# LongCat-2.5 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB (slim)

> NVIDIA Nemotron 3.5 Bolt E4B 4GB scores 61 (C) to LongCat-2.5's 50.5 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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NVIDIA Nemotron 3.5 Bolt E4B 4GB scores 61 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in every scored category. Both do open-weight models you run yourself.

- LongCat-2.5: D 50.5, rank #145 of 160 open-weight models · https://www.anchorterminal.com/tools/longcat-2-5.min.md
- NVIDIA Nemotron 3.5 Bolt E4B 4GB: C 61, rank #49 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-5-bolt-e4b-4gb.min.md
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do
- NVIDIA Nemotron 3.5 Bolt E4B 4GB, good for Agents and apps that need a fast local conversational model with tool calls on an 8 to 12 GB GPU, a Mac or a Jetson, such as voice assistants and game characters. Ahead on Reach, 90 against 35; Risk, 80 against 60; Agent interface, 85 against 75; Documentation and upkeep, 65 against 46.

| Category | LongCat-2.5 | NVIDIA Nemotron 3.5 Bolt E4B 4GB |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 35 | 90 |
| Risk (20%) | 60 | 80 |
| Agent interface (10%) | 75 | 85 |
| Documentation and upkeep (10%) | 46 | 65 |

| Fact (where they differ) | LongCat-2.5 | NVIDIA Nemotron 3.5 Bolt E4B 4GB |
| --- | --- | --- |
| Vendor | Meituan (LongCat) | NVIDIA |
| Licence | MIT | OpenMDW-1.1 |
| Last release | 2026-11-10 | 2026-10-23 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 4/5 (4) |

Why the edge:
- Reach, NVIDIA Nemotron 3.5 Bolt E4B 4GB +55: LongCat-2.5 35 (Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB.); NVIDIA Nemotron 3.5 Bolt E4B 4GB 90 (Memory earns 30, since NVIDIA's Q4_K_M GGUF is 6.18 GB, 7.4 GB with a fifth added.)
- Risk, NVIDIA Nemotron 3.5 Bolt E4B 4GB +20: LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.); NVIDIA Nemotron 3.5 Bolt E4B 4GB 80 (File safety earns 25, safetensors and GGUF only, and the documented routes run no repository code (an undocumented Inference Endpoints handler.py sits in the BF…)
- Documentation and upkeep, NVIDIA Nemotron 3.5 Bolt E4B 4GB +19: LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.); NVIDIA Nemotron 3.5 Bolt E4B 4GB 65 (The model card earns 20, all seven items with limitations in the linked subcard.)
- Agent interface, NVIDIA Nemotron 3.5 Bolt E4B 4GB +10: LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.); NVIDIA Nemotron 3.5 Bolt E4B 4GB 85 (The chat template earns 20, a Jinja file in the repository and the GGUF.)