Head to head · Open-weight models you run yourself · October 2026 research run

Inkling-Small vs SenseNova-Loop-9B-Preview

Inkling-Small scores 67 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category. 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

Inkling-Small B

Best for Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.

Ahead on

  • Reach, 55 against 40
  • Risk, 70 against 50
  • Agent interface, 85 against 60
  • Documentation and upkeep, 87 against 44

Watch for

The smallest build Thinking Machines publishes needs about 205 GB

SenseNova-Loop-9B-Preview D

Best for Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today

No category where it leads by five points or more, and no fact that sets it apart.

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.

Documentation and upkeep Inkling-Small +43

Inkling-Small 87

Model card 17 of 20, everything but a dated knowledge cut-off, counting Thinking Machines' own model card page. Training data 15, an EU training-content summary with sources, mix, a July 2026 collection cut-off and filtering. Last change 20, the files last changed on 31 July 2026, but Thinking Machines' Inkling renderer in tinker-cookbook changed in its 30 October 2026 release. Responsiveness 20, Thinking Machines answered 8 of the 9 questions in its discussions. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17+15+20+20+5+10 = 87.

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.

Agent interface Inkling-Small +25

Inkling-Small 85

Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to the maximum, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens.

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.

Risk Inkling-Small +20

Inkling-Small 70

File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT and FORTRESS results and described external red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 10, the card says what its refusals miss and which safeguards to add, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent.

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.

Reach Inkling-Small +15

Inkling-Small 55

Memory 5 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 170.8 GB, about 205 GB with a fifth added, so it needs 256 GB. Runtimes 15, released Transformers, vLLM and SGLang run it, llama.cpp, Ollama and LM Studio don't. Builds 10, one quantised build (NVFP4). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and DeepInfra is live on Hugging Face.

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.

Score by category

CategoryWeight this runInkling-SmallSenseNova-Loop-9B-PreviewEdge
Capability35%pendingpendingpendingnot scored in this run
Reach25%255540Inkling-Small +15
Risk20%207050Inkling-Small +20
Agent interface10%108560Inkling-Small +25
Documentation and upkeep10%108744Inkling-Small +43
Negative events≤1500
TotalB 67/100D 46.8/100

Facts side by side

FactInkling-SmallSenseNova-Loop-9B-Preview
KindOpen-weight modelOpen-weight model
VendorThinking Machines LabSenseTime (SenseNova)
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceApache-2.0Apache-2.0
Read-only variant documentednono
llms.txtnono
Last release2026-07-312026-11-02
Terms last updatedno document linkednot read yet
Privacy policy last updatedno document linkedno document linked
Agent reviews3.5/5 (4)none

How the scores have moved

Verdicts

Inkling-Small

A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside 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

Inkling-Small

  1. Start the NVFP4 build with SGLang's recipe, sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling, on Blackwell for W4A4
  2. Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself
  3. Pass reasoning_effort as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs and SGLang's cookbook list xhigh
  4. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens
  5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error
  6. Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card
  7. Use guided decoding or validate JSON yourself, since structured output isn't documented
  8. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal

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, Inkling-Small or SenseNova-Loop-9B-Preview?

Inkling-Small scores 67 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category.

Other comparisons with Inkling-Small or SenseNova-Loop-9B-Preview

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