# Gemma 4 26B A4B IT vs Inkling 2 Small > Gemma 4 26B A4B IT scores 72.2 (BB) to Inkling 2 Small's 58.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small - Markdown: https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small.md (~9,400 tokens) - Slim: https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small.min.md (~580 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small.json (this page as data, same URL with Accept: application/json) - 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: 2026-11-12 Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 2 of 4 scored categories. Both do open-weight models you run yourself. - Gemma 4 26B A4B IT: grade BB, 72.2/100, rank #5 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it.md · JSON https://www.anchorterminal.com/api/v1/tools/gemma-4-26b-a4b-it.json - Inkling 2 Small: grade C, 58.8/100, rank #102 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-2-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 6472 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### Gemma 4 26B A4B IT (BB) Good for: Agents on a 24 GB or larger GPU or Mac that want a fast, permissively licensed tool-calling model with images and long context Ahead on: - Reach, 90 against 40 - Risk, 70 against 65 Also in its favour: - Agent-ready, a grade of BB or better Watch for: No safety evaluation figures published ### Inkling 2 Small (C) Good 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. Watch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory ## Why the edge ### Reach: Gemma 4 26B A4B IT +50 - Gemma 4 26B A4B IT (90): Memory 25, Google's own 4-bit QAT GGUF is 14.4 GB, which with a fifth on top is 17.3 GB and lands in the 24 GB band, with the 1.2 GB vision projector extra for images. Runtimes 25, released support in vLLM, Transformers, llama.cpp, Ollama, SGLang and LM Studio, six of six. Builds 10, Google publishes one quantised precision (Q4_0 GGUF), since its unquantised QAT repository is BF16 and there's no FP8 build. Terms 15, plain Apache 2.0 with nothing added. Download 10, no account or gate. Hosted 5, the Gemini API serves it and four inference providers are live on Hugging Face. - 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. ### Risk: Gemma 4 26B A4B IT +5 - Gemma 4 26B A4B IT (70): File safety 25, safetensors and GGUF only, with nothing from the repository run on load. Provenance 15, the files sit in Google's own organisation and every file has a checksum. Safety evaluation 0, the card says testing showed minimal policy violations but gives no figures. Agent guidance 10, the card names the harm categories its safety training covers and asks for content-safety safeguards, and the tool guide says to validate calls, with no prompt-injection guidance. Licence risk 15, Apache 2.0 with no added policy, no threshold and a working link. Security programme 5, Google's security.txt and reward policy give a route to report a flaw, but no public Gemma advisories were found and GitHub's advisory tab couldn't be checked. - 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 | Gemma 4 26B A4B IT | Inkling 2 Small | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 90 | 40 | Gemma 4 26B A4B IT +50 | | Risk | 20% (20 this run) | 70 | 65 | Gemma 4 26B A4B IT +5 | | Agent interface | 10% (10 this run) | 85 | 85 | even | | Documentation and upkeep | 10% (10 this run) | 65 | 67 | Inkling 2 Small +2 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **72.2 · BB** | **58.8 · C** | | ## Facts side by side | Fact | Gemma 4 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 | no | no | | Last release | 2026-07-20 | 2026-11-12 | | Terms last updated | no document linked | no document linked | | Privacy policy last updated | no document linked | no document linked | | Agent reviews | 3.8/5 (4) | none | ## How the scores have moved ### Gemma 4 26B A4B IT No score change since it was listed. ### Inkling 2 Small - +6.7 on 12 November 2026 (D to C): product ## Verdicts **Gemma 4 26B A4B IT.** A fast mixture-of-experts cousin for general agent work with tools, optional thinking and image input, under Apache 2.0. Google's 4-bit build needs about 17 GB, so it runs on a 24 GB GPU or Mac in any common runtime. The main risks are no published safety results, no documented JSON output and unanswered template bug reports. **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 ### Gemma 4 26B A4B IT 1. On the reference machine run `llama-server -hf google/gemma-4-26B-A4B-it-qat-q4_0-gguf --hf-file gemma-4-26B_q4_0-it.gguf --jinja -c 65536`, and add the mmproj file for images 2. With Ollama run `ollama run gemma4:26b` and raise num_ctx or OLLAMA_CONTEXT_LENGTH, since Google's guide says it defaults to 4K below 24 GiB of VRAM and agents want at least 64K 3. In vLLM or SGLang pass `--tool-call-parser gemma4 --reasoning-parser gemma4` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as text 4. Thinking is off by default; pass enable_thinking=True or start the system prompt with <|think|>, and drop earlier turns' thinking from history except on tool-call turns 5. Validate tool names and arguments before running them, and check any JSON yourself ### Inkling 2 Small 1. 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 2. In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling` 3. Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet 4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99 5. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens 6. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error 7. Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part 8. Use guided decoding or validate JSON yourself, since structured output isn't documented 9. 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 10. 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, Gemma 4 26B A4B IT or Inkling 2 Small? Gemma 4 26B A4B IT scores 72.2 (BB) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 2 of 4 scored categories. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemma-4-26b-a4b-it", "b": "inkling-2-small"}`. 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