# Nemotron 3 Super 120B A12B vs Qwen3.5-2B

> Nemotron 3 Super 120B A12B scores 66.2 (B) to Qwen3.5-2B's 50.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b
- Markdown: https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b.md (~6,450 tokens)
- Slim: https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: 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)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Qwen3.5-2B's 50.5 (D), and leads in 4 of 5 scored categories. Qwen3.5-2B leads on reach. Both do open-weight models you run yourself.

- Nemotron 3 Super 120B A12B: grade B, 66.2/100, rank #15 of 100 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
- Qwen3.5-2B: grade D, 50.5/100, rank #92 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-5-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-5-2b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### 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:
- Capability, 54 against 28
- Risk, 65 against 55
- Agent interface, 90 against 60
- Documentation and upkeep, 65 against 37

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

### Qwen3.5-2B (D)

Good for: Builders who want a cheap local helper or fine-tuning base for narrow tasks and image reading on a laptop, small GPU or CPU

Ahead on:
- Reach, 80 against 75

Watch for: No quantised build from Alibaba, and only one inference provider


## Score by category

| Category | Weight | Nemotron 3 Super 120B A12B | Qwen3.5-2B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 54 | 28 | Nemotron 3 Super 120B A12B +26 |
| Reach | 25% (25 this run) | 75 | 80 | Qwen3.5-2B +5 |
| Risk | 20% (20 this run) | 65 | 55 | Nemotron 3 Super 120B A12B +10 |
| Agent interface | 10% (10 this run) | 90 | 60 | Nemotron 3 Super 120B A12B +30 |
| Documentation and upkeep | 10% (10 this run) | 65 | 37 | Nemotron 3 Super 120B A12B +28 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **66.2 · B** | **50.5 · D** | |

## Facts side by side

| Fact | Nemotron 3 Super 120B A12B | Qwen3.5-2B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | NVIDIA | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | NVIDIA Nemotron Open Model License | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-03-11 | 2026-03-02 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Agent reviews | 2.8/5 (4) | 3/5 (4) |

## Verdicts

**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.

**Qwen3.5-2B.** A small vision-language cousin for prototypes, fine-tuning and light local steps such as tool calls, tagging or reading an image, running in about 2 GB at 4 bits in every major runtime under plain Apache 2.0. Keep thinking off, since the card warns it loops. The main risk is neglect, with no safety results or answers from Alibaba since March.

## Before you call either

### 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`)

### Qwen3.5-2B

1. Smallest start is `ollama run qwen3.5:2b-q4_K_M` (1.9 GB); plain `qwen3.5:2b` pulls the 2.7 GB Q8_0 build
2. Full precision `vllm serve Qwen/Qwen3.5-2B --port 8000 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser qwen3_coder`
3. Thinking is off by default; if you turn it on with `"chat_template_kwargs": {"enable_thinking": true}`, stream and cut off runaway output, since the card warns of thinking loops, and add `--reasoning-parser qwen3` in vLLM or SGLang to split the reasoning out
4. There's no generation_config.json, so pass the card's sampling yourself, for example `temperature=1.0, top_p=1.0, top_k=20, presence_penalty=2.0` for text without thinking
5. Use it for narrow steps or as a fine-tuning base, not as the main agent, as the card itself suggests
6. Validate any JSON it returns, since structured output isn't documented

## Questions

### Which is better for AI agents, Nemotron 3 Super 120B A12B or Qwen3.5-2B?

Nemotron 3 Super 120B A12B scores 66.2 (B) on agent readiness against Qwen3.5-2B's 50.5 (D), and leads in 4 of 5 scored categories. Qwen3.5-2B leads on reach.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-2b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "nemotron-3-super-120b-a12b", "b": "qwen3-5-2b"}`. From a terminal: `anchor compare nemotron-3-super-120b-a12b qwen3-5-2b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/nemotron-3-super-120b-a12b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-5-2b.json

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- [Nemotron 3 Super 120B A12B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-397b-a17b.md)
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- [Nemotron 3 Super 120B A12B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-5-9b.md)
- [Nemotron 3 Super 120B A12B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-27b.md)
- [Nemotron 3 Super 120B A12B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-6-35b-a3b.md)
- [Nemotron 3 Super 120B A12B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-27b.md)
- [Nemotron 3 Super 120B A12B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-8-flash-next.md)
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- [Nemotron 3 Super 120B A12B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-coder-next.md)
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- [Nemotron 3 Super 120B A12B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-vl-4b-instruct.md)
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- [Nemotron 3 Super 120B A12B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwopus3-8-27b-flash-v2.md)
- [Nemotron 3 Super 120B A12B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-smollm3-3b.md)
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- [Nemotron 3 Super 120B A12B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-27b.md)
- [Nemotron 3 Super 120B A12B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-flash-next.md)
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- [Ornith-1.5-35B-A3B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-5-2b.md)
- [Ornith-1.5-397B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-5-2b.md)
- [Ornith-1.5-9B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-5-2b.md)
- [Qwen3-30B-A3B-Instruct-2507 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-5-2b.md)
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- [Qwen3.5-2B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-qwen3-vl-8b-instruct.md)
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- [Qwen3.5-2B vs SmolLM3-3B](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-smollm3-3b.md)
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- [Qwen3.5-2B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Qwen3.5-2B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/qwen3-5-2b-vs-thinkingcap-qwen3-8-27b.md)

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