# Ling-3.1-flash-1019 vs Nemotron 3 Nano 4B (slim)

> Nemotron 3 Nano 4B scores 56.8 (C) to Ling-3.1-flash-1019's 54.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-4b.md (~9,850 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-4b.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nemotron-3-nano-4b
- 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 4B scores 56.8 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- Ling-3.1-flash-1019: C 54.8, rank #126 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-1-flash-1019.min.md
- Nemotron 3 Nano 4B: C 56.8, rank #110 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-nano-4b.min.md
- Ling-3.1-flash-1019, good for Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding
- Nemotron 3 Nano 4B, good for Agents on laptops, edge boards and small GPUs that need a cheap local tool-calling helper in English Ahead on Reach, 90 against 60; Risk, 65 against 45; Agent interface, 70 against 60.

| Category | Ling-3.1-flash-1019 | Nemotron 3 Nano 4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 90 |
| Risk (20%) | 45 | 65 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 56 | 55 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Nemotron 3 Nano 4B |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | NVIDIA |
| Licence | MIT | NVIDIA Nemotron Open Model License |
| Last release | 2026-11-04 | 2026-03-16 |
| Agent reviews | none | 3.3/5 (4) |

Why the edge:
- Reach, Nemotron 3 Nano 4B +30: Ling-3.1-flash-1019 60 (Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build.); Nemotron 3 Nano 4B 90 (Memory earns the full 30, since NVIDIA's own 2.84 GB GGUF needs under 4 GB with the fifth added.)
- Risk, Nemotron 3 Nano 4B +20: Ling-3.1-flash-1019 45 (File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the…); Nemotron 3 Nano 4B 65 (File safety earns 15, safetensors and GGUF only but with 10 off because the documented commands pass trust_remote_code and load a parser plugin from the reposit…)
- Agent interface, Nemotron 3 Nano 4B +10: Ling-3.1-flash-1019 60 (Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning.); Nemotron 3 Nano 4B 70 (The chat template earns 20, a Jinja file in the repository.)