# Inkling 2 Small vs Nemotron 3 Super 120B A12B

> Nemotron 3 Super 120B A12B scores 66.7 (B) 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/inkling-2-small-vs-nemotron-3-super-120b-a12b
- Markdown: https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.md (~9,800 tokens)
- Slim: https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.min.md (~630 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.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 <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. 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

Nemotron 3 Super 120B A12B scores 66.7 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories. 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
- Nemotron 3 Super 120B A12B: grade B, 66.7/100, rank #15 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-super-120b-a12b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-super-120b-a12b.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.

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

### Nemotron 3 Super 120B A12B (B)

Good for: Agents on a 128 GB unified machine or Blackwell GPUs that want a long-context, tool-calling reasoning model with documented training data

Ahead on:
- Reach, 75 against 40
- Agent interface, 90 against 85

Watch for: The card's serving commands pass --trust-remote-code


## Why the edge

### Reach: Nemotron 3 Super 120B A12B +35

- 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.
- Nemotron 3 Super 120B A12B (75): Memory earns 10, because the smallest 4-bit build, NVIDIA's 80.3 GB NVFP4, needs about 96 GB with the fifth added, which fits the reference machine but not 64 GB, and Ollama's 87 GB build lands in the same band. Runtimes earn the full 25 from released Transformers, vLLM, SGLang, llama.cpp and Ollama. Builds earn 15 for NVIDIA's own FP8 and NVFP4. Terms earn 10, since the Nemotron licence is custom even though it's free for commercial use with no threshold or use policy. Download earns 10, with no gate or account. Hosted earns 5, since NVIDIA's own API serves it.

### Agent interface: Nemotron 3 Super 120B A12B +5

- 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.
- Nemotron 3 Super 120B A12B (90): The chat template earns 20, a Jinja file in the repository. The tool-calling format earns 25, since NVIDIA documents the format, names the qwen3_coder parser for three runtimes and shows a tool call in its cookbook. Trained tool calling earns 20, with tool-use reinforcement learning and several calls per turn in the template. Structured output earns 5, claimed from training with no instructions. Reasoning control earns 10, thinking off, low effort or a budget per request with the trace returned as reasoning_content. Context earns 10 for 262,144 tokens in the config and up to 1M per the card.

## Score by category

| Category | Weight | Inkling 2 Small | Nemotron 3 Super 120B A12B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 40 | 75 | Nemotron 3 Super 120B A12B +35 |
| Risk | 20% (20 this run) | 65 | 65 | even |
| Agent interface | 10% (10 this run) | 85 | 90 | Nemotron 3 Super 120B A12B +5 |
| Documentation and upkeep | 10% (10 this run) | 67 | 70 | Nemotron 3 Super 120B A12B +3 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **58.8 · C** | **66.7 · B** | |

## Facts side by side

| Fact | Inkling 2 Small | Nemotron 3 Super 120B A12B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Thinking Machines Lab | NVIDIA |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | NVIDIA Nemotron Open Model License |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-12 | 2026-03-11 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | none | 2.8/5 (4) |

## How the scores have moved

### Inkling 2 Small

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

### Nemotron 3 Super 120B A12B

- +0.5 on 1 November 2026: correction

## 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.

**Nemotron 3 Super 120B A12B.** A long-context agent cousin with trained parallel tool calls, a reasoning switch and a full account of its training data, under a free commercial licence. It needs about 100 GB of GPU memory, a 128 GB unified machine or Blackwell hardware for NVIDIA's NVFP4. The main risks are serving commands that run repository code and no published safety results.

## 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

### Nemotron 3 Super 120B A12B

1. On the reference machine start it with `ollama run nemotron-3-super`, the 87 GB q4_K_M build, the only one that fits (about 104 GB with the margin)
2. Raise the Strix Halo GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is far below what it needs
3. With vLLM serve it with `--reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` (SGLang uses `--reasoning-parser nemotron_3`)
4. Use `temperature=1.0` and `top_p=0.95` for every task, as the card says
5. Thinking is on by default. Pass `enable_thinking: false` or `low_effort: true` in `chat_template_kwargs` for short tasks
6. For coding agents pass `force_nonempty_content: true` in `chat_template_kwargs`, so a cut-off reasoning trace still returns content
7. Raise context past 262,144 only with the card's flags (`VLLM_ALLOW_LONG_MAX_MODEL_LEN=1`, `--max-model-len 1048576`)

## Questions

### Which is better for AI agents, Inkling 2 Small or Nemotron 3 Super 120B A12B?

Nemotron 3 Super 120B A12B scores 66.7 (B) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 3 of 4 scored categories.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-2-small-vs-nemotron-3-super-120b-a12b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "inkling-2-small", "b": "nemotron-3-super-120b-a12b"}`. From a terminal: `anchor compare inkling-2-small nemotron-3-super-120b-a12b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-super-120b-a12b.json

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