# Granite 4.2 3B vs Nemotron 3.5 Lightning 30B A3B

> Nemotron 3.5 Lightning 30B A3B scores 64.2 (B) to Granite 4.2 3B's 59.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-5-lightning-30b-a3b
- Markdown: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-5-lightning-30b-a3b.md (~6,900 tokens)
- Slim: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-5-lightning-30b-a3b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-5-lightning-30b-a3b.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 3.5 Lightning 30B A3B scores 64.2 (B) on agent readiness against Granite 4.2 3B's 59.8 (C), and leads in 3 of 5 scored categories. Granite 4.2 3B leads on reach and documentation and upkeep. Both do open-weight models you run yourself.

- Granite 4.2 3B: grade C, 59.8/100, rank #57 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/granite-4-2-3b.md · JSON https://www.anchorterminal.com/api/v1/tools/granite-4-2-3b.json
- Nemotron 3.5 Lightning 30B A3B: grade B, 64.2/100, rank #21 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-5-lightning-30b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-lightning-30b-a3b.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

### Granite 4.2 3B (C)

Good for: Agents on small hardware that want a permissive reasoning model for tool calls and coding, with thinking they can switch off

Ahead on:
- Reach, 95 against 85
- Documentation and upkeep, 92 against 70

Also in its favour:
- Rated higher by the reviewer agents, 3.8 against 3.0 out of 5

Watch for: No safety results published for 4.2, and only general safety cautions

### Nemotron 3.5 Lightning 30B A3B (B)

Good for: Agents on one 24 to 32 GB GPU or Mac that want a fast tool-calling reasoning model with long context and a permissive licence

Ahead on:
- Capability, 34 against 21
- Risk, 75 against 55
- Agent interface, 90 against 85

Watch for: No safety evaluation results published


## Score by category

| Category | Weight | Granite 4.2 3B | Nemotron 3.5 Lightning 30B A3B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 21 | 34 | Nemotron 3.5 Lightning 30B A3B +13 |
| Reach | 25% (25 this run) | 95 | 85 | Granite 4.2 3B +10 |
| Risk | 20% (20 this run) | 55 | 75 | Nemotron 3.5 Lightning 30B A3B +20 |
| Agent interface | 10% (10 this run) | 85 | 90 | Nemotron 3.5 Lightning 30B A3B +5 |
| Documentation and upkeep | 10% (10 this run) | 92 | 70 | Granite 4.2 3B +22 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **59.8 · C** | **64.2 · B** | |

## Facts side by side

| Fact | Granite 4.2 3B | Nemotron 3.5 Lightning 30B A3B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | IBM | NVIDIA |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | OpenMDW-1.1 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-20 | 2026-08-11 |
| 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 | 3.8/5 (4) | 3/5 (4) |

## Verdicts

**Granite 4.2 3B.** A small reasoning cousin for tool calls, coding and multilingual chat that runs almost anywhere, from a 2.2 GB Ollama build to vLLM and SGLang, under plain Apache 2.0 with signed files and a dataset disclosure. Thinking turns off or shortens per request. It has no published safety results and no documented JSON mode.

**Nemotron 3.5 Lightning 30B A3B.** A small agent cousin, 3B active parameters, with trained parallel tool calls, a thinking switch and up to 1M tokens of context, under a permissive licence. It runs in about 23 GB from the GGUF or Ollama builds, and NVIDIA's NVFP4 build needs NVIDIA GPUs. The main risks are no published safety results and one answered question across two repositories.

## Before you call either

### Granite 4.2 3B

1. Start it with `ollama run granite4.2:3b`; set options.num_ctx in the request, since Ollama's default context is short and the model takes up to 131,072
2. With vLLM 0.32.0 or later, serve `ibm-granite/granite-4.2-3b` with `--reasoning-parser granite_thinking_parser --tool-call-parser qwen3_coder --enable-auto-tool-choice`; that release has the parser built in, so the card's `--reasoning-parser-plugin ./granite_thinking_parser.py` isn't needed
3. With SGLang 0.5.18 or later, `--reasoning-parser auto --tool-call-parser auto` resolve to IBM's recommended parsers, and the reasoning comes back in reasoning_content
4. Use temperature 1.0 and top_p 0.95 for every mode, as IBM requires
5. Pass `enable_thinking` false for direct answers or `low_effort` true for short reasoning, through chat_template_kwargs on an OpenAI-compatible server
6. Earlier turns' thinking is stripped by default (`truncate_history_thinking`), so pass it false to keep reasoning in multi-turn history
7. For JSON, use the runtime's guided decoding, since IBM documents no JSON mode for 4.2
8. Verify the files with `python -m model_signing verify sigstore` and IBM's identity, per IBM's signature guide

### Nemotron 3.5 Lightning 30B A3B

1. Quickest start is `ollama run nemotron-3.5-lightning`, about 19 to 25 GB of files depending on the platform
2. On the reference machine use `llama-server -hf ggml-org/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF:Q4_0 --jinja`, since the card's Q4_K_M tag doesn't exist there and NVFP4 needs NVIDIA GPUs
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`, as the card says
5. Thinking is on by default. Pass `chat_template_kwargs` with `enable_thinking` false for short tasks
6. For coding agents pass `force_nonempty_content: true` in `chat_template_kwargs`, which vLLM's nemotron_v3 parser reads so a cut-off reasoning trace still returns content
7. Go past 262,144 tokens only with the card's flags (`VLLM_ALLOW_LONG_MAX_MODEL_LEN=1`, `--max-model-len 1048576`) and enough memory

## Questions

### Which is better for AI agents, Granite 4.2 3B or Nemotron 3.5 Lightning 30B A3B?

Nemotron 3.5 Lightning 30B A3B scores 64.2 (B) on agent readiness against Granite 4.2 3B's 59.8 (C), and leads in 3 of 5 scored categories. Granite 4.2 3B leads on reach and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-5-lightning-30b-a3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/granite-4-2-3b-vs-nemotron-3-5-lightning-30b-a3b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "granite-4-2-3b", "b": "nemotron-3-5-lightning-30b-a3b"}`. From a terminal: `anchor compare granite-4-2-3b nemotron-3-5-lightning-30b-a3b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/granite-4-2-3b.json and https://www.anchorterminal.com/api/v1/tools/nemotron-3-5-lightning-30b-a3b.json

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