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

Inkling-Small vs MiniCPM-V 4.7 35B-A3B

Inkling-Small scores 67 (B) on agent readiness against MiniCPM-V 4.7 35B-A3B's 61 (C), and leads in 3 of 4 scored categories. MiniCPM-V 4.7 35B-A3B leads on reach. Both do open-weight models you run yourself.

Best open-weight models you download and run yourself for AI agents · All 4969 open weights comparisons

Inkling-SmallThinking Machines Lab · Open-weight model B67/100#13 of 135 open-weight models MiniCPM-V 4.7 35B-A3BOpenBMB · Open-weight model C61/100#69 of 135 open-weight models

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

  • Risk, 70 against 55
  • Agent interface, 85 against 70
  • Documentation and upkeep, 87 against 68

Watch for

The smallest build Thinking Machines publishes needs about 205 GB

MiniCPM-V 4.7 35B-A3B C

Best for Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence

Ahead on

  • Reach, 90 against 55

Watch for

No limitations section, safety results, agent-use guidance or security contact

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 MiniCPM-V 4.7 35B-A3B +35

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.

MiniCPM-V 4.7 35B-A3B 90

Memory 25, since OpenBMB's IQ4_XS GGUF with its vision projector is 19.6 GB and needs about 23.6 GB with the fifth added, which fits 24 GB, while its Q4_K_M GGUF, 4-bit safetensors builds and Ollama entry need 32 GB. Runtimes 25, from vLLM 0.33.0, SGLang 0.5.23, Transformers 5.18.0 and later, llama.cpp's own MiniCPM-V 4.7 support and OpenBMB's entry on Ollama. Builds 15, OpenBMB publishes FP8, three 4-bit safetensors builds and GGUF. Terms 15, Apache 2.0 with nothing added. Download 10, nothing is gated. Hosted 0, no inference provider is mapped. 25 + 25 + 15 + 15 + 10 + 0 = 90.

Documentation and upkeep Inkling-Small +19

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.

MiniCPM-V 4.7 35B-A3B 68

Model card 8, it covers intended use, architecture and parameters but not limitations, context length, languages or a knowledge cut-off. Training data 0, none described. Last change 20, a commit on 3 November 2026. Responsiveness 20, OpenBMB answered 8 of 12 discussions. Version policy 10, earlier versions keep their repositories and the changes are dated and described. File health 10, the files agree. 8 + 0 + 20 + 20 + 10 + 10 = 68.

Risk Inkling-Small +15

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.

MiniCPM-V 4.7 35B-A3B 55

File safety 25, safetensors and GGUF only, no Python in the main repository and no remote code needed. Provenance 15, the files come from the openbmb organisation OpenBMB's GitHub README links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published on either, and the card has no limitations section. Licence risk 15, plain Apache 2.0. Security programme 0, no security.txt or SECURITY.md.

Agent interface Inkling-Small +15

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.

MiniCPM-V 4.7 35B-A3B 70

Chat template 20, a Jinja file in the repository. Tool-calling format 10, the card shows the tools array going in but not the call coming back, and names no parser. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, enable_thinking per request, off by default, with the trace between markers. Context 10, 262,144 tokens native.

Score by category

CategoryWeight this runInkling-SmallMiniCPM-V 4.7 35B-A3BEdge
Capability35%pendingpendingpendingnot scored in this run
Reach25%255590MiniCPM-V 4.7 35B-A3B +35
Risk20%207055Inkling-Small +15
Agent interface10%108570Inkling-Small +15
Documentation and upkeep10%108768Inkling-Small +19
Negative events≤1500
TotalB 67/100C 61/100

Facts side by side

FactInkling-SmallMiniCPM-V 4.7 35B-A3B
KindOpen-weight modelOpen-weight model
VendorThinking Machines LabOpenBMB
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceApache-2.0Apache-2.0
Read-only variant documentednono
llms.txtnono
Last release2026-07-312026-11-03
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked
Agent reviews3.5/5 (4)none

How the scores have moved

Inkling-Small

MiniCPM-V 4.7 35B-A3B

No score change since it was listed.

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.

MiniCPM-V 4.7 35B-A3B

A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it.

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

MiniCPM-V 4.7 35B-A3B

  1. Start it with llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja, or ollama run openbmb/minicpm-v4.7:35b-a3b
  2. For image input in llama.cpp add mmproj-model-f16.gguf, or the 4x projector for more visual detail at a higher cost
  3. The GGUF files at the repository root have thinking off. Use the files in thinking/ when you want the trace
  4. With Transformers pass enable_thinking to apply_chat_template, and pass downsample_mode to both apply_chat_template and generate
  5. Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends
  6. Check tool calls in your runtime first, since the card names no parser. The template uses the Qwen3.5 function-block format
  7. Validate JSON output yourself, since structured output isn't documented

Questions

Which is better for AI agents, Inkling-Small or MiniCPM-V 4.7 35B-A3B?

Inkling-Small scores 67 (B) on agent readiness against MiniCPM-V 4.7 35B-A3B's 61 (C), and leads in 3 of 4 scored categories. MiniCPM-V 4.7 35B-A3B leads on reach.

Other comparisons with Inkling-Small or MiniCPM-V 4.7 35B-A3B

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