{ "data": { "a": { "slug": "exaone-4-5-33b", "name": "EXAONE 4.5 33B", "vendor": "LG AI Research", "vendorUrl": "https://www.lgresearch.ai", "kind": "weights", "category": "open-weights", "summary": "EXAONE 4.5 33B is LG AI Research's open-weight vision-language model, 34B parameters, with tool calling, switchable reasoning and a 256K context, strong on documents and Korean. Its licence allows research and education only, with LG's own GGUF from 18 GB.", "url": "https://www.anchorterminal.com/tools/exaone-4-5-33b", "markdownUrl": "https://www.anchorterminal.com/tools/exaone-4-5-33b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/exaone-4-5-33b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/exaone-4-5-33b.json", "dns": "exaone-4-5-33b.grade.anchorterminal.com", "repo": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B", "license": "EXAONE AI Model License Agreement 1.2 - NC (research and education only)", "transports": [], "packages": [ { "registry": "huggingface", "name": "LGAI-EXAONE/EXAONE-4.5-33B" }, { "registry": "huggingface", "name": "LGAI-EXAONE/EXAONE-4.5-33B-GGUF" }, { "registry": "huggingface", "name": "LGAI-EXAONE/EXAONE-4.5-33B-AWQ" }, { "registry": "huggingface", "name": "LGAI-EXAONE/EXAONE-4.5-33B-FP8" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account or token. None of the four repositories is gated, though the licence says downloading is agreeing to it (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download for research and education. The EXAONE AI Model License Agreement 1.2 - NC prohibits commercial use of the model, its derivatives and its output without a separate agreement with LG. Running it yourself takes 20.6 GB at IQ4_XS with its projector, up to 68.7 GB in BF16 (checked 2026-11-10).", "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 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://github.com/LG-AI-EXAONE/EXAONE-4.5", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "multimodal", "vision", "documents", "korean", "reasoning", "tool-calling", "long-context", "non-commercial", "safetensors", "gguf", "awq", "fp8", "self-hosted" ], "lastRelease": "2026-07-06", "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": 1518, "categoryRank": 51, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 85, "reach": 65, "risk": 50, "upkeep": 50 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "A well-documented vision-language model with a full set of builds, tool calling, switchable reasoning, a 256K context and a stated knowledge cut-off. The licence decides whether you can use it: research and education only, output included, and LG can change the terms. Nothing answered on the repository and no safety results.", "bestFor": "Researchers and students working on documents, Korean or multimodal agents who don't need commercial rights", "strengths": [ "A complete card, down to a knowledge cut-off", "GGUF, AWQ and FP8 builds from LG", "Released vLLM, Transformers and llama.cpp run it with no repository code", "Tool calling and reasoning control documented with parsers", "A 256K context, served on one large GPU" ], "weaknesses": [ "Research and education only. No commercial use of the model or its output", "LG can amend the licence at any time, and it's revocable", "No building models that compete with LG's", "No reply from LG on the repository's discussions", "Not changed since the summer", "No safety results or training data sources on the card" ], "agentNotes": [ "Don't use it, or anything it writes, commercially. The licence covers the output too", "Serve it with vLLM and `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser hermes`", "Set `enable_thinking` false for a direct answer. Thinking is on by default", "Use temperature 1.0, top_p 0.95 and presence_penalty 1.5 in general, and temperature 0.6 with top_k 20 for documents and Korean", "For llama.cpp, load a projector file from LG's GGUF repository with the weights for image input", "Its knowledge stops at December 2024" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 85, "reach": 65, "risk": 50, "upkeep": 50 }, "provenanceScore": 49, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install \"vllm\u003e=0.33.0\" \"transformers\u003e=5.8.0\"\nvllm serve LGAI-EXAONE/EXAONE-4.5-33B --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser hermes", "http": "# vLLM serves an OpenAI-compatible API at http://localhost:8000/v1. The card recommends temperature 1.0,\n# top_p 0.95 and presence_penalty 1.5, and enable_thinking false for a direct answer" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/exaone-4-5-33b" }, "weights": { "trainedBy": "LG AI Research", "params": "34B", "context": 262144, "goodFor": "Research on document understanding, Korean and agent work with images, where non-commercial terms are acceptable.", "runtimes": [ "llama.cpp", "vLLM", "Transformers" ], "builds": [ { "name": "EXAONE-4.5-33B-GGUF IQ4_XS", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B-GGUF/blob/main/EXAONE-4.5-33B-IQ4_XS.gguf", "who": "publisher", "precision": "iq4_xs", "sizeGB": 20.6, "memoryGB": 32, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "18.03 GB with the 2.57 GB F16 projector" }, { "name": "EXAONE-4.5-33B-GGUF Q4_K_M", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B-GGUF/blob/main/EXAONE-4.5-33B-Q4_K_M.gguf", "who": "publisher", "precision": "q4_k_m", "sizeGB": 22.62, "memoryGB": 32, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "20.05 GB with the 2.57 GB F16 projector" }, { "name": "EXAONE-4.5-33B-AWQ", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B-AWQ", "who": "publisher", "precision": "awq", "sizeGB": 22.75, "memoryGB": 32, "format": "safetensors", "runsOn": [ "vLLM" ], "note": "LG's 4-bit AWQ build" }, { "name": "EXAONE-4.5-33B-GGUF Q8_0", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B-GGUF/blob/main/EXAONE-4.5-33B-Q8_0.gguf", "who": "publisher", "precision": "q8_0", "sizeGB": 37.71, "memoryGB": 48, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "35.14 GB with the 2.57 GB F16 projector" }, { "name": "EXAONE-4.5-33B-FP8", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 41.31, "memoryGB": 64, "format": "safetensors", "runsOn": [ "vLLM" ], "note": "LG's FP8 build" }, { "name": "EXAONE-4.5-33B (BF16 safetensors)", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B", "who": "publisher", "precision": "bf16", "sizeGB": 68.7, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM", "Transformers" ], "note": "Two shards" } ], "run": "llama-server -hf LGAI-EXAONE/EXAONE-4.5-33B-GGUF:Q4_K_M --jinja", "runBuild": "EXAONE-4.5-33B-GGUF Q4_K_M", "checked": "2026-11-10", "minMemoryGB": 32 }, "family": { "lab": "LG AI Research", "family": "EXAONE 4", "url": "https://www.anchorterminal.com/open-weights/#lg-ai-research", "others": [ { "name": "EXAONE-4.0.1-32B", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.0.1-32B" }, { "name": "EXAONE-4.0-1.2B", "url": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-1.2B" } ] }, "area": "models", "provenance": { "legalEntity": "LG Management Development Institute Co., Ltd., the licensor named in the model's licence. The card names LG AI Research", "domain": "lgresearch.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B/blob/main/LICENSE", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "The card and the Hub organisation name LG AI Research, and the licence names LG Management Development Institute Co., Ltd. as licensor. How the two relate wasn't read first-hand.", "www.lgresearch.ai's robots.txt allows reading. Its home page gave little text and its about page a 404, so no people or ownership facts were taken from it.", "The domain's registration date wasn't looked up. www.lgresearch.ai has no security.txt (404 on 10 November 2026).", "Nothing is hosted under this listing, so the model licence stands in for terms of service and no privacy policy is scored.", "The changelog is the commit history, 8 commits from 9 April to 6 July 2026." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/exaone-4-5-33b.json" }, "answer": "EXAONE 4.5 33B scores 61 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on reach and risk.", "b": { "slug": "laguna-m-1", "name": "Laguna M.1", "vendor": "Poolside", "vendorUrl": "https://poolside.ai", "kind": "weights", "category": "open-weights", "summary": "Laguna M.1 is Poolside's first-generation open-weight Mixture-of-Experts model for agentic coding, 225B total and 23B active parameters, with switchable reasoning and a 262,144-token context, published on Hugging Face under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/laguna-m-1", "markdownUrl": "https://www.anchorterminal.com/tools/laguna-m-1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-m-1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json", "dns": "laguna-m-1.grade.anchorterminal.com", "repo": "https://huggingface.co/poolside/Laguna-M.1", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "poolside/Laguna-M.1" }, { "registry": "huggingface", "name": "poolside/Laguna-M.1-FP8" }, { "registry": "huggingface", "name": "poolside/Laguna-M.1-NVFP4" } ], "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 both builds, 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 Apache 2.0. Running it yourself costs the hardware, 451.6 GB for the BF16 files and 139.3 GB for the NVFP4 build. The card links Poolside's API for hosted use, but no inference provider is mapped on the Hub and Poolside's API docs name only Laguna S 2.1 (checked 2026-11-04).", "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-M.1", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "coding", "reasoning", "tool-calling", "apache-2.0", "safetensors", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-07-14", "graded": true, "anchor": { "graded": true, "score": 56.7, "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": 1518, "categoryRank": 84, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 46, "interface": 85, "reach": 70, "risk": 55, "upkeep": 36 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-04" }, "negative": 0, "verdict": "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.", "bestFor": "Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.", "strengths": [ "Plain Apache 2.0 with no gate, account or use policy", "Released support in vLLM, SGLang, Transformers, llama.cpp and Ollama (through its pinned llama.cpp)", "Poolside's own FP8 and NVFP4 builds", "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": [ "The smallest build needs about 167 GB, more than a 128 GB machine", "No Ollama library or LM Studio catalogue entry, and no publisher GGUF build", "No change to the files since 14 July 2026 and no reply from Poolside to its one discussion", "No safety results and only general cautions for agent use", "No hosting found. No inference provider is mapped on the Hub, and Poolside's API docs name only Laguna S 2.1" ], "agentNotes": [ "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_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 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" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 56.7 } ], "editorialScores": { "capability": 46, "interface": 85, "reach": 70, "risk": 55, "upkeep": 36 }, "provenanceScore": 69, "checked": { "categories": { "capability": "2026-11-04", "interface": "2026-11-04", "reach": "2026-11-04", "risk": "2026-11-04", "upkeep": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install 'vllm\u003e=0.21.0'\nvllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 \\\n --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"model\": \"poolside/Laguna-M.1-NVFP4\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/laguna-m-1" }, "sameCompany": [ "laguna-s-2-1", "laguna-xs-2-1" ], "weights": { "trainedBy": "Poolside", "params": "225.8B total, 23B active", "context": 262144, "goodFor": "Agentic coding on a multi-GPU server, with tool calling and reasoning that turns on or off per request, under Apache 2.0.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Laguna-M.1-NVFP4", "url": "https://huggingface.co/poolside/Laguna-M.1-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 139.3, "memoryGB": 192, "format": "safetensors", "note": "For NVIDIA Blackwell GPUs" }, { "name": "Laguna-M.1-FP8", "url": "https://huggingface.co/poolside/Laguna-M.1-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 238.6, "memoryGB": 512, "format": "safetensors", "note": "238.6 GB summed from the file list, of which 9.5 GB is a Docker image (image/laguna-vllm-v0.19.0-overlay.tar.gz) and 229.1 GB the weights. Either way 512 GB" }, { "name": "Laguna-M.1", "url": "https://huggingface.co/poolside/Laguna-M.1", "who": "publisher", "precision": "bf16", "sizeGB": 451.6, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ] } ], "run": "vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'", "runBuild": "Laguna-M.1-NVFP4", "checked": "2026-11-04", "minMemoryGB": 192 }, "family": { "lab": "Poolside", "family": "Laguna 1 (M.1)", "url": "https://www.anchorterminal.com/open-weights/#poolside", "others": [ { "name": "Laguna-M.1-base", "url": "https://huggingface.co/poolside/Laguna-M.1-base", "params": "225.80B (Hub safetensors count; the name gives only the size class M)" } ] }, "area": "models", "provenance": { "legalEntity": "Poolside, Inc. (named in Poolside's Terms of Use; the LICENSE.md copyright line reads Poolside)", "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 M.1 blog post links the repository.", "Nothing is hosted for this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "Poolside's docs keep dated model release notes, with an April 2026 entry for M.1.", "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": 69 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-m-1.json", "live": { "slug": "laguna-m-1", "securityTxt": { "url": "https://poolside.ai/.well-known/security.txt", "state": "valid", "expires": "2028-04-01T12:00:00.000Z", "checkedAt": "2026-11-10T16:09:25.614312659Z" }, "domain": { "domain": "poolside.ai", "registered": "2020-07-07", "source": "https://rdap.identitydigital.services/rdap/domain/poolside.ai", "checkedAt": "2026-11-08T14:58:52.089559761Z" }, "pages": [ { "url": "https://docs.poolside.ai/release-notes/models", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:18:11.541481401Z", "changedAt": "2026-11-01T06:42:30.392417309Z", "fingerprint": "41c3a898c1a6" }, { "url": "https://poolside.ai/legal/privacy", "kind": "privacy", "status": 304, "checkedAt": "2026-11-10T16:28:14.659109859Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "95a56164038b" }, { "url": "https://poolside.ai/legal/eula", "kind": "terms", "status": 304, "checkedAt": "2026-11-10T16:28:12.585971651Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6daf0ef509c0" } ], "updatedAt": "2026-11-10T16:28:14.659109859Z" } }, "edges": [ { "by": 14, "category": "upkeep", "leads": "exaone-4-5-33b", "name": "Documentation and upkeep", "reasons": { "a": "Model card 20, Uses (the quickstart's question answering, document and agent examples), limitations, the architecture, the parameters, the context, the languages (in the metadata) and a knowledge cut-off of December 2024 are all on the card. Training data 5, A knowledge cut-off and one line on excluding personal, harmful and biased content, with no sources or sizes. Last change 10, the main repository last changed on 6 July 2026 (dependencies moved to official releases), 127 days before this check, and the FP8 repository on 9 August, 93 days. Responsiveness 0, none of the 5 most recent discussions that aren't pull requests (13 April to 4 May 2026) has a reply from an LGAI-EXAONE member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, EXAONE 4.0 and 4.0.1 stay in their own repositories and 4.5 came out in new ones, with no dated note on the older cards that we read. File health 10, Config, template and card agree on the architecture and the 262,144 tokens, and a July commit moved the dependencies to released versions. 20 + 5 + 10 + 0 + 5 + 10 = 50.", "b": "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." }, "scores": { "a": 50, "b": 36 } }, { "by": 5, "category": "reach", "leads": "laguna-m-1", "name": "Reach", "reasons": { "a": "Memory 20, the smallest build at 4 bits is LG's IQ4_XS GGUF, 18.03 GB with the 2.57 GB projector, and 20.60 GB × 1.2 = 24.7 GB, within 32 GB. Without the projector, for text only, it would fit 24 GB. Runtimes 15, Released vLLM 0.33.0 has exaone4_5.py, Transformers 5.22.2 has the exaone4_5 model, and llama.cpp b12242 has the architecture, with LG's own GGUF. Three at 5 each. Builds 15, LG publishes GGUF at five quantised precisions, an AWQ build and an FP8 build. Terms 5, Research and educational use only. Download 10, the Hub API reports gated false for all four repositories on 10 November 2026, so the files download with no account and no click-through, though the licence says downloading is acceptance. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API that serves it. 20 + 15 + 15 + 5 + 10 + 0 = 65.", "b": "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." }, "scores": { "a": 65, "b": 70 } }, { "by": 5, "category": "risk", "leads": "laguna-m-1", "name": "Risk", "reasons": { "a": "File safety 25, safetensors and GGUF only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the LGAI-EXAONE organisation (LG AI Research on the Hub), which the card's GitHub repository shares a name with and the licence in the repository is LG's (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions: the limitation section lists inappropriate, biased, incorrect and outdated answers and tells users not to try to induce harmful output. Licence risk 5, 15 less 5 for field-of-use limits beyond the law (no commercial use, no building competing models) and 5 for terms the licensor can change or revoke (LG may amend the agreement at any time, and the licence is revocable). Security programme 0, no way to report a flaw on the card beyond a support contact, and www.lgresearch.ai has no security.txt. 25 + 15 + 0 + 5 + 5 + 0 = 50.", "b": "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_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, plain Apache 2.0. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found." }, "scores": { "a": 50, "b": 55 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "LG AI Research", "b": "Poolside", "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": "EXAONE AI Model License Agreement 1.2 - NC (research and education only)", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-06", "b": "2026-07-14", "name": "Last release" }, { "a": "not read yet", "b": "2026-07-21", "name": "Terms last updated" }, { "a": "no document linked", "b": "2026-07-21", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "yes, with an opt-out", "name": "Customer content may train models" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "EXAONE 4.5 33B scores 61 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on reach and risk.", "question": "Which is better for AI agents, EXAONE 4.5 33B or Laguna M.1?" } ], "goodFor": [ { "aheadOn": [ "Documentation and upkeep, 50 against 36" ], "also": null, "goodFor": "Researchers and students working on documents, Korean or multimodal agents who don't need commercial rights", "slug": "exaone-4-5-33b", "watchFor": "Research and education only. No commercial use of the model or its output" }, { "aheadOn": [ "Reach, 70 against 65", "Risk, 55 against 50" ], "also": null, "goodFor": "Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.", "slug": "laguna-m-1", "watchFor": "The smallest build needs about 167 GB, more than a 128 GB machine" } ], "history": { "exaone-4-5-33b": null, "laguna-m-1": [ { "causes": [ "correction" ], "date": "2026-11-04", "delta": 1.2, "from": 55.5, "fromGrade": "C", "to": 56.7, "toGrade": "C" } ] }, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-exaone-4-5-33b.json", "title": "Agents-A1-4B vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1.json", "title": "Agents-A1-4B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-exaone-4-5-33b.json", "title": "Apertus v1.5 8B vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1.json", "title": "Apertus v1.5 8B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-exaone-4-5-33b.json", "title": "Apodex-1.1-mini vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1.json", "title": "Apodex-1.1-mini vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-exaone-4-5-33b.json", "title": "Arete-27B vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1.json", "title": "Arete-27B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-exaone-4-5-33b.json", "title": "BigBang-v1 vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1.json", "title": "BigBang-v1 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-exaone-4-5-33b.json", "title": "Carbon-X vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1.json", "title": "Carbon-X vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-exaone-4-5-33b.json", "title": "Cola2 vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/cola2-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-laguna-m-1.json", "title": "Cola2 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/cola2-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-exaone-4-5-33b.json", "title": "Cosmos-Reason2-2B vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1.json", "title": "Cosmos-Reason2-2B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-exaone-4-5-33b.json", "title": "Darwin-36B-Opus vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.json", "title": "Darwin-36B-Opus vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-exaone-4-5-33b.json", "title": "DeepSeek-V3.2 vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1.json", "title": "DeepSeek-V3.2 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-exaone-4-5-33b.json", "title": "DeepSeek V4.1 Flash vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-m-1.json", "title": "DeepSeek V4.1 Flash vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-exaone-4-5-33b.json", "title": "DeepSeek-V4-Flash-0731 vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-m-1.json", "title": "DeepSeek-V4-Flash-0731 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-exaone-4-5-33b.json", "title": "Devstral Small 2 vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-m-1.json", "title": "Devstral Small 2 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-exaone-4-5-33b.json", "title": "DiffusionGemma 26B A4B IT vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-m-1.json", "title": "DiffusionGemma 26B A4B IT vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-12b-it.json", "title": "EXAONE 4.5 33B vs Gemma 4 12B IT", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-12b-it" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-26b-a4b-it.json", "title": "EXAONE 4.5 33B vs Gemma 4 26B A4B IT", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-31b-it.json", "title": "EXAONE 4.5 33B vs Gemma 4 31B IT", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-31b-it" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-e2b-it.json", "title": "EXAONE 4.5 33B vs Gemma 4 E2B IT", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-e2b-it" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-e4b-it.json", "title": "EXAONE 4.5 33B vs Gemma 4 E4B IT", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-e4b-it" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-4-5-air.json", "title": "EXAONE 4.5 33B vs GLM-4.5-Air", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-4-5-air" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-4-7-flash.json", "title": "EXAONE 4.5 33B vs GLM-4.7-Flash", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-4-7-flash" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3.json", "title": "EXAONE 4.5 33B vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash.json", "title": "EXAONE 4.5 33B vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gpt-oss-120b.json", "title": "EXAONE 4.5 33B vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gpt-oss-120b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gpt-oss-20b.json", "title": "EXAONE 4.5 33B vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-30b.json", "title": "EXAONE 4.5 33B vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-3b.json", "title": "EXAONE 4.5 33B vs Granite 4.2 3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-8b.json", "title": "EXAONE 4.5 33B vs Granite 4.2 8B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-8b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-hy-memory-30b-a3b.json", "title": "EXAONE 4.5 33B vs Hy-Memory-30B-A3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-hy-memory-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-hy3.json", "title": "EXAONE 4.5 33B vs Hy3", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling.json", "title": "EXAONE 4.5 33B vs Inkling", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling-small.json", "title": "EXAONE 4.5 33B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "EXAONE 4.5 33B vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kimi-k3.json", "title": "EXAONE 4.5 33B vs Kimi K3", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kimi-k3-1-pro.json", "title": "EXAONE 4.5 33B vs Kimi K3.1 Pro", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kimi-k3-1-pro" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kolibri-1.json", "title": "EXAONE 4.5 33B vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kronos.json", "title": "EXAONE 4.5 33B vs Kronos", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kronos" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-s-2-1.json", "title": "EXAONE 4.5 33B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-xs-2-1.json", "title": "EXAONE 4.5 33B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lbs-27b.json", "title": "EXAONE 4.5 33B vs LBS-27B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm2-5-2-6b.json", "title": "EXAONE 4.5 33B vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-1-7b.json", "title": "EXAONE 4.5 33B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-audio-2b.json", "title": "EXAONE 4.5 33B vs LFM3-Audio-2B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-audio-2b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-omni-2b.json", "title": "EXAONE 4.5 33B vs LFM3-Omni-2B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-omni-2b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-vl-2b.json", "title": "EXAONE 4.5 33B vs LFM3-VL-2B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-0-tiny.json", "title": "EXAONE 4.5 33B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-1-flash-1019.json", "title": "EXAONE 4.5 33B vs Ling-3.1-flash-1019", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-1-flash-1019" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-longcat-2-5.json", "title": "EXAONE 4.5 33B vs LongCat-2.5", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-longcat-2-5" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-distill-qwen-9b.json", "title": "EXAONE 4.5 33B vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-flash-rl.json", "title": "EXAONE 4.5 33B vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-o-4-5.json", "title": "EXAONE 4.5 33B vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-v-4-7-1b.json", "title": "EXAONE 4.5 33B vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-v-4-7-35b-a3b.json", "title": "EXAONE 4.5 33B vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm5-2b.json", "title": "EXAONE 4.5 33B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m2-5.json", "title": "EXAONE 4.5 33B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m2-7.json", "title": "EXAONE 4.5 33B vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m3-1-flash.json", "title": "EXAONE 4.5 33B vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mistral-large-4.json", "title": "EXAONE 4.5 33B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-muse-glimmer-30b.json", "title": "EXAONE 4.5 33B vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nanbeige-4-2-3b.json", "title": "EXAONE 4.5 33B vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nanbeige-4-3-33b.json", "title": "EXAONE 4.5 33B vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "EXAONE 4.5 33B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "EXAONE 4.5 33B vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-30b-a3b.json", "title": "EXAONE 4.5 33B vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-4b.json", "title": "EXAONE 4.5 33B vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "EXAONE 4.5 33B vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-super-120b-a12b.json", "title": "EXAONE 4.5 33B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-ultra-550b-a55b.json", "title": "EXAONE 4.5 33B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-north-mini-code-1-0.json", "title": "EXAONE 4.5 33B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-occamy-1-0.json", "title": "EXAONE 4.5 33B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-olmo-3-7b-think.json", "title": "EXAONE 4.5 33B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-122b.json", "title": "EXAONE 4.5 33B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-35b-a3b.json", "title": "EXAONE 4.5 33B vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-397b.json", "title": "EXAONE 4.5 33B vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-9b.json", "title": "EXAONE 4.5 33B vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-otel-2-0-llm-31b-it.json", "title": "EXAONE 4.5 33B vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen-agentworld-35b-a3b.json", "title": "EXAONE 4.5 33B vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "EXAONE 4.5 33B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-4b-instruct-2507.json", "title": "EXAONE 4.5 33B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-0-8b.json", "title": "EXAONE 4.5 33B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-122b-a10b.json", "title": "EXAONE 4.5 33B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-2b.json", "title": "EXAONE 4.5 33B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-397b-a17b.json", "title": "EXAONE 4.5 33B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-4b.json", "title": "EXAONE 4.5 33B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-9b.json", "title": "EXAONE 4.5 33B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-6-27b.json", "title": "EXAONE 4.5 33B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-6-35b-a3b.json", "title": "EXAONE 4.5 33B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-8-27b.json", "title": "EXAONE 4.5 33B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-8-flash-next.json", "title": "EXAONE 4.5 33B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "EXAONE 4.5 33B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-coder-next.json", "title": "EXAONE 4.5 33B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "EXAONE 4.5 33B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-2b-instruct.json", "title": "EXAONE 4.5 33B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "EXAONE 4.5 33B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-32b-instruct.json", "title": "EXAONE 4.5 33B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-4b-instruct.json", "title": "EXAONE 4.5 33B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-8b-instruct.json", "title": "EXAONE 4.5 33B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwopus3-8-27b-flash-v2.json", "title": "EXAONE 4.5 33B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-recursive-flint.json", "title": "EXAONE 4.5 33B vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ripple-65b-preview.json", "title": "EXAONE 4.5 33B vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-sensenova-loop-9b-preview.json", "title": "EXAONE 4.5 33B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-smollm3-3b.json", "title": "EXAONE 4.5 33B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-spark-x2-6-4b.json", "title": "EXAONE 4.5 33B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-step-3-7-flash.json", "title": "EXAONE 4.5 33B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-swift-1-5-qwen3-8-27b.json", "title": "EXAONE 4.5 33B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "EXAONE 4.5 33B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-thinkingcap-qwen3-8-27b.json", "title": "EXAONE 4.5 33B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-unlimited-ocr-2.json", "title": "EXAONE 4.5 33B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-wevisone-vl-2b.json", "title": "EXAONE 4.5 33B vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-wevisone-vl-4b.json", "title": "EXAONE 4.5 33B vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-zaya1-8b.json", "title": "EXAONE 4.5 33B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-m-1.json", "title": "Gemma 4 12B IT vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-m-1.json", "title": "Gemma 4 26B A4B IT vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-m-1.json", "title": "Gemma 4 31B IT vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-m-1.json", "title": "Gemma 4 E2B IT vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-m-1.json", "title": "Gemma 4 E4B IT vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-m-1.json", "title": "GLM-4.5-Air vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-m-1.json", "title": "GLM-4.7-Flash vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-m-1.json", "title": "GLM-5.3-Flash vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1.json", "title": "GLM-5.3 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-m-1.json", "title": "gpt-oss-120b vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-m-1.json", "title": "gpt-oss-20b vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-m-1.json", "title": "Granite 4.2 30B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-m-1.json", "title": "Granite 4.2 3B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-m-1.json", "title": "Granite 4.2 8B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-laguna-m-1.json", "title": "Hy-Memory-30B-A3B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-laguna-m-1.json", "title": "Hy3 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/hy3-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-m-1.json", "title": "Inkling-Small vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1.json", "title": "Inkling vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-m-1.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-laguna-m-1.json", "title": "Kimi K3.1 Pro vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-m-1.json", "title": "Kimi K3 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-m-1.json", "title": "Kolibri-1 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/kronos-vs-laguna-m-1.json", "title": "Kronos vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/kronos-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-s-2-1.json", "title": "Laguna M.1 vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-s-2-1" }, { "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-lbs-27b.json", "title": "Laguna M.1 vs LBS-27B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm2-5-2-6b.json", "title": "Laguna M.1 vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-1-7b.json", "title": "Laguna M.1 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-audio-2b.json", "title": "Laguna M.1 vs LFM3-Audio-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-audio-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-omni-2b.json", "title": "Laguna M.1 vs LFM3-Omni-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-omni-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-vl-2b.json", "title": "Laguna M.1 vs LFM3-VL-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-0-tiny.json", "title": "Laguna M.1 vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-1-flash-1019.json", "title": "Laguna M.1 vs Ling-3.1-flash-1019", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-1-flash-1019" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-longcat-2-5.json", "title": "Laguna M.1 vs LongCat-2.5", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-longcat-2-5" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Laguna M.1 vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mimo-v2-6-flash-rl.json", "title": "Laguna M.1 vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-o-4-5.json", "title": "Laguna M.1 vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-v-4-7-1b.json", "title": "Laguna M.1 vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-v-4-7-35b-a3b.json", "title": "Laguna M.1 vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.json", "title": "Laguna M.1 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-5.json", "title": "Laguna M.1 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-7.json", "title": "Laguna M.1 vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m3-1-flash.json", "title": "Laguna M.1 vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mistral-large-4.json", "title": "Laguna M.1 vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-muse-glimmer-30b.json", "title": "Laguna M.1 vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b.json", "title": "Laguna M.1 vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-3-33b.json", "title": "Laguna M.1 vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "Laguna M.1 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Laguna M.1 vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-30b-a3b.json", "title": "Laguna M.1 vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-4b.json", "title": "Laguna M.1 vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Laguna M.1 vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-super-120b-a12b.json", "title": "Laguna M.1 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-ultra-550b-a55b.json", "title": "Laguna M.1 vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0.json", "title": "Laguna M.1 vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.json", "title": "Laguna M.1 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.json", "title": "Laguna M.1 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-122b.json", "title": "Laguna M.1 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-35b-a3b.json", "title": "Laguna M.1 vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-397b.json", "title": "Laguna M.1 vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-9b.json", "title": "Laguna M.1 vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-otel-2-0-llm-31b-it.json", "title": "Laguna M.1 vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b.json", "title": "Laguna M.1 vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Laguna M.1 vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.json", "title": "Laguna M.1 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-0-8b.json", "title": "Laguna M.1 vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-122b-a10b.json", "title": "Laguna M.1 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-2b.json", "title": "Laguna M.1 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b.json", "title": "Laguna M.1 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-4b.json", "title": "Laguna M.1 vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-9b.json", "title": "Laguna M.1 vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-27b.json", "title": "Laguna M.1 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-35b-a3b.json", "title": "Laguna M.1 vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b.json", "title": "Laguna M.1 vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next.json", "title": "Laguna M.1 vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-next.json", "title": "Laguna M.1 vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Laguna M.1 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-2b-instruct.json", "title": "Laguna M.1 vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Laguna M.1 vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-32b-instruct.json", "title": "Laguna M.1 vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-4b-instruct.json", "title": "Laguna M.1 vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-8b-instruct.json", "title": "Laguna M.1 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwopus3-8-27b-flash-v2.json", "title": "Laguna M.1 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint.json", "title": "Laguna M.1 vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ripple-65b-preview.json", "title": "Laguna M.1 vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-sensenova-loop-9b-preview.json", "title": "Laguna M.1 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b.json", "title": "Laguna M.1 vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-spark-x2-6-4b.json", "title": "Laguna M.1 vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.json", "title": "Laguna M.1 vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-27b.json", "title": "Laguna M.1 vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Laguna M.1 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next" }, { "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-m-1-vs-unlimited-ocr-2.json", "title": "Laguna M.1 vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b.json", "title": "Laguna M.1 vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b.json", "title": "Laguna M.1 vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b.json", "title": "Laguna M.1 vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 5, "edge": "laguna-m-1", "exaone-4-5-33b": 65, "key": "reach", "laguna-m-1": 70, "name": "Reach", "weight": 25 }, { "by": 5, "edge": "laguna-m-1", "exaone-4-5-33b": 50, "key": "risk", "laguna-m-1": 55, "name": "Risk", "weight": 20 }, { "by": 0, "edge": "", "exaone-4-5-33b": 85, "key": "interface", "laguna-m-1": 85, "name": "Agent interface", "weight": 10 }, { "by": 14, "edge": "exaone-4-5-33b", "exaone-4-5-33b": 50, "key": "upkeep", "laguna-m-1": 36, "name": "Documentation and upkeep", "weight": 10 } ], "summary": "EXAONE 4.5 33B scores 61 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on reach and risk. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "exaone-4-5-33b": "A well-documented vision-language model with a full set of builds, tool calling, switchable reasoning, a 256K context and a stated knowledge cut-off. The licence decides whether you can use it: research and education only, output included, and LG can change the terms. Nothing answered on the repository and no safety results.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1", "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1.min.md" }, "markdown": "EXAONE 4.5 33B scores 61 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on reach and risk. Both do open-weight models you run yourself.\n\n- EXAONE 4.5 33B: grade C, 61/100, rank #61 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/exaone-4-5-33b.md · JSON https://www.anchorterminal.com/api/v1/tools/exaone-4-5-33b.json\n- Laguna M.1: grade C, 56.7/100, rank #112 of 160 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\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### EXAONE 4.5 33B (C)\n\nGood for: Researchers and students working on documents, Korean or multimodal agents who don't need commercial rights\n\nAhead on:\n- Documentation and upkeep, 50 against 36\n\nWatch for: Research and education only. No commercial use of the model or its output\n\n### Laguna M.1 (C)\n\nGood for: Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.\n\nAhead on:\n- Reach, 70 against 65\n- Risk, 55 against 50\n\nWatch for: The smallest build needs about 167 GB, more than a 128 GB machine\n\n\n## Why the edge\n\n### Documentation and upkeep: EXAONE 4.5 33B +14\n\n- EXAONE 4.5 33B (50): Model card 20, Uses (the quickstart's question answering, document and agent examples), limitations, the architecture, the parameters, the context, the languages (in the metadata) and a knowledge cut-off of December 2024 are all on the card. Training data 5, A knowledge cut-off and one line on excluding personal, harmful and biased content, with no sources or sizes. Last change 10, the main repository last changed on 6 July 2026 (dependencies moved to official releases), 127 days before this check, and the FP8 repository on 9 August, 93 days. Responsiveness 0, none of the 5 most recent discussions that aren't pull requests (13 April to 4 May 2026) has a reply from an LGAI-EXAONE member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, EXAONE 4.0 and 4.0.1 stay in their own repositories and 4.5 came out in new ones, with no dated note on the older cards that we read. File health 10, Config, template and card agree on the architecture and the 262,144 tokens, and a July commit moved the dependencies to released versions. 20 + 5 + 10 + 0 + 5 + 10 = 50.\n- 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.\n\n### Reach: Laguna M.1 +5\n\n- EXAONE 4.5 33B (65): Memory 20, the smallest build at 4 bits is LG's IQ4_XS GGUF, 18.03 GB with the 2.57 GB projector, and 20.60 GB × 1.2 = 24.7 GB, within 32 GB. Without the projector, for text only, it would fit 24 GB. Runtimes 15, Released vLLM 0.33.0 has exaone4_5.py, Transformers 5.22.2 has the exaone4_5 model, and llama.cpp b12242 has the architecture, with LG's own GGUF. Three at 5 each. Builds 15, LG publishes GGUF at five quantised precisions, an AWQ build and an FP8 build. Terms 5, Research and educational use only. Download 10, the Hub API reports gated false for all four repositories on 10 November 2026, so the files download with no account and no click-through, though the licence says downloading is acceptance. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API that serves it. 20 + 15 + 15 + 5 + 10 + 0 = 65.\n- 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.\n\n### Risk: Laguna M.1 +5\n\n- EXAONE 4.5 33B (50): File safety 25, safetensors and GGUF only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the LGAI-EXAONE organisation (LG AI Research on the Hub), which the card's GitHub repository shares a name with and the licence in the repository is LG's (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions: the limitation section lists inappropriate, biased, incorrect and outdated answers and tells users not to try to induce harmful output. Licence risk 5, 15 less 5 for field-of-use limits beyond the law (no commercial use, no building competing models) and 5 for terms the licensor can change or revoke (LG may amend the agreement at any time, and the licence is revocable). Security programme 0, no way to report a flaw on the card beyond a support contact, and www.lgresearch.ai has no security.txt. 25 + 15 + 0 + 5 + 5 + 0 = 50.\n- 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_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, plain Apache 2.0. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.\n\n## Score by category\n\n| Category | Weight | EXAONE 4.5 33B | Laguna M.1 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 70 | Laguna M.1 +5 |\n| Risk | 20% (20 this run) | 50 | 55 | Laguna M.1 +5 |\n| Agent interface | 10% (10 this run) | 85 | 85 | even |\n| Documentation and upkeep | 10% (10 this run) | 50 | 36 | EXAONE 4.5 33B +14 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **56.7 · C** | |\n\n## Facts side by side\n\n| Fact | EXAONE 4.5 33B | Laguna M.1 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | LG AI Research | Poolside |\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 | EXAONE AI Model License Agreement 1.2 - NC (research and education only) | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-06 | 2026-07-14 |\n| Terms last updated | not read yet | 2026-07-21 |\n| Privacy policy last updated | no document linked | 2026-07-21 |\n| Customer content may train models | not read yet | yes, with an opt-out |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | yes |\n| Arbitration or class-action waiver | not read yet | yes |\n| Agent reviews | none | 2.5/5 (4) |\n\n## How the scores have moved\n\n### EXAONE 4.5 33B\n\nNo score change since it was listed.\n\n### Laguna M.1\n\n- +1.2 on 4 November 2026: correction\n\n## Verdicts\n\n**EXAONE 4.5 33B.** A well-documented vision-language model with a full set of builds, tool calling, switchable reasoning, a 256K context and a stated knowledge cut-off. The licence decides whether you can use it: research and education only, output included, and LG can change the terms. Nothing answered on the repository and no safety results.\n\n**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.\n\n## Before you call either\n\n### EXAONE 4.5 33B\n\n1. Don't use it, or anything it writes, commercially. The licence covers the output too\n2. Serve it with vLLM and `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser hermes`\n3. Set `enable_thinking` false for a direct answer. Thinking is on by default\n4. Use temperature 1.0, top_p 0.95 and presence_penalty 1.5 in general, and temperature 0.6 with top_k 20 for documents and Korean\n5. For llama.cpp, load a projector file from LG's GGUF repository with the weights for image input\n6. Its knowledge stops at December 2024\n\n### Laguna M.1\n\n1. 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\n2. 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\n3. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped\n4. Sampling per the card is temperature 1.0 and top_k 20\n5. The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM\n6. It doesn't fit our 128 GB reference machine at any published precision\n7. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\n\n## Questions\n\n### Which is better for AI agents, EXAONE 4.5 33B or Laguna M.1?\n\nEXAONE 4.5 33B scores 61 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 1 of 4 scored categories. Laguna M.1 leads on reach and risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"exaone-4-5-33b\", \"b\": \"laguna-m-1\"}`. From a terminal: `anchor compare exaone-4-5-33b laguna-m-1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/exaone-4-5-33b.json and https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json\n\n## Other comparisons with EXAONE 4.5 33B or Laguna M.1\n\n- [Agents-A1-4B vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-exaone-4-5-33b.md)\n- [Agents-A1-4B vs Laguna M.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-m-1.md)\n- [Apertus v1.5 8B vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-exaone-4-5-33b.md)\n- [Apertus v1.5 8B vs Laguna M.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-m-1.md)\n- [Apodex-1.1-mini vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-exaone-4-5-33b.md)\n- [Apodex-1.1-mini vs Laguna M.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-m-1.md)\n- [Arete-27B vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/arete-27b-vs-exaone-4-5-33b.md)\n- [Arete-27B vs Laguna M.1](https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1.md)\n- [BigBang-v1 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/bigbang-v1-vs-exaone-4-5-33b.md)\n- [BigBang-v1 vs Laguna M.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1.md)\n- [Carbon-X vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/carbon-x-vs-exaone-4-5-33b.md)\n- [Carbon-X vs Laguna M.1](https://www.anchorterminal.com/compare/carbon-x-vs-laguna-m-1.md)\n- [Cola2 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/cola2-vs-exaone-4-5-33b.md)\n- [Cola2 vs Laguna M.1](https://www.anchorterminal.com/compare/cola2-vs-laguna-m-1.md)\n- [Cosmos-Reason2-2B vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-exaone-4-5-33b.md)\n- [Cosmos-Reason2-2B vs Laguna M.1](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1.md)\n- [Darwin-36B-Opus vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-exaone-4-5-33b.md)\n- [Darwin-36B-Opus vs Laguna M.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-m-1.md)\n- [DeepSeek-V3.2 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-exaone-4-5-33b.md)\n- [DeepSeek-V3.2 vs Laguna M.1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1.md)\n- [DeepSeek V4.1 Flash vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-exaone-4-5-33b.md)\n- [DeepSeek V4.1 Flash vs Laguna M.1](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-m-1.md)\n- [DeepSeek-V4-Flash-0731 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-exaone-4-5-33b.md)\n- [DeepSeek-V4-Flash-0731 vs Laguna M.1](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-m-1.md)\n- [Devstral Small 2 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/devstral-small-2-vs-exaone-4-5-33b.md)\n- [Devstral Small 2 vs Laguna M.1](https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-m-1.md)\n- [DiffusionGemma 26B A4B IT vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-exaone-4-5-33b.md)\n- [DiffusionGemma 26B A4B IT vs Laguna M.1](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-m-1.md)\n- [EXAONE 4.5 33B vs Gemma 4 12B IT](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-12b-it.md)\n- [EXAONE 4.5 33B vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-26b-a4b-it.md)\n- [EXAONE 4.5 33B vs Gemma 4 31B IT](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-31b-it.md)\n- [EXAONE 4.5 33B vs Gemma 4 E2B IT](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-e2b-it.md)\n- [EXAONE 4.5 33B vs Gemma 4 E4B IT](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gemma-4-e4b-it.md)\n- [EXAONE 4.5 33B vs GLM-4.5-Air](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-4-5-air.md)\n- [EXAONE 4.5 33B vs GLM-4.7-Flash](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-4-7-flash.md)\n- [EXAONE 4.5 33B vs GLM-5.3](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3.md)\n- [EXAONE 4.5 33B vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash.md)\n- [EXAONE 4.5 33B vs gpt-oss-120b](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gpt-oss-120b.md)\n- [EXAONE 4.5 33B vs gpt-oss-20b](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-gpt-oss-20b.md)\n- [EXAONE 4.5 33B vs Granite 4.2 30B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-30b.md)\n- [EXAONE 4.5 33B vs Granite 4.2 3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-3b.md)\n- [EXAONE 4.5 33B vs Granite 4.2 8B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-granite-4-2-8b.md)\n- [EXAONE 4.5 33B vs Hy-Memory-30B-A3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-hy-memory-30b-a3b.md)\n- [EXAONE 4.5 33B vs Hy3](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-hy3.md)\n- [EXAONE 4.5 33B vs Inkling](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling.md)\n- [EXAONE 4.5 33B vs Inkling-Small](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling-small.md)\n- [EXAONE 4.5 33B vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [EXAONE 4.5 33B vs Kimi K3](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kimi-k3.md)\n- [EXAONE 4.5 33B vs Kimi K3.1 Pro](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kimi-k3-1-pro.md)\n- [EXAONE 4.5 33B vs Kolibri-1](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kolibri-1.md)\n- [EXAONE 4.5 33B vs Kronos](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kronos.md)\n- [EXAONE 4.5 33B vs Laguna S 2.1](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-s-2-1.md)\n- [EXAONE 4.5 33B vs Laguna XS 2.1](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-xs-2-1.md)\n- [EXAONE 4.5 33B vs LBS-27B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lbs-27b.md)\n- [EXAONE 4.5 33B vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm2-5-2-6b.md)\n- [EXAONE 4.5 33B vs LFM3-1.7B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-1-7b.md)\n- [EXAONE 4.5 33B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-audio-2b.md)\n- [EXAONE 4.5 33B vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-omni-2b.md)\n- [EXAONE 4.5 33B vs LFM3-VL-2B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-vl-2b.md)\n- [EXAONE 4.5 33B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-0-tiny.md)\n- [EXAONE 4.5 33B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ling-3-1-flash-1019.md)\n- [EXAONE 4.5 33B vs LongCat-2.5](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-longcat-2-5.md)\n- [EXAONE 4.5 33B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [EXAONE 4.5 33B vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-flash-rl.md)\n- [EXAONE 4.5 33B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-o-4-5.md)\n- [EXAONE 4.5 33B vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-v-4-7-1b.md)\n- [EXAONE 4.5 33B vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-v-4-7-35b-a3b.md)\n- [EXAONE 4.5 33B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm5-2b.md)\n- [EXAONE 4.5 33B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m2-5.md)\n- [EXAONE 4.5 33B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m2-7.md)\n- [EXAONE 4.5 33B vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minimax-m3-1-flash.md)\n- [EXAONE 4.5 33B vs Mistral Large 4](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mistral-large-4.md)\n- [EXAONE 4.5 33B vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-muse-glimmer-30b.md)\n- [EXAONE 4.5 33B vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nanbeige-4-2-3b.md)\n- [EXAONE 4.5 33B vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nanbeige-4-3-33b.md)\n- [EXAONE 4.5 33B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [EXAONE 4.5 33B vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [EXAONE 4.5 33B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-30b-a3b.md)\n- [EXAONE 4.5 33B vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-4b.md)\n- [EXAONE 4.5 33B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [EXAONE 4.5 33B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-super-120b-a12b.md)\n- [EXAONE 4.5 33B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-nemotron-3-ultra-550b-a55b.md)\n- [EXAONE 4.5 33B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-north-mini-code-1-0.md)\n- [EXAONE 4.5 33B vs occamy-1.0](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-occamy-1-0.md)\n- [EXAONE 4.5 33B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-olmo-3-7b-think.md)\n- [EXAONE 4.5 33B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-122b.md)\n- [EXAONE 4.5 33B vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-35b-a3b.md)\n- [EXAONE 4.5 33B vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-397b.md)\n- [EXAONE 4.5 33B vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-9b.md)\n- [EXAONE 4.5 33B vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-otel-2-0-llm-31b-it.md)\n- [EXAONE 4.5 33B vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen-agentworld-35b-a3b.md)\n- [EXAONE 4.5 33B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-30b-a3b-instruct-2507.md)\n- [EXAONE 4.5 33B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-4b-instruct-2507.md)\n- [EXAONE 4.5 33B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-0-8b.md)\n- [EXAONE 4.5 33B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-122b-a10b.md)\n- [EXAONE 4.5 33B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-2b.md)\n- [EXAONE 4.5 33B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-397b-a17b.md)\n- [EXAONE 4.5 33B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-4b.md)\n- [EXAONE 4.5 33B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-5-9b.md)\n- [EXAONE 4.5 33B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-6-27b.md)\n- [EXAONE 4.5 33B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-6-35b-a3b.md)\n- [EXAONE 4.5 33B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-8-27b.md)\n- [EXAONE 4.5 33B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-8-flash-next.md)\n- [EXAONE 4.5 33B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [EXAONE 4.5 33B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-coder-next.md)\n- [EXAONE 4.5 33B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [EXAONE 4.5 33B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-2b-instruct.md)\n- [EXAONE 4.5 33B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-30b-a3b-instruct.md)\n- [EXAONE 4.5 33B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-32b-instruct.md)\n- [EXAONE 4.5 33B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-4b-instruct.md)\n- [EXAONE 4.5 33B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwen3-vl-8b-instruct.md)\n- [EXAONE 4.5 33B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-qwopus3-8-27b-flash-v2.md)\n- [EXAONE 4.5 33B vs Recursive Flint](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-recursive-flint.md)\n- [EXAONE 4.5 33B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ripple-65b-preview.md)\n- [EXAONE 4.5 33B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-sensenova-loop-9b-preview.md)\n- [EXAONE 4.5 33B vs SmolLM3-3B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-smollm3-3b.md)\n- [EXAONE 4.5 33B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-spark-x2-6-4b.md)\n- [EXAONE 4.5 33B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-step-3-7-flash.md)\n- [EXAONE 4.5 33B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-swift-1-5-qwen3-8-27b.md)\n- [EXAONE 4.5 33B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [EXAONE 4.5 33B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-thinkingcap-qwen3-8-27b.md)\n- [EXAONE 4.5 33B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-unlimited-ocr-2.md)\n- [EXAONE 4.5 33B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-wevisone-vl-2b.md)\n- [EXAONE 4.5 33B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-wevisone-vl-4b.md)\n- [EXAONE 4.5 33B vs ZAYA1-8B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-zaya1-8b.md)\n- [Gemma 4 12B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-m-1.md)\n- [Gemma 4 26B A4B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-m-1.md)\n- [Gemma 4 31B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-m-1.md)\n- [Gemma 4 E2B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-m-1.md)\n- [Gemma 4 E4B IT vs Laguna M.1](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-m-1.md)\n- [GLM-4.5-Air vs Laguna M.1](https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-m-1.md)\n- [GLM-4.7-Flash vs Laguna M.1](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-m-1.md)\n- [GLM-5.3-Flash vs Laguna M.1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-m-1.md)\n- [GLM-5.3 vs Laguna M.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1.md)\n- [gpt-oss-120b vs Laguna M.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-m-1.md)\n- [gpt-oss-20b vs Laguna M.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-m-1.md)\n- [Granite 4.2 30B vs Laguna M.1](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-m-1.md)\n- [Granite 4.2 3B vs Laguna M.1](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-m-1.md)\n- [Granite 4.2 8B vs Laguna M.1](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-m-1.md)\n- [Hy-Memory-30B-A3B vs Laguna M.1](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-laguna-m-1.md)\n- [Hy3 vs Laguna M.1](https://www.anchorterminal.com/compare/hy3-vs-laguna-m-1.md)\n- [Inkling-Small vs Laguna M.1](https://www.anchorterminal.com/compare/inkling-small-vs-laguna-m-1.md)\n- [Inkling vs Laguna M.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Laguna M.1](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-m-1.md)\n- [Kimi K3.1 Pro vs Laguna M.1](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-laguna-m-1.md)\n- [Kimi K3 vs Laguna M.1](https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-m-1.md)\n- [Kolibri-1 vs Laguna M.1](https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-m-1.md)\n- [Kronos vs Laguna M.1](https://www.anchorterminal.com/compare/kronos-vs-laguna-m-1.md)\n- [Laguna M.1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-s-2-1.md)\n- [Laguna M.1 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-xs-2-1.md)\n- [Laguna M.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lbs-27b.md)\n- [Laguna M.1 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm2-5-2-6b.md)\n- [Laguna M.1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-1-7b.md)\n- [Laguna M.1 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-audio-2b.md)\n- [Laguna M.1 vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-omni-2b.md)\n- [Laguna M.1 vs LFM3-VL-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-vl-2b.md)\n- [Laguna M.1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-0-tiny.md)\n- [Laguna M.1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/laguna-m-1-vs-ling-3-1-flash-1019.md)\n- [Laguna M.1 vs LongCat-2.5](https://www.anchorterminal.com/compare/laguna-m-1-vs-longcat-2-5.md)\n- [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)\n- [Laguna M.1 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/laguna-m-1-vs-mimo-v2-6-flash-rl.md)\n- [Laguna M.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-o-4-5.md)\n- [Laguna M.1 vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-v-4-7-1b.md)\n- [Laguna M.1 vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm-v-4-7-35b-a3b.md)\n- [Laguna M.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-minicpm5-2b.md)\n- [Laguna M.1 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-5.md)\n- [Laguna M.1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-7.md)\n- [Laguna M.1 vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m3-1-flash.md)\n- [Laguna M.1 vs Mistral Large 4](https://www.anchorterminal.com/compare/laguna-m-1-vs-mistral-large-4.md)\n- [Laguna M.1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/laguna-m-1-vs-muse-glimmer-30b.md)\n- [Laguna M.1 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b.md)\n- [Laguna M.1 vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-3-33b.md)\n- [Laguna M.1 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [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)\n- [Laguna M.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna M.1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-nano-4b.md)\n- [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)\n- [Laguna M.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-super-120b-a12b.md)\n- [Laguna M.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Laguna M.1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/laguna-m-1-vs-north-mini-code-1-0.md)\n- [Laguna M.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.md)\n- [Laguna M.1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-m-1-vs-olmo-3-7b-think.md)\n- [Laguna M.1 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-122b.md)\n- [Laguna M.1 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-35b-a3b.md)\n- [Laguna M.1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-397b.md)\n- [Laguna M.1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-9b.md)\n- [Laguna M.1 vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/laguna-m-1-vs-otel-2-0-llm-31b-it.md)\n- [Laguna M.1 vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen-agentworld-35b-a3b.md)\n- [Laguna M.1 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Laguna M.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.md)\n- [Laguna M.1 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-0-8b.md)\n- [Laguna M.1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-122b-a10b.md)\n- [Laguna M.1 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-2b.md)\n- [Laguna M.1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b.md)\n- [Laguna M.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-4b.md)\n- [Laguna M.1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-9b.md)\n- [Laguna M.1 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-27b.md)\n- [Laguna M.1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-35b-a3b.md)\n- [Laguna M.1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b.md)\n- [Laguna M.1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next.md)\n- [Laguna M.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Laguna M.1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-coder-next.md)\n- [Laguna M.1 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Laguna M.1 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-2b-instruct.md)\n- [Laguna M.1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Laguna M.1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-32b-instruct.md)\n- [Laguna M.1 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-4b-instruct.md)\n- [Laguna M.1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-8b-instruct.md)\n- [Laguna M.1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwopus3-8-27b-flash-v2.md)\n- [Laguna M.1 vs Recursive Flint](https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint.md)\n- [Laguna M.1 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/laguna-m-1-vs-ripple-65b-preview.md)\n- [Laguna M.1 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/laguna-m-1-vs-sensenova-loop-9b-preview.md)\n- [Laguna M.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b.md)\n- [Laguna M.1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-spark-x2-6-4b.md)\n- [Laguna M.1 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.md)\n- [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)\n- [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)\n- [Laguna M.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-m-1-vs-thinkingcap-qwen3-8-27b.md)\n- [Laguna M.1 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/laguna-m-1-vs-unlimited-ocr-2.md)\n- [Laguna M.1 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b.md)\n- [Laguna M.1 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b.md)\n- [Laguna M.1 vs ZAYA1-8B](https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-11", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "EXAONE 4.5 33B vs Laguna M.1", "url": "" } ], "description": "EXAONE 4.5 33B scores 61 (C) to Laguna M.1's 56.7 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "EXAONE 4.5 33B C 61", "Laguna M.1 C 56.7", "scores" ], "h1": "EXAONE 4.5 33B vs Laguna M.1", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/exaone-4-5-33b-vs-laguna-m-1", "published": "2026-10-01", "section": "tools", "title": "EXAONE 4.5 33B vs Laguna M.1 for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1" }, "tokens": { "markdown": 9150, "slim": 830 }, "version": 1 }