# SenseNova-Loop-9B-Preview vs Step 3.7 Flash > Step 3.7 Flash scores 59.8 (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-step-3-7-flash - Markdown: https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash.md (~10,300 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 Step 3.7 Flash scores 59.8 (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 and documentation and upkeep. 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 - Step 3.7 Flash: grade C, 59.8/100, rank #93 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/step-3-7-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/step-3-7-flash.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 Ahead on: - Risk, 50 against 45 - Documentation and upkeep, 44 against 39 Watch for: No released runtime runs it. vLLM and SGLang need unmerged pull requests ### Step 3.7 Flash (C) Good for: Teams with a GPU server or a provider account that want an open, long-context agent model with vision Ahead on: - Reach, 70 against 40 - Agent interface, 85 against 60 Watch for: About 131 GB to run at 4 bits with images, over a 128 GB machine's share ## Why the edge ### Reach: Step 3.7 Flash +30 - 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. - Step 3.7 Flash (70): Memory 5, the smallest build at 4 bits is StepFun's IQ4_XS GGUF, 104.99 GB with the 3.97 GB projector, and 108.96 GB × 1.2 = 130.8 GB, over what the reference machine can give a model and within 256 GB. The IQ3 and Q3 builds are below 4 bits and aren't read. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the step3p7 model, and llama.cpp b12242 has the architecture, with StepFun's own GGUF. Four at 5 each, and the card documents all four. Builds 15, StepFun publishes GGUF at five quantised precisions, an FP8 build and an NVFP4 build. Terms 15, Apache 2.0 in the card's metadata and its licence section, an OSI licence with nothing added. Download 10, the Hub API reports gated false for all four repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, StepFun's own API serves it, per the card and our StepFun API listing, and Featherless and DeepInfra are live for it on Hugging Face. 5 + 20 + 15 + 15 + 10 + 5 = 70. ### Agent interface: Step 3.7 Flash +25 - 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. - Step 3.7 Flash (85): Chat template 20, chat_template.jinja in the repository (5,723 characters). Tool-calling format 25, the card names the parser to use in two runtimes, step3p5 in vLLM (with auto tool choice) and in SGLang, and both ship Step parsers in a release. Trained tool calling 20, the card presents tool orchestration as a main use, with multi-turn results, and the template renders every call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output for the weights. Reasoning control 10, the template has a reasoning_effort setting and keeps reasoning_content, and the card names the step3p5 reasoning parser for vLLM and SGLang, which returns the reasoning apart from the answer. Context 10, 256K tokens per the card, and 262,144 positions in config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85. ### Risk: SenseNova-Loop-9B-Preview +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. - Step 3.7 Flash (45): File safety 15, safetensors and GGUF only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the stepfun-ai organisation, which the card's StepFun platform and model page belong to (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations section and gives no guidance on prompt injection, instruction priority, refusals or safeguards. 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 our StepFun API listing found no security.txt, bug bounty or disclosure policy. 15 + 15 + 0 + 0 + 15 + 0 = 45. ### Documentation and upkeep: SenseNova-Loop-9B-Preview +5 - 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. - Step 3.7 Flash (39): Model card 14, Intended use, the architecture, the parameters, the context and the language (in the metadata) are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the last commit, on 3 June 2026, fixed the modelling code, 160 days before this check and within 180. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (29 May to 24 June 2026) has a reply from a stepfun-ai member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, Step-3.5-Flash stays in its own repositories and 3.7 came out in new ones, with no dated note on the older cards that we read. File health 10, Config, template and card agree on the architecture and the context, and June commits fixed the modelling code. 14 + 0 + 10 + 0 + 5 + 10 = 39. ## Score by category | Category | Weight | SenseNova-Loop-9B-Preview | Step 3.7 Flash | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 40 | 70 | Step 3.7 Flash +30 | | Risk | 20% (20 this run) | 50 | 45 | SenseNova-Loop-9B-Preview +5 | | Agent interface | 10% (10 this run) | 60 | 85 | Step 3.7 Flash +25 | | Documentation and upkeep | 10% (10 this run) | 44 | 39 | SenseNova-Loop-9B-Preview +5 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **46.8 · D** | **59.8 · C** | | ## Facts side by side | Fact | SenseNova-Loop-9B-Preview | Step 3.7 Flash | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | SenseTime (SenseNova) | StepFun | | 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 (metadata and card; no LICENSE file) | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-11-02 | 2026-06-03 | | 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. **Step 3.7 Flash.** A capable open agent model with a clean licence, every kind of build and four released runtimes. Two things hold it back: it's a little too big for a 128 GB machine at 4 bits, whatever the card says, and StepFun has gone quiet on the repository since June. No safety results, limitations or data description. ## 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 ### Step 3.7 Flash 1. On a 128 GB machine the 4-bit GGUF won't fit with a working context. Use StepFun's API or a provider, or a server 2. On vLLM or SGLang pass `--tool-call-parser step3p5 --reasoning-parser step3p5` 3. The card's commands pass trust-remote-code. Released Transformers 5.22.2 has the model built in if you'd rather not run the repository's code 4. For llama.cpp load the mmproj file from StepFun's GGUF repository for image input 5. StepFun's API has two hosts. Use the one where your key was issued, `api.stepfun.ai` or `api.stepfun.com` 6. The same model is on our StepFun API listing, with prices and terms ## Questions ### Which is better for AI agents, SenseNova-Loop-9B-Preview or Step 3.7 Flash? Step 3.7 Flash scores 59.8 (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 and documentation and upkeep. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash.json, and with the fewest tokens: https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "sensenova-loop-9b-preview", "b": "step-3-7-flash"}`. 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[Step 3.7 Flash vs ZAYA1-8B](https://www.anchorterminal.com/compare/step-3-7-flash-vs-zaya1-8b.md) --- Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). 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