# Ling-3.1-flash-1019 vs Nanbeige4.3-33B (slim)

> Nanbeige4.3-33B scores 60.8 (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-nanbeige-4-3-33b.md (~9,850 tokens) · this version ~680 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-3-33b.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-nanbeige-4-3-33b
- 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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Nanbeige4.3-33B scores 60.8 (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
- Nanbeige4.3-33B: C 60.8, rank #86 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-3-33b.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
- Nanbeige4.3-33B, good for Agents with a 32 GB GPU (INT4) or more, or the 128 GB reference machine at BF16, that want an Apache-tagged 33B model for long coding and tool loops. Ahead on Reach, 80 against 60; Risk, 60 against 45; Agent interface, 85 against 60.

| Category | Ling-3.1-flash-1019 | Nanbeige4.3-33B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 80 |
| Risk (20%) | 45 | 60 |
| Agent interface (10%) | 60 | 85 |
| Documentation and upkeep (10%) | 56 | 56 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Nanbeige4.3-33B |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | MIT | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| Last release | 2026-11-04 | 2026-10-31 |

Why the edge:
- Agent interface, Nanbeige4.3-33B +25: 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.); Nanbeige4.3-33B 85 (The chat template earns 20, Jinja in tokenizer_config.json.)
- Reach, Nanbeige4.3-33B +20: 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.); Nanbeige4.3-33B 80 (Memory earns 20, since Nanbeige's INT4 build is 22.57 GB, about 27 GB with a fifth added, which fits 32 GB.)
- Risk, Nanbeige4.3-33B +15: 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…); Nanbeige4.3-33B 60 (File safety earns 25, safetensors only and no repository code, so the card's trust_remote_code has nothing to run.)