Head to head · Open-weight models you run yourself · October 2026 research run
DiffusionGemma 26B A4B IT vs Inkling 2 Small
Inkling 2 Small scores 58.8 (C) on agent readiness against DiffusionGemma 26B A4B IT's 51.3 (D), and leads in 2 of 4 scored categories. DiffusionGemma 26B A4B IT leads on reach and risk. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 6472 open weights comparisons
Which one, for what
Best for Agents with about 64 GB of GPU memory that want fast single-user generation from text and images and can accept lower quality than Gemma 4
Ahead on
- Reach, 55 against 40
- Risk, 70 against 65
Watch for
No quantised build from Google, so the smallest official build needs the 64 GB band
Best for Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.
Ahead on
- Agent interface, 85 against 70
- Documentation and upkeep, 67 against 60
Watch for
The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory
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 DiffusionGemma 26B A4B IT +15
DiffusionGemma 26B A4B IT 55
Memory earns 15 because the only Google build is 51.7 GB of BF16, about 62 GB with the fifth added, which needs the 64 GB band. Runtimes get 15 for Transformers from 5.11.0, SGLang from v0.5.22 and vLLM, whose releases from v0.24.0 (tag commit 28 June 2026) to v0.33.0 register DiffusionGemmaForBlockDiffusion; llama.cpp (b12114, and Ollama through its pin b11963) and LM Studio don't run it. Builds score 0 because Google publishes no quantised build, though others have published FP8, NVFP4, GGUF and 4-bit copies. Apache 2.0 with nothing added gives terms the full 15 and the ungated repository gives download the full 10. Hosted too scores 0, since no inference provider is mapped and the Gemini API doesn't serve it.
Inkling 2 Small 40
Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). 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 Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.
Agent interface Inkling 2 Small +15
DiffusionGemma 26B A4B IT 70
The chat template is in the repository (20) and handles several tool calls in one turn, and the card names function calling as trained (20). The tool-calling format gets 10, since only the template and the shipped response schema say how tools work here and Google's tool-calling guide is for Gemma 4. Structured output scores 0, undocumented and rejected by SGLang. Thinking can be turned on or off per request with the reasoning in its own channel (10), and the context is 256K (10).
Inkling 2 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 for this model, 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 xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85.
Documentation and upkeep Inkling 2 Small +7
DiffusionGemma 26B A4B IT 60
The card covers all seven points (20), and the training data is a general description with a January 2025 cut-off (10). The files last changed on 15 July 2026, 112 days before this check (10). Google organisation members answered 10 of the 20 discussions (10). It's a first release (5). File health gets 5 because the diffusers scheduler config disagrees with the card's sampling settings, though the files on the documented path agree.
Inkling 2 Small 67
Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67.
Risk DiffusionGemma 26B A4B IT +5
DiffusionGemma 26B A4B IT 70
File safety gets the full 25, safetensors only and loaded by Transformers' own code and a Jinja template. Provenance gets 15 for files in Google's organisation with a hash for every file. Licence risk keeps 15 under plain Apache 2.0. Agent guidance gets 10 for the card's list of harm categories and its advice to add content-safety safeguards. Safety evaluation scores 0 because the card states improvements without figures. The security programme gets 5 for Google's security.txt, with no public advisories for Gemma.
Inkling 2 Small 65
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, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, 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. 25 + 15 + 10 + 5 + 5 + 5 = 65.
Score by category
| Category | Weight this run | DiffusionGemma 26B A4B IT | Inkling 2 Small | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 55 | 40 | DiffusionGemma 26B A4B IT +15 |
| Risk | 20%20 | 70 | 65 | DiffusionGemma 26B A4B IT +5 |
| Agent interface | 10%10 | 70 | 85 | Inkling 2 Small +15 |
| Documentation and upkeep | 10%10 | 60 | 67 | Inkling 2 Small +7 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 51.3/100 | C 58.8/100 |
Facts side by side
| Fact | DiffusionGemma 26B A4B IT | Inkling 2 Small |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Google DeepMind | Thinking Machines Lab |
| 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 | yes | no |
| Last release | 2026-07-15 | 2026-11-12 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 2.5/5 (4) | none |
How the scores have moved
Verdicts
DiffusionGemma 26B A4B IT
A text diffusion model for fast low-concurrency local generation from text, images and video, with optional thinking and Gemma 4's tool format, under Apache 2.0. Google's BF16 files need about 62 GB, and it runs in Transformers, SGLang and vLLM. Google's own figures put it below Gemma 4 26B A4B, and Google labels it experimental.
Inkling 2 Small
Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.
Before you call either
DiffusionGemma 26B A4B IT
- Serve it with
sglang serve --model-path google/diffusiongemma-26B-A4B-it --dllm-algorithm Gemma4Renoise --trust-remote-codeon SGLang v0.5.22 or later, then call /v1/chat/completions - In Transformers, install
transformers>=5.11.0and loadDiffusionGemmaForBlockDiffusionwithdtype="auto"; generation_config.json already holds the recommended sampler - Turn thinking on with
enable_thinking=Truein apply_chat_template or<|think|>at the start of the system prompt, read the reasoning between<|channel>thoughtand<channel|>, and drop it from history before the next turn - Don't rely on temperature, top_p, logit_bias or JSON Schema in SGLang, which ignores or rejects them for this model; validate JSON yourself
- Streaming arrives one 256-token canvas at a time, not token by token
- Put images before text in the prompt, and pick an image token budget of 70 to 1,120 by how much detail the task needs
Inkling 2 Small
- No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image
- In vLLM pass
--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling. In SGLang the tool-call parser isinkling2and the reasoning parserinkling - Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet
- Pass
reasoning_effortas none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99 - Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens
- Tool call arguments must reach the template as an object, not a JSON string, or it raises an error
- Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part
- Use guided decoding or validate JSON yourself, since structured output isn't documented
- Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026
- Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal
Questions
Which is better for AI agents, DiffusionGemma 26B A4B IT or Inkling 2 Small?
Inkling 2 Small scores 58.8 (C) on agent readiness against DiffusionGemma 26B A4B IT's 51.3 (D), and leads in 2 of 4 scored categories. DiffusionGemma 26B A4B IT leads on reach and risk.
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- Inkling vs Inkling 2 Small
Machine-readable
- This page as Markdown
/compare/diffusiongemma-26b-a4b-it-vs-inkling-2-small.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/diffusiongemma-26b-a4b-it.json·/api/v1/tools/inkling-2-small.json - From a terminal
anchor compare diffusiongemma-26b-a4b-it inkling-2-small(the CLI) - Over MCP
compare_tools {"a": "diffusiongemma-26b-a4b-it", "b": "inkling-2-small"}at/mcp, no key