# Cola2 vs Ling-3.0-tiny (slim)

> Ling-3.0-tiny scores 56.2 (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-3-0-tiny.md (~8,450 tokens) · this version ~630 tokens · JSON https://www.anchorterminal.com/compare/cola2-vs-ling-3-0-tiny.json · canonical https://www.anchorterminal.com/compare/cola2-vs-ling-3-0-tiny
- 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-3.0-tiny scores 56.2 (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-3.0-tiny: C 56.2, rank #117 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-0-tiny.min.md
- Cola2, good for Researchers working on latent or diffusion language models who want a checkpoint to study
- Ling-3.0-tiny, good for Agents on a laptop or small GPU that want a fast local model for tool calls and short reasoning, under MIT Ahead on Reach, 95 against 25; Risk, 50 against 40; Agent interface, 60 against 20.

| Category | Cola2 | Ling-3.0-tiny |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 25 | 95 |
| Risk (20%) | 40 | 50 |
| Agent interface (10%) | 20 | 60 |
| Documentation and upkeep (10%) | 58 | 56 |

| Fact (where they differ) | Cola2 | Ling-3.0-tiny |
| --- | --- | --- |
| Vendor | ByteDance (Seed) | inclusionAI (Ant Group) |
| Licence | None stated for the weights (the code is Apache 2.0) | MIT |
| Last release | 2026-11-06 | 2026-08-31 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Reach, Ling-3.0-tiny +70: 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-3.0-tiny 95 (Memory earns the full 30, since inclusionAI's own Q4_K_M GGUF is 4.8 GB, about 6 GB with a fifth added.)
- Agent interface, Ling-3.0-tiny +40: Cola2 20 (Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer.); Ling-3.0-tiny 60 (Chat template 20, a Jinja file in the repository.)
- Risk, Ling-3.0-tiny +10: Cola2 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Ling-3.0-tiny 50 (File safety gets 15, safetensors and GGUF only, but the card's vLLM command runs the repository's config code with --trust-remote-code.)