# Laguna M.1 vs Ling-3.1-flash-1019 (slim)

> Laguna M.1 scores 56.7 (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.

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- 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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Laguna M.1 scores 56.7 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep. Both do open-weight models you run yourself.

- Laguna M.1: C 56.7, rank #112 of 160 open-weight models · https://www.anchorterminal.com/tools/laguna-m-1.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
- Laguna M.1, good for Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0. Ahead on Reach, 70 against 60; Risk, 55 against 45; Agent interface, 85 against 60.
- 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 Documentation and upkeep, 56 against 36.

| Category | Laguna M.1 | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 60 |
| Risk (20%) | 55 | 45 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 36 | 56 |

| Fact (where they differ) | Laguna M.1 | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Vendor | Poolside | inclusionAI (Ant Group) |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-07-14 | 2026-11-04 |
| Terms last updated | 2026-07-21 | no document linked |
| Privacy policy last updated | 2026-07-21 | no document linked |
| Customer content may train models | yes, with an opt-out | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | yes | not read yet |
| Arbitration or class-action waiver | yes | not read yet |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Agent interface, Laguna M.1 +25: Laguna M.1 85 (Chat template 20, a Jinja file in the repository.); 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.)
- Documentation and upkeep, Ling-3.1-flash-1019 +20: Laguna M.1 36 (Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't.); Ling-3.1-flash-1019 56 (Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claim…)
- Reach, Laguna M.1 +10: Laguna M.1 70 (Memory 5 of 30, the smallest 4-bit build is Poolside's 139.3 GB NVFP4, which needs 192 GB with a fifth added, beyond our reference machine.); 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, Laguna M.1 +10: Laguna M.1 55 (File safety 15 of 25, safetensors only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM instructions use trust_remote…); 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…)