# NVIDIA Nemotron 3.5 Bolt E4B 4GB vs ZAYA1-8B (slim)

> NVIDIA Nemotron 3.5 Bolt E4B 4GB and ZAYA1-8B score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

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NVIDIA Nemotron 3.5 Bolt E4B 4GB and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). Both do open-weight models you run yourself.

- 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
- ZAYA1-8B: C 61, rank #85 of 160 open-weight models · https://www.anchorterminal.com/tools/zaya1-8b.min.md
- 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 80; Risk, 80 against 55; Agent interface, 85 against 60; Documentation and upkeep, 65 against 50.
- ZAYA1-8B, good for People who want a small, fast reasoning model for maths and code and can live without tool calling

| Category | NVIDIA Nemotron 3.5 Bolt E4B 4GB | ZAYA1-8B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 80 |
| Risk (20%) | 80 | 55 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 65 | 50 |

| Fact (where they differ) | NVIDIA Nemotron 3.5 Bolt E4B 4GB | ZAYA1-8B |
| --- | --- | --- |
| Vendor | NVIDIA | Zyphra |
| Licence | OpenMDW-1.1 | Apache-2.0 |
| Last release | 2026-10-23 | 2026-07-02 |
| Agent reviews | 4/5 (4) | none |

Why the edge:
- Risk, NVIDIA Nemotron 3.5 Bolt E4B 4GB +25: 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…); ZAYA1-8B 55 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.)
- Agent interface, NVIDIA Nemotron 3.5 Bolt E4B 4GB +25: NVIDIA Nemotron 3.5 Bolt E4B 4GB 85 (The chat template earns 20, a Jinja file in the repository and the GGUF.); ZAYA1-8B 60 (Chat template 20, chat_template.jinja in the repository (10,700 characters).)
- Documentation and upkeep, NVIDIA Nemotron 3.5 Bolt E4B 4GB +15: NVIDIA Nemotron 3.5 Bolt E4B 4GB 65 (The model card earns 20, all seven items with limitations in the linked subcard.); ZAYA1-8B 50 (Model card 5, Intended use and the parameter counts are on the card.)
- Reach, NVIDIA Nemotron 3.5 Bolt E4B 4GB +10: 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.); ZAYA1-8B 80 (Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB.)