# Cola2 vs Ling-3.1-flash-1019 (slim)

> Ling-3.1-flash-1019 scores 54.8 (C) to Cola2's 33.9 (F) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/cola2-vs-ling-3-1-flash-1019.md (~9,000 tokens) · this version ~630 tokens · JSON https://www.anchorterminal.com/compare/cola2-vs-ling-3-1-flash-1019.json · canonical https://www.anchorterminal.com/compare/cola2-vs-ling-3-1-flash-1019
- 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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Ling-3.1-flash-1019 scores 54.8 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- Cola2: F 33.9, rank #160 of 160 open-weight models · https://www.anchorterminal.com/tools/cola2.min.md
- 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
- Cola2, good for Researchers working on latent or diffusion language models who want a checkpoint to study
- 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 Ahead on Reach, 60 against 25; Risk, 45 against 40; Agent interface, 60 against 20.

| Category | Cola2 | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 25 | 60 |
| Risk (20%) | 40 | 45 |
| Agent interface (10%) | 20 | 60 |
| Documentation and upkeep (10%) | 58 | 56 |

| Fact (where they differ) | Cola2 | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Vendor | ByteDance (Seed) | inclusionAI (Ant Group) |
| Licence | None stated for the weights (the code is Apache 2.0) | MIT |
| Last release | 2026-11-06 | 2026-11-04 |

Why the edge:
- Agent interface, Ling-3.1-flash-1019 +40: Cola2 20 (Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer.); 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.)
- Reach, Ling-3.1-flash-1019 +35: Cola2 25 (Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 GB.); 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.)
- Risk, Ling-3.1-flash-1019 +5: Cola2 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); 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…)
