# MiniCPM-o 4.5 vs Nemotron 3.5 Lightning 30B A3B

> Nemotron 3.5 Lightning 30B A3B scores 64.2 (B) to MiniCPM-o 4.5's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-5-lightning-30b-a3b
- Markdown: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-nemotron-3-5-lightning-30b-a3b.md (~6,750 tokens)
- Slim: https://www.anchorterminal.com/compare/minicpm-o-4-5-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/minicpm-o-4-5-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 MiniCPM-o 4.5's 61 (C), and leads in 3 of 4 scored categories. MiniCPM-o 4.5 leads on reach. Both do open-weight models you run yourself.

- MiniCPM-o 4.5: grade C, 61/100, rank #42 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm-o-4-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.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
- Best conversational voice-agent APIs: https://www.anchorterminal.com/best/voice-agents/index.md
- All 388 voice agents comparisons: https://www.anchorterminal.com/compare/voice-agents/index.md

## Which one, for what

### MiniCPM-o 4.5 (C)

Good for: Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.

Ahead on:
- Reach, 90 against 85

Watch for: Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni

### 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:
- Risk, 75 against 40
- Agent interface, 90 against 35

Watch for: No safety evaluation results published


## Score by category

| Category | Weight | MiniCPM-o 4.5 | Nemotron 3.5 Lightning 30B A3B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 85 | MiniCPM-o 4.5 +5 |
| Risk | 20% (20 this run) | 40 | 75 | Nemotron 3.5 Lightning 30B A3B +35 |
| Agent interface | 10% (10 this run) | 35 | 90 | Nemotron 3.5 Lightning 30B A3B +55 |
| Documentation and upkeep | 10% (10 this run) | 66 | 70 | Nemotron 3.5 Lightning 30B A3B +4 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **64.2 · B** | |

## Facts side by side

| Fact | MiniCPM-o 4.5 | Nemotron 3.5 Lightning 30B A3B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenBMB | NVIDIA |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards | OpenMDW-1.1 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-16 | 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 | 2.8/5 (4) | 3/5 (4) |

## Verdicts

**MiniCPM-o 4.5.** A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and no safety results.

**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

### MiniCPM-o 4.5

1. Quickest start for text and images is `ollama run openbmb/minicpm-o4.5`, about 6 GB
2. With vLLM 0.16.0 or later pass `--trust-remote-code`, and send `stop_token_ids` [151643, 151645] as OpenBMB's guide does
3. vLLM, llama.cpp and Ollama return text only; for speech out use the card's Transformers 4.51.0 code or OpenBMB's llama.cpp-omni
4. In llama.cpp pass both the language GGUF and MiniCPM-o-4_5-vision-F16.gguf with `--mmproj`, and use `--jinja --reasoning-budget 0` to turn thinking off
5. Keep prompts within 40,960 tokens
6. Don't rely on tool calls or JSON output, neither is documented; validate any you get

### 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, MiniCPM-o 4.5 or Nemotron 3.5 Lightning 30B A3B?

Nemotron 3.5 Lightning 30B A3B scores 64.2 (B) on agent readiness against MiniCPM-o 4.5's 61 (C), and leads in 3 of 4 scored categories. MiniCPM-o 4.5 leads on reach.


## For agents

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

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