# Cola2 vs Laguna S 2.1 (slim)

> Laguna S 2.1 scores 61 (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-laguna-s-2-1.md (~8,850 tokens) · this version ~880 tokens · JSON https://www.anchorterminal.com/compare/cola2-vs-laguna-s-2-1.json · canonical https://www.anchorterminal.com/compare/cola2-vs-laguna-s-2-1
- 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)

Laguna S 2.1 scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep. 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
- Laguna S 2.1: C 61, rank #45 of 160 open-weight models · https://www.anchorterminal.com/tools/laguna-s-2-1.min.md
- Cola2, good for Researchers working on latent or diffusion language models who want a checkpoint to study Ahead on Documentation and upkeep, 58 against 41.
- Laguna S 2.1, good for Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context. Ahead on Reach, 75 against 25; Risk, 55 against 40; Agent interface, 85 against 20.

| Category | Cola2 | Laguna S 2.1 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 25 | 75 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 20 | 85 |
| Documentation and upkeep (10%) | 58 | 41 |

| Fact (where they differ) | Cola2 | Laguna S 2.1 |
| --- | --- | --- |
| Vendor | ByteDance (Seed) | Poolside |
| Licence | None stated for the weights (the code is Apache 2.0) | OpenMDW-1.1 |
| Last release | 2026-11-06 | 2026-08-19 |
| Terms last updated | no document linked | 2026-07-21 |
| Privacy policy last updated | no document linked | 2026-07-21 |
| Customer content may train models | not read yet | yes, with an opt-out |
| 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 | yes |
| Arbitration or class-action waiver | not read yet | yes |
| Agent reviews | none | 2.3/5 (4) |

Why the edge:
- Agent interface, Laguna S 2.1 +65: Cola2 20 (Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer.); Laguna S 2.1 85 (Chat template 20, a Jinja file in the repository.)
- Reach, Laguna S 2.1 +50: 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.); Laguna S 2.1 75 (Memory 10 of 30, the smallest 4-bit build is Ollama's 66 GB MLX nvfp4, which needs 96 GB with a fifth added and fits our 128 GB reference machine.)
- Documentation and upkeep, Cola2 +17: Cola2 58 (Model card 8, Intended use and limitations (the out-of-scope list, and the unconverged latent model) and the architecture are on the card and the GitHub model c…); Laguna S 2.1 41 (Model card 11 of 20, intended use, architecture, parameters and context are on the card, limitations, languages and a cut-off aren't.)
- Risk, Laguna S 2.1 +15: Cola2 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Laguna S 2.1 55 (File safety 15 of 25, safetensors and GGUF only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM commands use trust_r…)