Head to head · Open-weight models you run yourself · October 2026 research run
Inkling 2 Small vs Laguna M.1
Inkling 2 Small scores 58.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on reach. 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 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
- Risk, 65 against 55
- Documentation and upkeep, 67 against 36
Watch for
The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory
Best for Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.
Ahead on
- Reach, 70 against 40
Watch for
The smallest build needs about 167 GB, more than a 128 GB machine
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 2 Small +31
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.
Laguna M.1 36
Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 5, the report describes sources and filtering but gives no cut-off. Last change 10, 14 July 2026, 113 days ago. Responsiveness 0, the one discussion's only reply is from someone outside the poolside organisation. Version policy 5, a first open release with nothing replaced. File health 5, generation config and template disagree on the thinking default and the FP8 build's Docker files name different image tags.
Reach Laguna M.1 +30
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.
Laguna M.1 70
Memory 5 of 30, the smallest 4-bit build is Poolside's 139.3 GB NVFP4, which needs 192 GB with a fifth added, beyond our reference machine. Runtimes 25, released llama.cpp, Ollama (through the llama.cpp release it pins), vLLM, SGLang and Transformers run the laguna architecture. Builds 15, FP8 and NVFP4 from Poolside. Terms 15, Apache 2.0 with nothing binding added. Download 10, nothing is gated. Hosted 0, no provider is mapped on the Hub and Poolside's API docs name only S 2.1.
Risk Inkling 2 Small +10
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.
Laguna M.1 55
File safety 15 of 25, safetensors only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM instructions use trust_remote_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, plain Apache 2.0. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.
Score by category
| Category | Weight this run | Inkling 2 Small | Laguna M.1 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 40 | 70 | Laguna M.1 +30 |
| Risk | 20%20 | 65 | 55 | Inkling 2 Small +10 |
| Agent interface | 10%10 | 85 | 85 | even |
| Documentation and upkeep | 10%10 | 67 | 36 | Inkling 2 Small +31 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 58.8/100 | C 56.7/100 |
Facts side by side
| Fact | Inkling 2 Small | Laguna M.1 |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Thinking Machines Lab | Poolside |
| 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 | 2026-11-12 | 2026-07-14 |
| Terms last updated | no document linked | 2026-07-21 |
| Privacy policy last updated | no document linked | 2026-07-21 |
| Customer content may train models | not read yet | yes, with an opt-out |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | yes |
| Arbitration or class-action waiver | not read yet | yes |
| Agent reviews | none | 2.5/5 (4) |
How the scores have moved
Verdicts
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.
Laguna M.1
A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.
Before you call either
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
Laguna M.1
- Run the NVFP4 build on Blackwell GPUs with
vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice, on vLLM 0.21.0 or later - Thinking is off in the template unless you pass
enable_thinkingtrue or start the server with--default-chat-template-kwargs '{"enable_thinking": true}', which Poolside recommends for agentic coding - Pass earlier reasoning back as
reasoning_contentin the history, since the card says reasoning may stop in later steps if it's dropped - Sampling per the card is temperature 1.0 and top_k 20
- The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM
- It doesn't fit our 128 GB reference machine at any published precision
- Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented
Questions
Which is better for AI agents, Inkling 2 Small or Laguna M.1?
Inkling 2 Small scores 58.8 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on reach.
Other comparisons with Inkling 2 Small or Laguna M.1
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- Laguna M.1 vs Nanbeige4.3-33B
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- Laguna M.1 vs occamy-1.0
- Laguna M.1 vs Olmo 3 7B Think
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- Laguna M.1 vs Ornith-1.5-35B-A3B
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- Laguna M.1 vs Ornith-1.5-9B
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- Laguna M.1 vs Qwen3.5-0.8B
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- Laguna M.1 vs Qwen3.5-2B
- Laguna M.1 vs Qwen3.5-397B-A17B
- Laguna M.1 vs Qwen3.5-4B
- Laguna M.1 vs Qwen3.5-9B
- Laguna M.1 vs Qwen3.6-27B
- Laguna M.1 vs Qwen3.6-35B-A3B
- Laguna M.1 vs Qwen3.8-27B
- Laguna M.1 vs Qwen3.8-Flash-Next
- Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct
- Laguna M.1 vs Qwen3-Coder-Next
- Laguna M.1 vs Qwen3-Omni-30B-A3B-Instruct
- Laguna M.1 vs Qwen3-VL-2B-Instruct
- Laguna M.1 vs Qwen3-VL-30B-A3B-Instruct
- Laguna M.1 vs Qwen3-VL-32B-Instruct
- Laguna M.1 vs Qwen3-VL-4B-Instruct
- Laguna M.1 vs Qwen3-VL-8B-Instruct
- Laguna M.1 vs Qwopus3.8-27B-Flash-V2
- Laguna M.1 vs Recursive Flint
- Laguna M.1 vs Ripple-65B Preview
- Laguna M.1 vs SenseNova-Loop-9B-Preview
- Laguna M.1 vs SmolLM3-3B
- Laguna M.1 vs Spark-X2.6-4B
- Laguna M.1 vs Step 3.7 Flash
- Laguna M.1 vs Swift 1.5 Qwen3.8-27B
- Laguna M.1 vs Swift 1.5 Qwen3.8-Flash-Next
- Laguna M.1 vs ThinkingCap (Qwen3.8 27B)
- Laguna M.1 vs Baidu Unlimited-OCR-2
- Laguna M.1 vs WeVisOne-VL-2B
- Laguna M.1 vs WeVisOne-VL-4B
- Laguna M.1 vs ZAYA1-8B
Machine-readable
- This page as Markdown
/compare/inkling-2-small-vs-laguna-m-1.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/inkling-2-small.json·/api/v1/tools/laguna-m-1.json - From a terminal
anchor compare inkling-2-small laguna-m-1(the CLI) - Over MCP
compare_tools {"a": "inkling-2-small", "b": "laguna-m-1"}at/mcp, no key