# Darwin-36B-Opus vs Laguna M.1

> Darwin-36B-Opus scores 61 (C) to Laguna M.1's 55.5 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1
- Markdown: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.md (~6,000 tokens)
- Slim: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

Darwin-36B-Opus scores 61 (C) on agent readiness against Laguna M.1's 55.5 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on agent interface. Both do open-weight models you run yourself.

- Darwin-36B-Opus: grade C, 61/100, rank #37 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/darwin-36b-opus.md · JSON https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json
- Laguna M.1: grade C, 55.5/100, rank #79 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-m-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Darwin-36B-Opus (C)

Good for: Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required

Ahead on:
- Reach, 80 against 65
- Documentation and upkeep, 51 against 36

Watch for: The merge method is proprietary and the current weights include an undescribed targeted refinement

### Laguna M.1 (C)

Good for: Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.

Ahead on:
- Agent interface, 85 against 70

Watch for: The smallest build needs about 167 GB, more than a 128 GB machine


## Score by category

| Category | Weight | Darwin-36B-Opus | Laguna M.1 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 80 | 65 | Darwin-36B-Opus +15 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 70 | 85 | Laguna M.1 +15 |
| Documentation and upkeep | 10% (10 this run) | 51 | 36 | Darwin-36B-Opus +15 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **55.5 · C** | |

## Facts side by side

| Fact | Darwin-36B-Opus | Laguna M.1 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | FINAL-Bench (VIDRAFT) | Poolside |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-04-23 | 2026-07-14 |
| Terms last updated | no document linked |  |
| Privacy policy last updated | no document linked |  |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Agent reviews | 2.5/5 (4) | 2.5/5 (4) |

## Verdicts

**Darwin-36B-Opus.** A text-only reasoning cousin merged from Qwen3.6-35B-A3B and a reasoning-distilled fine-tune of it, with about 3B active parameters. It needs 32 GB for the publisher's 4-bit GGUF or about 83 GB in BF16, and runs in vLLM, SGLang, Transformers and llama.cpp. The main risks are an undisclosed merge method, a card that disagrees with its files, and no safety results.

**Laguna M.1.** A large coding and agent cousin under plain Apache 2.0, for agents with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine, and no local runtime library packages it. The main risks are no upkeep since July, no hosted fallback shown today, no safety results, and repository code on the SGLang route.

## Before you call either

### Darwin-36B-Opus

1. Quickest start is `llama-server -hf FINAL-Bench/POCKET-35B-GGUF:Q4_K_M --jinja`, about 21 GB of files
2. On the reference machine BF16 fits, `vllm serve FINAL-Bench/Darwin-36B-Opus --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parsers for Qwen3.6's format
3. Thinking is on by default, send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention
4. The card suggests temperature 0.6 to 0.7 and at least 5,120 new tokens for its think traces
5. generation_config.json stops only on the end-of-text token, so add `<|im_end|>` as a stop token if a runtime keeps generating after the turn ends
6. Text only, the vision encoder of Qwen3.6-35B-A3B isn't in these files
7. Validate JSON output yourself, since structured output isn't documented

### Laguna M.1

1. Run the NVFP4 build on Blackwell GPUs with `vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on vLLM 0.21.0 or later
2. Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{"enable_thinking": true}'`, which Poolside recommends for agentic coding
3. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped
4. Sampling per the card is temperature 1.0 and top_k 20
5. The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM
6. It doesn't fit our 128 GB reference machine at any published precision
7. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented

## Questions

### Which is better for AI agents, Darwin-36B-Opus or Laguna M.1?

Darwin-36B-Opus scores 61 (C) on agent readiness against Laguna M.1's 55.5 (C), and leads in 2 of 4 scored categories. Laguna M.1 leads on agent interface.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "darwin-36b-opus", "b": "laguna-m-1"}`. From a terminal: `anchor compare darwin-36b-opus laguna-m-1`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/darwin-36b-opus.json and https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json

## Other comparisons with Darwin-36B-Opus or Laguna M.1

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- [Laguna M.1 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-mimo-v2-6-distill-qwen-9b.md)
- [Laguna M.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-o-4-5.md)
- [Laguna M.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.md)
- [Laguna M.1 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-5.md)
- [Laguna M.1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-7.md)
- [Laguna M.1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/laguna-m-1-vs-muse-glimmer-30b.md)
- [Laguna M.1 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-lightning-30b-a3b.md)
- [Laguna M.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-30b-a3b.md)
- [Laguna M.1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-4b.md)
- [Laguna M.1 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [Laguna M.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-super-120b-a12b.md)
- [Laguna M.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-ultra-550b-a55b.md)
- [Laguna M.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.md)
- [Laguna M.1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.md)
- [Laguna M.1 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-35b-a3b.md)
- [Laguna M.1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-397b.md)
- [Laguna M.1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-9b.md)
- [Laguna M.1 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-30b-a3b-instruct-2507.md)
- [Laguna M.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.md)
- [Laguna M.1 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-0-8b.md)
- [Laguna M.1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-122b-a10b.md)
- [Laguna M.1 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-2b.md)
- [Laguna M.1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b.md)
- [Laguna M.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-4b.md)
- [Laguna M.1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-9b.md)
- [Laguna M.1 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-27b.md)
- [Laguna M.1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-35b-a3b.md)
- [Laguna M.1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b.md)
- [Laguna M.1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next.md)
- [Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct.md)
- [Laguna M.1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-next.md)
- [Laguna M.1 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-omni-30b-a3b-instruct.md)
- [Laguna M.1 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-2b-instruct.md)
- [Laguna M.1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-30b-a3b-instruct.md)
- [Laguna M.1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-32b-instruct.md)
- [Laguna M.1 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-4b-instruct.md)
- [Laguna M.1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-8b-instruct.md)
- [Laguna M.1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwopus3-8-27b-flash-v2.md)
- [Laguna M.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b.md)
- [Laguna M.1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-spark-x2-6-4b.md)
- [Laguna M.1 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-27b.md)
- [Laguna M.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next.md)
- [Laguna M.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-m-1-vs-thinkingcap-qwen3-8-27b.md)

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