-9B-Preview
- Laguna S 2.1 vs Qwen3-Coder-30B-A3B-Instruct
- Laguna S 2.1 vs SenseNova-Loop-9B-Preview
- Laguna XS 2.1 vs Qwen3-Coder-30B-A3B-Instruct
- Laguna XS 2.1 vs SenseNova-Loop-9B-Preview
- LBS-27B vs Qwen3-Coder-30B-A3B-Instruct
- LBS-27B vs SenseNova-Loop-9B-Preview
- LFM2.5-2.6B vs Qwen3-Coder-30B-A3B-Instruct
- LFM2.5-2.6B vs SenseNova-Loop-9B-Preview
- LFM3-1.7B vs Qwen3-Coder-30B-A3B-Instruct
- LFM3-1.7B vs SenseNova-Loop-9B-Preview
- LFM3-Audio-2B vs Qwen3-Coder-30B-A3B-Instruct
- LFM3-Audio-2B vs SenseNova-Loop-9B-Preview
- LFM3-Omni-2B vs Qwen3-Coder-30B-A3B-Instruct
- LFM3-Omni-2B vs SenseNova-Loop-9B-Preview
- LFM3-VL-2B vs Qwen3-Coder-30B-A3B-Instruct
- LFM3-VL-2B vs SenseNova-Loop-9B-Preview
- Ling-3.0-tiny vs Qwen3-Coder-30B-A3B-Instruct
- Ling-3.0-tiny vs SenseNova-Loop-9B-Preview
- Ling-3.1-flash-1019 vs Qwen3-Coder-30B-A3B-Instruct
- Ling-3.1-flash-1019 vs SenseNova-Loop-9B-Preview
- LongCat-2.5 vs Qwen3-Coder-30B-A3B-Instruct
- LongCat-2.5 vs SenseNova-Loop-9B-Preview
- MiMo-V2.6 Distill Qwen 9B vs Qwen3-Coder-30B-A3B-Instruct
- MiMo-V2.6 Distill Qwen 9B vs SenseNova-Loop-9B-Preview
- MiMo-V2.6-Flash-RL vs Qwen3-Coder-30B-A3B-Instruct
- MiMo-V2.6-Flash-RL vs SenseNova-Loop-9B-Preview
- MiniCPM-o 4.5 vs Qwen3-Coder-30B-A3B-Instruct
- MiniCPM-o 4.5 vs SenseNova-Loop-9B-Preview
- MiniCPM-V 4.7 1B vs Qwen3-Coder-30B-A3B-Instruct
- MiniCPM-V 4.7 1B vs SenseNova-Loop-9B-Preview
- MiniCPM-V 4.7 35B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- MiniCPM-V 4.7 35B-A3B vs SenseNova-Loop-9B-Preview
- MiniCPM5-2B vs Qwen3-Coder-30B-A3B-Instruct
- MiniCPM5-2B vs SenseNova-Loop-9B-Preview
- MiniMax-M2.5 vs Qwen3-Coder-30B-A3B-Instruct
- MiniMax-M2.5 vs SenseNova-Loop-9B-Preview
- MiniMax-M2.7 vs Qwen3-Coder-30B-A3B-Instruct
- MiniMax-M2.7 vs SenseNova-Loop-9B-Preview
- MiniMax-M3.1-Flash vs Qwen3-Coder-30B-A3B-Instruct
- MiniMax-M3.1-Flash vs SenseNova-Loop-9B-Preview
- Mistral Large 4 vs Qwen3-Coder-30B-A3B-Instruct
- Mistral Large 4 vs SenseNova-Loop-9B-Preview
- Muse Glimmer 30B vs Qwen3-Coder-30B-A3B-Instruct
- Muse Glimmer 30B vs SenseNova-Loop-9B-Preview
- Nanbeige4.2-3B vs Qwen3-Coder-30B-A3B-Instruct
- Nanbeige4.2-3B vs SenseNova-Loop-9B-Preview
- Nanbeige4.3-33B vs Qwen3-Coder-30B-A3B-Instruct
- Nanbeige4.3-33B vs SenseNova-Loop-9B-Preview
- NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Qwen3-Coder-30B-A3B-Instruct
- NVIDIA Nemotron 3.5 Bolt E4B 4GB vs SenseNova-Loop-9B-Preview
- Nemotron 3.5 Lightning 30B A3B vs Qwen3-Coder-30B-A3B-Instruct
- Nemotron 3.5 Lightning 30B A3B vs SenseNova-Loop-9B-Preview
- Nemotron 3 Nano 30B A3B vs Qwen3-Coder-30B-A3B-Instruct
- Nemotron 3 Nano 30B A3B vs SenseNova-Loop-9B-Preview
- Nemotron 3 Nano 4B vs Qwen3-Coder-30B-A3B-Instruct
- Nemotron 3 Nano 4B vs SenseNova-Loop-9B-Preview
- Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-Coder-30B-A3B-Instruct
- Nemotron 3 Nano Omni 30B A3B Reasoning vs SenseNova-Loop-9B-Preview
- Nemotron 3 Super 120B A12B vs Qwen3-Coder-30B-A3B-Instruct
- Nemotron 3 Super 120B A12B vs SenseNova-Loop-9B-Preview
- Nemotron 3 Ultra 550B A55B vs Qwen3-Coder-30B-A3B-Instruct
- Nemotron 3 Ultra 550B A55B vs SenseNova-Loop-9B-Preview
- North Mini Code 1.0 vs Qwen3-Coder-30B-A3B-Instruct
- North Mini Code 1.0 vs SenseNova-Loop-9B-Preview
- occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct
- occamy-1.0 vs SenseNova-Loop-9B-Preview
- Olmo 3 7B Think vs Qwen3-Coder-30B-A3B-Instruct
- Olmo 3 7B Think vs SenseNova-Loop-9B-Preview
- Ornith-1.5-122B vs Qwen3-Coder-30B-A3B-Instruct
- Ornith-1.5-122B vs SenseNova-Loop-9B-Preview
- Ornith-1.5-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- Ornith-1.5-35B-A3B vs SenseNova-Loop-9B-Preview
- Ornith-1.5-397B vs Qwen3-Coder-30B-A3B-Instruct
- Ornith-1.5-397B vs SenseNova-Loop-9B-Preview
- Ornith-1.5-9B vs Qwen3-Coder-30B-A3B-Instruct
- Ornith-1.5-9B vs SenseNova-Loop-9B-Preview
- OTel-2.0-LLM-31B-IT vs Qwen3-Coder-30B-A3B-Instruct
- OTel-2.0-LLM-31B-IT vs SenseNova-Loop-9B-Preview
- Qwen-AgentWorld-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen-AgentWorld-35B-A3B vs SenseNova-Loop-9B-Preview
- Qwen3-30B-A3B-Instruct-2507 vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3-30B-A3B-Instruct-2507 vs SenseNova-Loop-9B-Preview
- Qwen3-4B-Instruct-2507 vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3-4B-Instruct-2507 vs SenseNova-Loop-9B-Preview
- Qwen3.5-0.8B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.5-0.8B vs SenseNova-Loop-9B-Preview
- Qwen3.5-122B-A10B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.5-122B-A10B vs SenseNova-Loop-9B-Preview
- Qwen3.5-2B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.5-2B vs SenseNova-Loop-9B-Preview
- Qwen3.5-397B-A17B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.5-397B-A17B vs SenseNova-Loop-9B-Preview
- Qwen3.5-4B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.5-4B vs SenseNova-Loop-9B-Preview
- Qwen3.5-9B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.5-9B vs SenseNova-Loop-9B-Preview
- Qwen3.6-27B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.6-27B vs SenseNova-Loop-9B-Preview
- Qwen3.6-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.6-35B-A3B vs SenseNova-Loop-9B-Preview
- Qwen3.8-27B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.8-27B vs SenseNova-Loop-9B-Preview
- Qwen3.8-Flash-Next vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3.8-Flash-Next vs SenseNova-Loop-9B-Preview
- Qwen3-Coder-30B-A3B-Instruct vs Qwen3-Coder-Next
- Qwen3-Coder-30B-A3B-Instruct vs Qwen3-Omni-30B-A3B-Instruct
- Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-2B-Instruct
- Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-30B-A3B-Instruct
- Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-32B-Instruct
- Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-4B-Instruct
- Qwen3-Coder-30B-A3B-Instruct vs Qwen3-VL-8B-Instruct
- Qwen3-Coder-30B-A3B-Instruct vs Qwopus3.8-27B-Flash-V2
- Qwen3-Coder-30B-A3B-Instruct vs Recursive Flint
- Qwen3-Coder-30B-A3B-Instruct vs Ripple-65B Preview
- Qwen3-Coder-30B-A3B-Instruct vs SmolLM3-3B
- Qwen3-Coder-30B-A3B-Instruct vs Spark-X2.6-4B
- Qwen3-Coder-30B-A3B-Instruct vs Step 3.7 Flash
- Qwen3-Coder-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-27B
- Qwen3-Coder-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next
- Qwen3-Coder-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)
- Qwen3-Coder-30B-A3B-Instruct vs Baidu Unlimited-OCR-2
- Qwen3-Coder-30B-A3B-Instruct vs WeVisOne-VL-2B
- Qwen3-Coder-30B-A3B-Instruct vs WeVisOne-VL-4B
- Qwen3-Coder-30B-A3B-Instruct vs ZAYA1-8B
- Qwen3-Coder-Next vs SenseNova-Loop-9B-Preview
- Qwen3-Omni-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview
- Qwen3-VL-2B-Instruct vs SenseNova-Loop-9B-Preview
- Qwen3-VL-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview
- Qwen3-VL-32B-Instruct vs SenseNova-Loop-9B-Preview
- Qwen3-VL-4B-Instruct vs SenseNova-Loop-9B-Preview
- Qwen3-VL-8B-Instruct vs SenseNova-Loop-9B-Preview
- Qwopus3.8-27B-Flash-V2 vs SenseNova-Loop-9B-Preview
- Recursive Flint vs SenseNova-Loop-9B-Preview
- Ripple-65B Preview vs SenseNova-Loop-9B-Preview
- SenseNova-Loop-9B-Preview vs SmolLM3-3B
- SenseNova-Loop-9B-Preview vs Spark-X2.6-4B
- SenseNova-Loop-9B-Preview vs Step 3.7 Flash
- SenseNova-Loop-9B-Preview vs Swift 1.5 Qwen3.8-27B
- SenseNova-Loop-9B-Preview vs Swift 1.5 Qwen3.8-Flash-Next
- SenseNova-Loop-9B-Preview vs ThinkingCap (Qwen3.8 27B)
- SenseNova-Loop-9B-Preview vs Baidu Unlimited-OCR-2
- SenseNova-Loop-9B-Preview vs WeVisOne-VL-2B
- SenseNova-Loop-9B-Preview vs WeVisOne-VL-4B
- SenseNova-Loop-9B-Preview vs ZAYA1-8B
Machine-readable
- This page as Markdown
/compare/qwen3-coder-30b-a3b-instruct-vs-sensenova-loop-9b-preview.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/qwen3-coder-30b-a3b-instruct.json·/api/v1/tools/sensenova-loop-9b-preview.json - From a terminal
anchor compare qwen3-coder-30b-a3b-instruct sensenova-loop-9b-preview(the CLI) - Over MCP
compare_tools {"a": "qwen3-coder-30b-a3b-instruct", "b": "sensenova-loop-9b-preview"}at/mcp, no key