# Hy-Memory-30B-A3B vs Nemotron 3 Nano 30B A3B (slim)

> Nemotron 3 Nano 30B A3B scores 67.6 (B) to Hy-Memory-30B-A3B's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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Nemotron 3 Nano 30B A3B scores 67.6 (B) on agent readiness against Hy-Memory-30B-A3B's 61 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- Hy-Memory-30B-A3B: C 61, rank #68 of 160 open-weight models · https://www.anchorterminal.com/tools/hy-memory-30b-a3b.min.md
- Nemotron 3 Nano 30B A3B: B 67.6, rank #12 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.min.md
- Hy-Memory-30B-A3B, good for Agents with an external memory framework that want a local model for the write path on a 24 GB card
- Nemotron 3 Nano 30B A3B, good for Agents with a 24 to 32 GB GPU or Mac that want a quick tool-calling and reasoning cousin with very long context. Ahead on Reach, 90 against 85; Agent interface, 90 against 65; Documentation and upkeep, 80 against 68.

| Category | Hy-Memory-30B-A3B | Nemotron 3 Nano 30B A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 90 |
| Risk (20%) | 60 | 60 |
| Agent interface (10%) | 65 | 90 |
| Documentation and upkeep (10%) | 68 | 80 |

| Fact (where they differ) | Hy-Memory-30B-A3B | Nemotron 3 Nano 30B A3B |
| --- | --- | --- |
| Vendor | Tencent (Hy team) | NVIDIA |
| Licence | Apache-2.0 | NVIDIA Nemotron Open Model License (custom, Apache-style, commercial use allowed, not an OSI licence) |
| Last release | 2026-10-16 | 2026-08-24 |
| Terms last updated | no document linked | 2025-12-15 |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Agent reviews | none | 3.3/5 (4) |

Why the edge:
- Agent interface, Nemotron 3 Nano 30B A3B +25: Hy-Memory-30B-A3B 65 (Chat template 20, chat_template.jinja in the repository.); Nemotron 3 Nano 30B A3B 90 (The chat template earns 20 as a Jinja file in the repository.)
- Documentation and upkeep, Nemotron 3 Nano 30B A3B +12: Hy-Memory-30B-A3B 68 (Model card 8, Intended use (the write path of Mem0, MemOS and Hy-Memory), parameters (30B, about 3B active) and languages (English and Chinese, in the metadata)…); Nemotron 3 Nano 30B A3B 80 (The model card earns 20, with all seven items on the card and its subcards.)
- Reach, Nemotron 3 Nano 30B A3B +5: Hy-Memory-30B-A3B 85 (Memory 25, Tencent's own Q4_K_M GGUF is 18.24 GB, and 18.24 GB × 1.2 = 21.9 GB, which fits 24 GB but not 16 GB.); Nemotron 3 Nano 30B A3B 90 (Memory earns 25 because the smallest 4-bit build is Ollama's NVFP4 MLX build at 18 GB, 21.6 GB with the fifth added, and NVIDIA's own NVFP4 build lands in the s…)