{ "data": { "a": { "slug": "laguna-xs-2-1", "name": "Laguna XS 2.1", "vendor": "Poolside", "vendorUrl": "https://poolside.ai", "kind": "weights", "category": "open-weights", "summary": "Laguna XS 2.1 is Poolside's open-weight Mixture-of-Experts coding model, 33B total and 3B active parameters, with switchable reasoning and a 262,144-token context, published on Hugging Face under OpenMDW-1.1.", "url": "https://www.anchorterminal.com/tools/laguna-xs-2-1", "markdownUrl": "https://www.anchorterminal.com/tools/laguna-xs-2-1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-xs-2-1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json", "repo": "https://huggingface.co/poolside/Laguna-XS-2.1", "license": "OpenMDW-1.1", "transports": [], "packages": [ { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-FP8" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-INT4" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-NVFP4" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-NVFP4-mlx" }, { "registry": "huggingface", "name": "poolside/Laguna-XS-2.1-GGUF" }, { "registry": "ollama", "name": "laguna-xs-2.1" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for the main repository and every build, although the card's metadata carries an unused gate description pointing to Poolside's privacy policy (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under OpenMDW-1.1. Running it yourself costs the hardware, 66.9 GB for the BF16 files and 20.3 GB for Poolside's Q4_K_M GGUF, which is also Ollama's default build. Poolside serves it on OpenRouter with a free and a paid endpoint, both marked to expire on 31 October 2026 (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://huggingface.co/poolside/Laguna-XS-2.1", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "coding", "reasoning", "tool-calling", "openmdw-1.1", "safetensors", "gguf", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-08-19", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 33, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 85, "reach": 85, "risk": 55, "upkeep": 46 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.", "bestFor": "Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.", "strengths": [ "Released support in llama.cpp, Ollama, vLLM, SGLang, Transformers and mlx-lm", "Poolside's own Q4_K_M, FP8, INT4, NVFP4 and MLX builds, the Q4_K_M at 20.3 GB", "Permissive OpenMDW-1.1 licence with no gate, account or use policy", "Tool calling and the poolside_v1 parser documented on the card, several calls a turn", "Thinking on or off per request, with the reasoning returned in reasoning_content" ], "weaknesses": [ "No reply from Poolside to any discussion, including reports about the tokenizer and remote code", "No safety results and only general cautions for agent use", "The SGLang and TensorRT-LLM commands run the repository's Python with trust_remote_code", "The template defaults thinking off while generation_config.json turns it on", "No structured output documentation, and no limitations, languages or cut-off on the card" ], "agentNotes": [ "Quickest start is `ollama run laguna-xs-2.1`, 20 GB of files, the same Q4_K_M as Poolside's GGUF", "On our reference machine use `llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072`, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB)", "With vLLM use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on a build with vllm-project/vllm#47311, or `--tool-call-parser glm47` on older builds", "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", "Pass earlier reasoning back as `reasoning_content` in 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 card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships", "Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 85, "reach": 85, "risk": 55, "upkeep": 46 }, "provenanceScore": 71, "checked": { "categories": { "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run laguna-xs-2.1\n# or, with vLLM 0.21.0 or later (a build with vllm-project/vllm#47311):\nvllm serve poolside/Laguna-XS-2.1 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 \\\n --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"laguna-xs-2.1\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/laguna-xs-2-1" }, "sameCompany": [ "laguna-m-1", "laguna-s-2-1" ], "weights": { "trainedBy": "Poolside", "params": "33.4B total, 3B active", "context": 262144, "goodFor": "Agentic coding and long-horizon terminal work on one GPU or a 32 GB machine, with tool calling and reasoning that turns on or off per request.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "Laguna-XS-2.1-INT4", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-INT4", "who": "publisher", "precision": "int4 (w4a16)", "sizeGB": 23.9, "memoryGB": 32, "format": "safetensors" }, { "name": "Laguna-XS-2.1-NVFP4", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 21.6, "memoryGB": 32, "format": "safetensors", "note": "For NVIDIA Blackwell GPUs" }, { "name": "Laguna-XS-2.1-NVFP4-mlx", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-NVFP4-mlx", "who": "publisher", "precision": "nvfp4", "sizeGB": 21.6, "memoryGB": 32, "format": "mlx", "runsOn": [ "MLX" ] }, { "name": "Laguna-XS-2.1-GGUF Q4_K_M", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 20.3, "memoryGB": 32, "format": "gguf", "runsOn": [ "llama.cpp", "Ollama" ], "note": "Laguna-XS-2.1-Q4_K_M.gguf, 20,274,300,032 bytes. The repository also holds a BF16 GGUF of 66.9 GB (96 GB of memory)" }, { "name": "ollama laguna-xs-2.1:latest", "url": "https://ollama.com/library/laguna-xs-2.1:latest", "who": "ollama", "precision": "q4_k_m", "sizeGB": 20.3, "memoryGB": 32, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Ollama shows 20 GB. Its model blob (sha256 1ac7079101fc) is Poolside's Q4_K_M GGUF, so the exact size is Poolside's. The library also has q8_0 (36 GB), bf16 (67 GB) and MLX tags (nvfp4 shown as 20 GB, exact size unpublished, mxfp8 40 GB, mlx-bf16 68 GB). The card warns that ollama run may return empty output on Apple Silicon until llama.cpp#25389 ships" }, { "name": "Laguna-XS-2.1-FP8", "url": "https://huggingface.co/poolside/Laguna-XS-2.1-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 35.3, "memoryGB": 48, "format": "safetensors" }, { "name": "Laguna-XS-2.1", "url": "https://huggingface.co/poolside/Laguna-XS-2.1", "who": "publisher", "precision": "bf16", "sizeGB": 66.9, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ] } ], "run": "llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072 --port 8000", "runBuild": "Laguna-XS-2.1-GGUF Q4_K_M", "checked": "2026-10-21", "minMemoryGB": 32 }, "family": { "lab": "Poolside", "family": "Laguna 2 (XS.2, XS 2.1, S 2.1)", "url": "https://www.anchorterminal.com/open-weights/#poolside", "others": [ { "name": "Laguna-S-2.1", "url": "https://huggingface.co/poolside/Laguna-S-2.1", "params": "117.56B (Hub safetensors count; the name gives only the size class S)", "listing": "https://www.anchorterminal.com/tools/laguna-s-2-1" }, { "name": "Laguna-S-2.1-base", "url": "https://huggingface.co/poolside/Laguna-S-2.1-base", "params": "not stated (no safetensors count on the Hub; the instruct model is 117.56B)" }, { "name": "Laguna-XS.2", "url": "https://huggingface.co/poolside/Laguna-XS.2", "params": "33.44B (Hub safetensors count; the name gives only the size class XS)" } ], "unrestrictedCopies": 1 }, "area": "models", "provenance": { "legalEntity": "Poolside, Inc. (named in Poolside's Terms of Use)", "domain": "poolside.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://poolside.ai/legal/eula", "privacy": "https://poolside.ai/legal/privacy", "statusPage": "", "changelog": "https://docs.poolside.ai/release-notes/models", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "The Hugging Face organisation poolside is verified, and Poolside's blog post for this release links its collection there.", "Nothing is hosted for this listing, so the OpenMDW-1.1 licence stands in for terms of service and no privacy policy is scored.", "Poolside's docs keep dated model release notes. The June 2026 entry calls XS 2.1 an incremental update to Laguna XS.2.", "security.txt is PGP-signed, names a security contact at poolside.ai and expires on 1 April 2028. The domain's registration date wasn't checked." ], "score": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-xs-2-1.json" }, "answer": "Laguna XS 2.1 and ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on documentation and upkeep.", "b": { "slug": "thinkingcap-qwen3-8-27b", "name": "ThinkingCap (Qwen3.8 27B)", "vendor": "BottleCap AI", "vendorUrl": "https://bottlecapai.com", "kind": "weights", "category": "open-weights", "summary": "ThinkingCap-Qwen3.8-27B is BottleCap AI's fine-tune of Alibaba's Qwen3.8-27B that shortens its reasoning traces, a 27B dense vision-language model on Hugging Face under PolyForm Small Business 1.0.0, with a gated main repository.", "url": "https://www.anchorterminal.com/tools/thinkingcap-qwen3-8-27b", "markdownUrl": "https://www.anchorterminal.com/tools/thinkingcap-qwen3-8-27b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/thinkingcap-qwen3-8-27b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/thinkingcap-qwen3-8-27b.json", "repo": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B", "license": "PolyForm-Small-Business-1.0.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "bottlecapai/ThinkingCap-Qwen3.8-27B" }, { "registry": "huggingface", "name": "bottlecapai/ThinkingCap-Qwen3.8-27B-FP8" }, { "registry": "huggingface", "name": "bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF" }, { "registry": "huggingface", "name": "bottlecapai/ThinkingCap-Qwen3.8-27B-NVFP4" }, { "registry": "huggingface", "name": "bottlecapai/ThinkingCap-Qwen3.8-27B-NVFP4A4-AWQ" }, { "registry": "huggingface", "name": "bottlecapai/ThinkingCap-Qwen3.8-27B-MLX-4bit-DWQ" }, { "registry": "huggingface", "name": "bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF-RCO-4.2bpw" } ], "auth": "none", "authNotes": "The BF16 and FP8 repositories are gated (gated auto). A Hugging Face account must accept the card's conditions and give a name, a company and an email before the files open, with automatic approval. The GGUF, NVFP4, NVFP4A4-AWQ, MLX and RCO GGUF repositories were not gated on 21 October 2026, though their cards carry the same request form in their metadata (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free for personal non-commercial use and for companies with fewer than 100 people and under 1,000,000 USD (2019, inflation-adjusted) revenue, under PolyForm Small Business 1.0.0 plus BottleCap's personal-use grant. Larger organisations need a separate commercial licence from BottleCap AI. Running it costs the hardware, 55.6 GB for BF16 and 15.5 GB for the smallest 4-bit GGUF (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "multimodal", "reasoning", "tool-calling", "derivative", "gated", "source-available", "safetensors", "gguf", "fp8", "nvfp4", "mlx", "self-hosted" ], "lastRelease": "2026-10-06", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1197, "categoryRank": 43, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 70, "reach": 75, "risk": 45, "upkeep": 53 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A Qwen3.8-27B with shorter reasoning, for agent work where thinking tokens cost time, and BottleCap's 4-bit GGUF runs in about 19 GB. The main limits are the licence, which needs a paid licence above 100 people or 1,000,000 USD revenue, a gated main repository, and no safety results or training-data description.", "bestFor": "Small teams and individuals running Qwen3.8-27B for agent or reasoning work who want shorter thinking traces on one 24 GB GPU or Mac.", "strengths": [ "Same architecture and template as Qwen3.8-27B, so released vLLM, SGLang, Transformers and llama.cpp run it", "BottleCap publishes FP8, NVFP4, MLX and GGUF builds, the IQ4_XS needing about 19 GB", "Per-request reasoning effort, several tool calls a turn and 262,144 tokens of context", "The card documents its own evaluation method with seeds, intervals and paired quantisation checks", "Safetensors only, in a verified organisation" ], "weaknesses": [ "PolyForm Small Business licence, free commercially only below 100 people and 1,000,000 USD (2019) revenue", "The BF16 and FP8 repositories are gated behind contact details", "No safety results, agent guidance, security contact or training-data description", "No hosted API or inference provider", "Every accuracy and token-saving figure comes from BottleCap's own harness" ], "agentNotes": [ "Check the licence first, an organisation with 100 or more people or 1,000,000 USD (2019) revenue needs a commercial licence from BottleCap", "For files without the gate use `llama-server -hf bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF:Q4_K_M --jinja`, about 17.4 GB", "On vLLM use `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_xml`, and on SGLang `--tool-call-parser qwen3_coder`", "Set `reasoning_effort` (xhigh, medium or low) in chat_template_kwargs, any other value makes the template raise an error", "Keep the base's sampling (temperature 1.0, top_p 0.95, top_k 20), the GGUF card says greedy decoding can loop", "The GGUFs carry an MTP head, and llama.cpp builds without MTP support for this architecture may refuse to load them with a missing blk.64 tensor" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 70, "reach": 75, "risk": 45, "upkeep": 53 }, "provenanceScore": 47, "checked": { "categories": { "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "llama-server -hf bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF:Q4_K_M --jinja\n# or the gated BF16 weights, after accepting the card's conditions:\nvllm serve bottlecapai/ThinkingCap-Qwen3.8-27B --reasoning-parser qwen3 \\\n --enable-auto-tool-choice --tool-call-parser qwen3_xml", "http": "curl http://localhost:8080/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/thinkingcap-qwen3-8-27b" }, "weights": { "trainedBy": "BottleCap AI", "builtOn": "Qwen/Qwen3.8-27B (Apache 2.0), declared in the card's metadata (base_model, base_model_relation finetune) and in NOTICE as the base checkpoint. ThinkingCap's own weights are under PolyForm Small Business 1.0.0 with a personal-use grant, and NOTICE keeps Apache 2.0 for the upstream Qwen materials", "params": "27B", "context": 262144, "goodFor": "Qwen3.8-27B with shorter reasoning traces, for agent and reasoning work where thinking tokens cost time, with images and video in.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "ThinkingCap-Qwen3.8-27B-IQ4_XS", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF/blob/main/ThinkingCap-Qwen3.8-27B-IQ4_XS.gguf", "who": "publisher", "precision": "iq4_xs", "sizeGB": 15.5, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "Not gated. Image input needs the 0.93 GB mmproj file from the same repository" }, { "name": "ThinkingCap-Qwen3.8-27B-Q4_K_M", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF/blob/main/ThinkingCap-Qwen3.8-27B-Q4_K_M.gguf", "who": "publisher", "precision": "q4_k_m", "sizeGB": 17.4, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] }, { "name": "ThinkingCap-Qwen3.8-27B-RCO-4.2bpw", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF-RCO-4.2bpw", "who": "publisher", "precision": "mixed-4.2bpw", "sizeGB": 14.3, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "Not gated. Mixed precision averaging 4.19 bits per weight, with the feed-forward weights at 3.8 to 3.9 bits, so it doesn't count as a 4-bit build for the memory line" }, { "name": "ThinkingCap-Qwen3.8-27B-NVFP4", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 20.6, "memoryGB": 32, "format": "safetensors", "note": "Not gated. Weight-only NVFP4 for vLLM on Hopper (Marlin) and Blackwell" }, { "name": "ThinkingCap-Qwen3.8-27B-NVFP4A4-AWQ", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-NVFP4A4-AWQ", "who": "publisher", "precision": "nvfp4", "sizeGB": 23.4, "memoryGB": 32, "format": "safetensors", "note": "Not gated. NVFP4 weights and activations, Blackwell only" }, { "name": "ThinkingCap-Qwen3.8-27B-MLX-4bit-DWQ", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-MLX-4bit-DWQ", "who": "publisher", "precision": "mlx-4bit", "sizeGB": 22.8, "memoryGB": 32, "format": "mlx", "runsOn": [ "mlx-vlm" ], "note": "Not gated. Mixed 4 and 8-bit DWQ with the vision tower and MTP head (22.0 GB without the MTP files). The card says to use mlx-vlm or oMLX" }, { "name": "ThinkingCap-Qwen3.8-27B-Q6_K", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF/blob/main/ThinkingCap-Qwen3.8-27B-Q6_K.gguf", "who": "publisher", "precision": "q6_k", "sizeGB": 23.9, "memoryGB": 32, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] }, { "name": "ThinkingCap-Qwen3.8-27B-FP8", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 31.2, "memoryGB": 48, "format": "safetensors", "note": "Gated like the main repository. Block-wise FP8 for vLLM on Hopper and Blackwell, per the card" }, { "name": "ThinkingCap-Qwen3.8-27B-Q8_0", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF/blob/main/ThinkingCap-Qwen3.8-27B-Q8_0.gguf", "who": "publisher", "precision": "q8_0", "sizeGB": 29, "memoryGB": 48, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] }, { "name": "ThinkingCap-Qwen3.8-27B", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B", "who": "publisher", "precision": "bf16", "sizeGB": 55.6, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)", "Transformers" ], "note": "Gated (auto approval after accepting the card's conditions)" }, { "name": "ThinkingCap-Qwen3.8-27B-f16", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF/blob/main/ThinkingCap-Qwen3.8-27B-f16.gguf", "who": "publisher", "precision": "f16", "sizeGB": 54.7, "memoryGB": 96, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] } ], "run": "llama-server -hf bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF:Q4_K_M --jinja", "runBuild": "ThinkingCap-Qwen3.8-27B-Q4_K_M", "checked": "2026-10-21", "minMemoryGB": 24 }, "family": { "lab": "BottleCap AI (bottlecapai)", "family": "ThinkingCap", "url": "https://www.anchorterminal.com/open-weights/#bottlecap", "others": [ { "name": "ThinkingCap-Qwen3.6-27B", "url": "https://huggingface.co/bottlecapai/ThinkingCap-Qwen3.6-27B", "params": "27B (27,356,728,560 by the Hub's safetensors count)" } ], "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "BottleCap AI (named in the licence's copyright line)", "domain": "bottlecapai.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://bottlecapai.com/privacy-policy/", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The Hugging Face organisation bottlecapai is verified (team plan, 15 members). BottleCap's blog post for this model links the repository.", "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored.", "bottlecapai.com/.well-known/security.txt returns 404. A trust centre at trust.mycroft.io/bottlecap-ai lists SOC 2 and policies behind a request form, with no route for reporting a flaw in the model.", "unchecked: the domain's registration date, and the main repository's commit history, which is behind the gate." ], "score": 47 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/thinkingcap-qwen3-8-27b.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Poolside", "b": "BottleCap AI", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "OpenMDW-1.1", "b": "PolyForm-Small-Business-1.0.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-08-19", "b": "2026-10-06", "name": "Last release" }, { "a": "", "b": "no document linked", "name": "Terms last updated" }, { "a": "", "b": "", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2.8/5 (4)", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Laguna XS 2.1 and ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on documentation and upkeep.", "question": "Which is better for AI agents, Laguna XS 2.1 or ThinkingCap (Qwen3.8 27B)?" } ], "goodFor": [ { "aheadOn": [ "Reach, 85 against 75", "Risk, 55 against 45", "Agent interface, 85 against 70" ], "also": null, "goodFor": "Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.", "slug": "laguna-xs-2-1", "watchFor": "No reply from Poolside to any discussion, including reports about the tokenizer and remote code" }, { "aheadOn": [ "Documentation and upkeep, 53 against 46" ], "also": null, "goodFor": "Small teams and individuals running Qwen3.8-27B for agent or reasoning work who want shorter thinking traces on one 24 GB GPU or Mac.", "slug": "thinkingcap-qwen3-8-27b", "watchFor": "PolyForm Small Business licence, free commercially only below 100 people and 1,000,000 USD (2019) revenue" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-2-1.json", "title": "Agents-A1-4B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-thinkingcap-qwen3-8-27b.json", "title": "Agents-A1-4B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-2-1.json", "title": "Apertus v1.5 8B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-thinkingcap-qwen3-8-27b.json", "title": "Apertus v1.5 8B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1.json", "title": "Apodex-1.1-mini vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-thinkingcap-qwen3-8-27b.json", "title": "Apodex-1.1-mini vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-xs-2-1.json", "title": "BigBang-v1 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-thinkingcap-qwen3-8-27b.json", "title": "BigBang-v1 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1.json", "title": "Cosmos-Reason2-2B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-thinkingcap-qwen3-8-27b.json", "title": "Cosmos-Reason2-2B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-2-1.json", "title": "Darwin-36B-Opus vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-thinkingcap-qwen3-8-27b.json", "title": "Darwin-36B-Opus vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1.json", "title": "DeepSeek-V3.2 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-thinkingcap-qwen3-8-27b.json", "title": "DeepSeek-V3.2 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-xs-2-1.json", "title": "DeepSeek V4.1 Flash vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-thinkingcap-qwen3-8-27b.json", "title": "DeepSeek V4.1 Flash vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-xs-2-1.json", "title": "DeepSeek-V4-Flash-0731 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-thinkingcap-qwen3-8-27b.json", "title": "DeepSeek-V4-Flash-0731 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-xs-2-1.json", "title": "DiffusionGemma 26B A4B IT vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-thinkingcap-qwen3-8-27b.json", "title": "DiffusionGemma 26B A4B IT vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-xs-2-1.json", "title": "Gemma 4 12B IT vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-thinkingcap-qwen3-8-27b.json", "title": "Gemma 4 12B IT vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-xs-2-1.json", "title": "Gemma 4 26B A4B IT vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-thinkingcap-qwen3-8-27b.json", "title": "Gemma 4 26B A4B IT vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-xs-2-1.json", "title": "Gemma 4 31B IT vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-thinkingcap-qwen3-8-27b.json", "title": "Gemma 4 31B IT vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-xs-2-1.json", "title": "Gemma 4 E2B IT vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-thinkingcap-qwen3-8-27b.json", "title": "Gemma 4 E2B IT vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-xs-2-1.json", "title": "Gemma 4 E4B IT vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-thinkingcap-qwen3-8-27b.json", "title": "Gemma 4 E4B IT vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-xs-2-1.json", "title": "GLM-4.5-Air vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-thinkingcap-qwen3-8-27b.json", "title": "GLM-4.5-Air vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-xs-2-1.json", "title": "GLM-4.7-Flash vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-thinkingcap-qwen3-8-27b.json", "title": "GLM-4.7-Flash vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-xs-2-1.json", "title": "GLM-5.3-Flash vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-thinkingcap-qwen3-8-27b.json", "title": "GLM-5.3-Flash vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1.json", "title": "GLM-5.3 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-thinkingcap-qwen3-8-27b.json", "title": "GLM-5.3 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-xs-2-1.json", "title": "gpt-oss-120b vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-thinkingcap-qwen3-8-27b.json", "title": "gpt-oss-120b vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-xs-2-1.json", "title": "gpt-oss-20b vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-thinkingcap-qwen3-8-27b.json", "title": "gpt-oss-20b vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-xs-2-1.json", "title": "Granite 4.2 3B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-thinkingcap-qwen3-8-27b.json", "title": "Granite 4.2 3B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-laguna-xs-2-1.json", "title": "Hy3 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/hy3-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-thinkingcap-qwen3-8-27b.json", "title": "Hy3 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/hy3-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-xs-2-1.json", "title": "Inkling-Small vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-thinkingcap-qwen3-8-27b.json", "title": "Inkling-Small vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-2-1.json", "title": "Inkling vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-thinkingcap-qwen3-8-27b.json", "title": "Inkling vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/inkling-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-xs-2-1.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-thinkingcap-qwen3-8-27b.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-xs-2-1.json", "title": "Kimi K3 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-thinkingcap-qwen3-8-27b.json", "title": "Kimi K3 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-xs-2-1.json", "title": "Kolibri-1 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-thinkingcap-qwen3-8-27b.json", "title": "Kolibri-1 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-xs-2-1.json", "title": "Laguna M.1 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-thinkingcap-qwen3-8-27b.json", "title": "Laguna M.1 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-laguna-xs-2-1.json", "title": "Laguna S 2.1 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-laguna-xs-2-1" }, { "json": 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"json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-4b-instruct-2507.json", "title": "Laguna XS 2.1 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-0-8b.json", "title": "Laguna XS 2.1 vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-122b-a10b.json", "title": "Laguna XS 2.1 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-2b.json", "title": "Laguna XS 2.1 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-5-397b-a17b.json", "title": "Laguna XS 2.1 vs 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"https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-4B-Instruct-2507 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.5-0.8B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.5-122B-A10B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.5-2B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.5-397B-A17B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.5-4B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.5-9B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.6-27B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.6-35B-A3B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.8-27B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3.8-Flash-Next vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-Coder-Next vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-Omni-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-VL-2B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-VL-30B-A3B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-VL-32B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-VL-4B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwen3-VL-8B-Instruct vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-thinkingcap-qwen3-8-27b.json", "title": "Qwopus3.8-27B-Flash-V2 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-thinkingcap-qwen3-8-27b.json", "title": "SmolLM3-3B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-thinkingcap-qwen3-8-27b.json", "title": "Spark-X2.6-4B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-thinkingcap-qwen3-8-27b.json", "title": "Swift 1.5 Qwen3.8-27B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b.json", "title": "Swift 1.5 Qwen3.8-Flash-Next vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 10, "edge": "laguna-xs-2-1", "key": "reach", "laguna-xs-2-1": 85, "name": "Reach", "thinkingcap-qwen3-8-27b": 75, "weight": 25 }, { "by": 10, "edge": "laguna-xs-2-1", "key": "risk", "laguna-xs-2-1": 55, "name": "Risk", "thinkingcap-qwen3-8-27b": 45, "weight": 20 }, { "by": 15, "edge": "laguna-xs-2-1", "key": "interface", "laguna-xs-2-1": 85, "name": "Agent interface", "thinkingcap-qwen3-8-27b": 70, "weight": 10 }, { "by": 7, "edge": "thinkingcap-qwen3-8-27b", "key": "upkeep", "laguna-xs-2-1": 46, "name": "Documentation and upkeep", "thinkingcap-qwen3-8-27b": 53, "weight": 10 } ], "summary": "Laguna XS 2.1 and ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on documentation and upkeep. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "laguna-xs-2-1": "A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.", "thinkingcap-qwen3-8-27b": "A Qwen3.8-27B with shorter reasoning, for agent work where thinking tokens cost time, and BottleCap's 4-bit GGUF runs in about 19 GB. The main limits are the licence, which needs a paid licence above 100 people or 1,000,000 USD revenue, a gated main repository, and no safety results or training-data description." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b", "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.min.md" }, "markdown": "Laguna XS 2.1 and ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on documentation and upkeep. Both do open-weight models you run yourself.\n\n- Laguna XS 2.1: grade C, 61/100, rank #40 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-xs-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json\n- ThinkingCap (Qwen3.8 27B): grade C, 61/100, rank #50 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/thinkingcap-qwen3-8-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/thinkingcap-qwen3-8-27b.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Laguna XS 2.1 (C)\n\nGood for: Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.\n\nAhead on:\n- Reach, 85 against 75\n- Risk, 55 against 45\n- Agent interface, 85 against 70\n\nWatch for: No reply from Poolside to any discussion, including reports about the tokenizer and remote code\n\n### ThinkingCap (Qwen3.8 27B) (C)\n\nGood for: Small teams and individuals running Qwen3.8-27B for agent or reasoning work who want shorter thinking traces on one 24 GB GPU or Mac.\n\nAhead on:\n- Documentation and upkeep, 53 against 46\n\nWatch for: PolyForm Small Business licence, free commercially only below 100 people and 1,000,000 USD (2019) revenue\n\n\n## Score by category\n\n| Category | Weight | Laguna XS 2.1 | ThinkingCap (Qwen3.8 27B) | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 85 | 75 | Laguna XS 2.1 +10 |\n| Risk | 20% (20 this run) | 55 | 45 | Laguna XS 2.1 +10 |\n| Agent interface | 10% (10 this run) | 85 | 70 | Laguna XS 2.1 +15 |\n| Documentation and upkeep | 10% (10 this run) | 46 | 53 | ThinkingCap (Qwen3.8 27B) +7 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Laguna XS 2.1 | ThinkingCap (Qwen3.8 27B) |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Poolside | BottleCap AI |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | OpenMDW-1.1 | PolyForm-Small-Business-1.0.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-19 | 2026-10-06 |\n| Terms last updated | | no document linked |\n| Privacy policy last updated | | |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 2.8/5 (4) | 2.5/5 (4) |\n\n## Verdicts\n\n**Laguna XS 2.1.** A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.\n\n**ThinkingCap (Qwen3.8 27B).** A Qwen3.8-27B with shorter reasoning, for agent work where thinking tokens cost time, and BottleCap's 4-bit GGUF runs in about 19 GB. The main limits are the licence, which needs a paid licence above 100 people or 1,000,000 USD revenue, a gated main repository, and no safety results or training-data description.\n\n## Before you call either\n\n### Laguna XS 2.1\n\n1. Quickest start is `ollama run laguna-xs-2.1`, 20 GB of files, the same Q4_K_M as Poolside's GGUF\n2. On our reference machine use `llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072`, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB)\n3. With vLLM use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on a build with vllm-project/vllm#47311, or `--tool-call-parser glm47` on older builds\n4. 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\n5. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped\n6. Sampling per the card is temperature 1.0 and top_k 20\n7. The card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships\n8. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\n\n### ThinkingCap (Qwen3.8 27B)\n\n1. Check the licence first, an organisation with 100 or more people or 1,000,000 USD (2019) revenue needs a commercial licence from BottleCap\n2. For files without the gate use `llama-server -hf bottlecapai/ThinkingCap-Qwen3.8-27B-GGUF:Q4_K_M --jinja`, about 17.4 GB\n3. On vLLM use `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_xml`, and on SGLang `--tool-call-parser qwen3_coder`\n4. Set `reasoning_effort` (xhigh, medium or low) in chat_template_kwargs, any other value makes the template raise an error\n5. Keep the base's sampling (temperature 1.0, top_p 0.95, top_k 20), the GGUF card says greedy decoding can loop\n6. The GGUFs carry an MTP head, and llama.cpp builds without MTP support for this architecture may refuse to load them with a missing blk.64 tensor\n\n## Questions\n\n### Which is better for AI agents, Laguna XS 2.1 or ThinkingCap (Qwen3.8 27B)?\n\nLaguna XS 2.1 and ThinkingCap (Qwen3.8 27B) score within a point of each other on agent readiness, 61 (C) and 61 (C). ThinkingCap (Qwen3.8 27B) leads on documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-thinkingcap-qwen3-8-27b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"laguna-xs-2-1\", \"b\": \"thinkingcap-qwen3-8-27b\"}`. From a terminal: `anchor compare laguna-xs-2-1 thinkingcap-qwen3-8-27b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json and https://www.anchorterminal.com/api/v1/tools/thinkingcap-qwen3-8-27b.json\n\n## Other comparisons with Laguna XS 2.1 or ThinkingCap (Qwen3.8 27B)\n\n- [Agents-A1-4B vs Laguna XS 2.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-2-1.md)\n- [Agents-A1-4B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/agents-a1-4b-vs-thinkingcap-qwen3-8-27b.md)\n- [Apertus v1.5 8B vs Laguna XS 2.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-2-1.md)\n- [Apertus v1.5 8B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-thinkingcap-qwen3-8-27b.md)\n- [Apodex-1.1-mini vs Laguna XS 2.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-2-1.md)\n- [Apodex-1.1-mini vs ThinkingCap (Qwen3.8 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