Head to head · Open-weight models you run yourself · October 2026 research run
Laguna M.1 vs Qwen-AgentWorld-35B-A3B
Laguna M.1 scores 56.7 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 2 of 4 scored categories. Qwen-AgentWorld-35B-A3B leads on documentation and upkeep. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons
Which one, for what
Best 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 55
- Agent interface, 85 against 50
Watch for
The smallest build needs about 167 GB, more than a 128 GB machine
Best for Agent builders who want to train or test an agent against simulated tools, terminals, browsers and phones on a 128 GB machine
Ahead on
- Documentation and upkeep, 41 against 36
Watch for
Not a general assistant, and the card doesn't describe using it to call tools
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Agent interface Laguna M.1 +35
Laguna M.1 85
Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card shows how tools go in and calls come back and names the poolside_v1 parser. Trained tool calling 20, several calls a turn. Structured output 0, not documented. Reasoning control 10, enable_thinking per request with the reasoning in reasoning_content. Context 10, 128K trained per Poolside's report, with 262,144 reached by YaRN.
Qwen-AgentWorld-35B-A3B 50
Chat template 20, chat_template.jinja in the repository, the same as the template in tokenizer_config.json. Tool-calling format 10, only the template says how tools are declared and how calls come back. Trained tool calling 10, the template renders several tool_call blocks in one turn, but the card presents the model as a simulator of what tools and environments return, not as a tool caller. Structured output 0, no JSON or JSON Schema output documented for the model. Reasoning control 0, the card says thinking is on by default and names the qwen3 reasoning parser, but doesn't say how to turn thinking off or budget it. Context 10, 262,144 tokens native per the card and the text config. 20 + 10 + 10 + 0 + 0 + 10 = 50.
Reach Laguna M.1 +15
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. Runtimes 25, released llama.cpp, Ollama (through the llama.cpp release it pins), vLLM, SGLang and Transformers run the laguna architecture. Builds 15, FP8 and NVFP4 from Poolside. Terms 15, Apache 2.0 with nothing binding added. Download 10, nothing is gated. Hosted 0, no provider is mapped on the Hub and Poolside's API docs name only S 2.1.
Qwen-AgentWorld-35B-A3B 55
Memory 10, Alibaba's only build is the BF16 safetensors, 69.32 GB, and 69.32 GB × 1.2 = 83.2 GB, above 64 GB and inside the reference machine's GPU share. Runtimes 20, Four released runtimes run the architecture, vLLM 0.33.0 (Qwen3_5MoeForConditionalGeneration), SGLang 0.5.23, Transformers 5.22.2 (qwen3_5_moe) and llama.cpp b12242 (its Qwen conversion code). Builds 0, Alibaba publishes the BF16 weights only. Terms 15, Apache 2.0, an OSI licence, in the metadata and as a LICENSE file, with no use policy or other terms added. Download 10, the repository isn't gated, so the files download with no account and no terms to accept. Hosted 0, Hugging Face lists no inference provider for the model (an empty provider mapping on 10 November 2026). 10 + 20 + 0 + 15 + 10 + 0 = 55.
Documentation and upkeep Qwen-AgentWorld-35B-A3B +5
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. Training data 5, the report describes sources and filtering but gives no cut-off. Last change 10, 14 July 2026, 113 days ago. Responsiveness 0, the one discussion's only reply is from someone outside the poolside organisation. Version policy 5, a first open release with nothing replaced. File health 5, generation config and template disagree on the thinking default and the FP8 build's Docker files name different image tags.
Qwen-AgentWorld-35B-A3B 41
Model card 11, the card gives intended use (simulating agent environments), architecture, parameters and context length. Training data 5, A general description without a cut-off, the three training stages and a statement that no outputs from external API services were included. Last change 10, the last commit was on 25 June 2026, an update to the card, 138 days before this check, past 90 days and within 180. Responsiveness 0, 10 discussions that aren't pull requests, opened between 24 June and 5 July 2026. Version policy 5, A first release, with nothing replaced. File health 10, Config, both copies of the template and the card agree on the architecture and the context. 11 + 5 + 10 + 0 + 5 + 10 = 41.
Score by category
| Category | Weight this run | Laguna M.1 | Qwen-AgentWorld-35B-A3B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 70 | 55 | Laguna M.1 +15 |
| Risk | 20%20 | 55 | 55 | even |
| Agent interface | 10%10 | 85 | 50 | Laguna M.1 +35 |
| Documentation and upkeep | 10%10 | 36 | 41 | Qwen-AgentWorld-35B-A3B +5 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 56.7/100 | D 52.1/100 |
Facts side by side
| Fact | Laguna M.1 | Qwen-AgentWorld-35B-A3B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Poolside | Alibaba (Qwen team) |
| 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 | 2026-07-14 | 2026-06-25 |
| 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 |
How the scores have moved
Qwen-AgentWorld-35B-A3B
No score change since it was listed.
Verdicts
Laguna M.1
A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.
Qwen-AgentWorld-35B-A3B
A specialist, not a chat model. It plays the environment an agent acts in, across seven domains, so you can train or test an agent without the real thing. Alibaba ships BF16 only, which fits a 128 GB machine, and hasn't answered a discussion on it or changed the files since June.
Before you call either
Laguna M.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 - Thinking is off in the template unless you pass
enable_thinkingtrue or start the server with--default-chat-template-kwargs '{"enable_thinking": true}', which Poolside recommends for agentic coding - Pass earlier reasoning back as
reasoning_contentin the history, since the card says reasoning may stop in later steps if it's dropped - Sampling per the card is temperature 1.0 and top_k 20
- The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM
- It doesn't fit our 128 GB reference machine at any published precision
- Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented
Qwen-AgentWorld-35B-A3B
- Use it as the environment, not the agent. Give it the domain's system prompt from Alibaba's GitHub repository, the history and the agent's action, and it returns the predicted observation
- With vLLM pass
--language-model-only, or startup fails on the missing vision weights - Use temperature 0.6, top_p 0.95 and top_k 20, and allow up to 32,768 output tokens, as the card recommends
- Keep at least 128K of context, since the simulation depends on the history
- Thinking is on by default and comes back through the qwen3 reasoning parser
- A simulated observation is a prediction. Check anything that matters against the real environment
Questions
Which is better for AI agents, Laguna M.1 or Qwen-AgentWorld-35B-A3B?
Laguna M.1 scores 56.7 (C) on agent readiness against Qwen-AgentWorld-35B-A3B's 52.1 (D), and leads in 2 of 4 scored categories. Qwen-AgentWorld-35B-A3B leads on documentation and upkeep.
Other comparisons with Laguna M.1 or Qwen-AgentWorld-35B-A3B
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- Inkling-Small vs Laguna M.1
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- Kolibri-1 vs Laguna M.1
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- Laguna XS 2.1 vs Qwen-AgentWorld-35B-A3B
- LBS-27B vs Qwen-AgentWorld-35B-A3B
- LFM2.5-2.6B vs Qwen-AgentWorld-35B-A3B
- LFM3-1.7B vs Qwen-AgentWorld-35B-A3B
- LFM3-Audio-2B vs Qwen-AgentWorld-35B-A3B
- LFM3-Omni-2B vs Qwen-AgentWorld-35B-A3B
- LFM3-VL-2B vs Qwen-AgentWorld-35B-A3B
- Ling-3.0-tiny vs Qwen-AgentWorld-35B-A3B
- Ling-3.1-flash-1019 vs Qwen-AgentWorld-35B-A3B
- LongCat-2.5 vs Qwen-AgentWorld-35B-A3B
- MiMo-V2.6 Distill Qwen 9B vs Qwen-AgentWorld-35B-A3B
- MiMo-V2.6-Flash-RL vs Qwen-AgentWorld-35B-A3B
- MiniCPM-o 4.5 vs Qwen-AgentWorld-35B-A3B
- MiniCPM-V 4.7 1B vs Qwen-AgentWorld-35B-A3B
- MiniCPM-V 4.7 35B-A3B vs Qwen-AgentWorld-35B-A3B
- MiniCPM5-2B vs Qwen-AgentWorld-35B-A3B
- MiniMax-M2.5 vs Qwen-AgentWorld-35B-A3B
- MiniMax-M2.7 vs Qwen-AgentWorld-35B-A3B
- MiniMax-M3.1-Flash vs Qwen-AgentWorld-35B-A3B
- Mistral Large 4 vs Qwen-AgentWorld-35B-A3B
- Muse Glimmer 30B vs Qwen-AgentWorld-35B-A3B
- Nanbeige4.2-3B vs Qwen-AgentWorld-35B-A3B
- Nanbeige4.3-33B vs Qwen-AgentWorld-35B-A3B
- NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Qwen-AgentWorld-35B-A3B
- Nemotron 3.5 Lightning 30B A3B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Nano 30B A3B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Nano 4B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Super 120B A12B vs Qwen-AgentWorld-35B-A3B
- Nemotron 3 Ultra 550B A55B vs Qwen-AgentWorld-35B-A3B
- North Mini Code 1.0 vs Qwen-AgentWorld-35B-A3B
- occamy-1.0 vs Qwen-AgentWorld-35B-A3B
- Olmo 3 7B Think vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-122B vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-35B-A3B vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-397B vs Qwen-AgentWorld-35B-A3B
- Ornith-1.5-9B vs Qwen-AgentWorld-35B-A3B
- OTel-2.0-LLM-31B-IT vs Qwen-AgentWorld-35B-A3B
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- Qwen-AgentWorld-35B-A3B vs Qwen3.5-0.8B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-122B-A10B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-2B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-397B-A17B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-4B
- Qwen-AgentWorld-35B-A3B vs Qwen3.5-9B
- Qwen-AgentWorld-35B-A3B vs Qwen3.6-27B
- Qwen-AgentWorld-35B-A3B vs Qwen3.6-35B-A3B
- Qwen-AgentWorld-35B-A3B vs Qwen3.8-27B
- Qwen-AgentWorld-35B-A3B vs Qwen3.8-Flash-Next
- Qwen-AgentWorld-35B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-Coder-Next
- Qwen-AgentWorld-35B-A3B vs Qwen3-Omni-30B-A3B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-2B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-30B-A3B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-32B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-4B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwen3-VL-8B-Instruct
- Qwen-AgentWorld-35B-A3B vs Qwopus3.8-27B-Flash-V2
- Qwen-AgentWorld-35B-A3B vs Recursive Flint
- Qwen-AgentWorld-35B-A3B vs Ripple-65B Preview
- Qwen-AgentWorld-35B-A3B vs SenseNova-Loop-9B-Preview
- Qwen-AgentWorld-35B-A3B vs SmolLM3-3B
- Qwen-AgentWorld-35B-A3B vs Spark-X2.6-4B
- Qwen-AgentWorld-35B-A3B vs Step 3.7 Flash
- Qwen-AgentWorld-35B-A3B vs Swift 1.5 Qwen3.8-27B
- Qwen-AgentWorld-35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next
- Qwen-AgentWorld-35B-A3B vs ThinkingCap (Qwen3.8 27B)
- Qwen-AgentWorld-35B-A3B vs Baidu Unlimited-OCR-2
- Qwen-AgentWorld-35B-A3B vs WeVisOne-VL-2B
- Qwen-AgentWorld-35B-A3B vs WeVisOne-VL-4B
- Qwen-AgentWorld-35B-A3B vs ZAYA1-8B
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anchor compare laguna-m-1 qwen-agentworld-35b-a3b(the CLI) - Over MCP
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