# Inkling 2 Small vs MiniMax-M2.5

> MiniMax-M2.5 and Inkling 2 Small score within a point of each other for open-weight models you run yourself, 59 and 58.8 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5
- Markdown: https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5.md (~9,900 tokens)
- Slim: https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5.min.md (~780 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5.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)
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- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-12

MiniMax-M2.5 and Inkling 2 Small score within a point of each other on agent readiness, 59 (C) and 58.8 (C). Inkling 2 Small leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- 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
- MiniMax-M2.5: grade C, 59/100, rank #99 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m2-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.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

### 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.

Ahead on:
- Risk, 65 against 30
- Agent interface, 85 against 75
- Documentation and upkeep, 67 against 37

Watch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory

### MiniMax-M2.5 (C)

Good for: Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy

Ahead on:
- Reach, 65 against 40

Watch for: 230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine


## Why the edge

### Risk: Inkling 2 Small +35

- 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.
- MiniMax-M2.5 (30): File safety earns 15, safetensors only with no pickle files, less 10 because every documented loading route passes trust_remote_code for the repository's Python. Provenance earns the full 15, files in the organisation MiniMax links to with a SHA-256 for each shard. Safety evaluation and agent guidance earn nothing, as MiniMax publishes neither. Licence risk earns nothing (read 21 October 2026). The Prohibited Uses Policy goes beyond the law, MiniMax can end the licence for any breach and replaced its terms three weeks after release, and that change on 6 March 2026 came with no dated note while the card still links to a deleted file. The security programme earns nothing, with no security.txt, disclosure policy, SECURITY.md or advisories, and only a general contact address on the card.

### Documentation and upkeep: Inkling 2 Small +30

- 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.
- MiniMax-M2.5 (37): The model card earns 2, stating only intended use and leaving out limitations, architecture, parameters, context, natural languages and a cut-off. Training data earns 5 for a general description with no cut-off. The last change earns 20, a card edit on 26 October 2026 (commit 2515a3ea, a link renamed from MiniMax Agent to MiniMax Code), 9 days before this check; the files, template and code are unchanged since February. Responsiveness earns 5, with a MiniMax reply in 2 of the 40 most recent discussions and none since April. Version policy earns 5, since earlier and later models sit in their own repositories without dated notes. File health earns nothing, because the card's licence metadata still contradicts the licence in the files and an FP8 output report still waits without a reply. 2+5+20+5+5+0 = 37.

### Reach: MiniMax-M2.5 +25

- 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.
- MiniMax-M2.5 (65): Memory earns 5. MiniMax only publishes its 230 GB FP8 release, and the smallest build of 4-bit or better from a runtime's own library is LM Studio's MLX 4-bit at 128.7 GB, about 154 GB with the fifth added, so it needs more than our 107.4 GB machine and fits within 256 GB. Runtimes earn the full 25, with model code in released vLLM v0.33.0, SGLang v0.5.23, llama.cpp and Transformers, an LM Studio catalogue entry, and Ollama 0.40.14, whose pinned llama.cpp b11963 has the minimax-m2 architecture, though Ollama's library lists no build. Builds earn 10 for one publisher precision, the FP8 release. Terms earn 10 for a custom licence that allows free commercial use under a use policy. Download earns 10, with no gate or account. Hosted earns 5, since Novita and Featherless AI serve it through Hugging Face, while MiniMax's own API is closed to new users and retires it on 18 November 2026. 5+25+10+10+10+5 = 65.

### Agent interface: Inkling 2 Small +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.
- MiniMax-M2.5 (75): The chat template earns 20 for chat_template.jinja in the repository. The tool-calling format earns 25, as MiniMax's own guide documents how tools go in and how calls come back, gives a parsing function, and its deployment guides name the vLLM and SGLang parsers. Trained tool calling earns 20, with several invoke blocks in one call. Structured output earns nothing, since JSON output isn't documented or claimed. Reasoning control earns nothing, because thinking is always on with no documented way to turn it off or budget it. Context earns 10 for 196,608 tokens with no position scaling.

## Score by category

| Category | Weight | Inkling 2 Small | MiniMax-M2.5 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 40 | 65 | MiniMax-M2.5 +25 |
| Risk | 20% (20 this run) | 65 | 30 | Inkling 2 Small +35 |
| Agent interface | 10% (10 this run) | 85 | 75 | Inkling 2 Small +10 |
| Documentation and upkeep | 10% (10 this run) | 67 | 37 | Inkling 2 Small +30 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **58.8 · C** | **59 · C** | |

## Facts side by side

| Fact | Inkling 2 Small | MiniMax-M2.5 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Thinking Machines Lab | MiniMax |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | MiniMax Model License (model) and modified MIT (code) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-12 | 2026-02-12 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | none | 1.8/5 (4) |

## How the scores have moved

### Inkling 2 Small

- +6.7 on 12 November 2026 (D to C): product

### MiniMax-M2.5

- +1.5 on 4 November 2026: product

## 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.

**MiniMax-M2.5.** MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT.

## Before you call either

### 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

### MiniMax-M2.5

1. Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think
2. In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code
3. MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache
4. On a single large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.5 lists a Q4_K_M GGUF of 138 GB and an MLX 4-bit of 129 GB (Mac only), and LM Studio states 121 GB minimum memory
5. Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends
6. Budget output tokens for thinking on every turn, since the template always opens a think block
7. Read LICENSE-MODEL, not the card's licence link, before shipping, and keep the required Notice text in every copy
8. Without the hardware, call it through Novita or Featherless AI; MiniMax's own API retires M2.5 on 18 November 2026

## Questions

### Which is better for AI agents, Inkling 2 Small or MiniMax-M2.5?

MiniMax-M2.5 and Inkling 2 Small score within a point of each other on agent readiness, 59 (C) and 58.8 (C). Inkling 2 Small leads on risk, agent interface and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-2-small-vs-minimax-m2-5.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "inkling-2-small", "b": "minimax-m2-5"}`. From a terminal: `anchor compare inkling-2-small minimax-m2-5`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json and https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json

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- [MiniMax-M2.5 vs ZAYA1-8B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-zaya1-8b.md)

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