{ "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": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against EXAONE 4.5 33B's 61 (C), and leads in 2 of 4 scored categories. EXAONE 4.5 33B leads on reach and agent interface.", "b": { "slug": "glm-5-3-flash", "name": "GLM-5.3-Flash", "vendor": "Z.ai", "vendorUrl": "https://z.ai", "kind": "weights", "category": "open-weights", "summary": "GLM-5.3-Flash is Z.ai's open-weight multimodal mixture-of-experts model, 320B parameters with 18B active and a 1,048,576-token context, published on Hugging Face in FP8 and BF16 under the MIT licence.", "url": "https://www.anchorterminal.com/tools/glm-5-3-flash", "markdownUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/glm-5-3-flash.json", "dns": "glm-5-3-flash.grade.anchorterminal.com", "repo": "https://huggingface.co/zai-org/GLM-5.3-Flash", "license": "MIT", "transports": [], "packages": [ { "registry": "huggingface", "name": "zai-org/GLM-5.3-Flash" }, { "registry": "huggingface", "name": "zai-org/GLM-5.3-Flash-BF16" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the MIT licence. Z.ai also sells hosted access as glm-5.3-flash on its own API, which isn't graded here. Running the weights yourself costs the hardware, 328.4 GB for the FP8 files and 642.7 GB for BF16 (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-02" }, "docsUrl": "https://huggingface.co/zai-org/GLM-5.3-Flash", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "reasoning", "tool-calling", "mit", "safetensors", "fp8", "self-hosted" ], "lastRelease": "2026-08-26", "graded": true, "anchor": { "graded": true, "score": 65.1, "grade": "B", "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": 13, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 75, "interface": 70, "reach": 60, "risk": 55, "upkeep": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-02" }, "negative": 0, "verdict": "An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.", "bestFor": "Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider", "strengths": [ "MIT weights with no use policy, downloadable with no account", "Model code in released llama.cpp b11768, vLLM 0.32.0, SGLang 0.5.22 and Transformers 5.16.1", "Safetensors only, no remote code, files in Z.ai's own organisation with a SHA-256 per shard", "1,048,576 tokens of native context and several tool calls per turn in the chat template", "Chat template changed as recently as 15 October 2026, and hosted by Z.ai and six other providers for agents without the hardware" ], "weaknesses": [ "Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists", "No safety evaluation, agent-use guidance or security contact", "Thinking is always on, and reasoning_effort only lowers it to low", "The tool-call format lives only in the chat template, with the parser named by the runtimes", "The card leaves out intended use, limitations, context length and knowledge cut-off, and no zai-org reply on discussions since 28 September" ], "agentNotes": [ "Start it with `vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47` (vLLM 0.32.0 or later, about 386 GB of GPU memory per vLLM's recipe)", "Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; calls come back as tool_call blocks with arg_key and arg_value pairs", "Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max", "Don't rely on `thinking: false` from SGLang's cookbook, since the template has no such switch and always opens a think block", "Set `clear_thinking: true` in chat use, since the default keeps earlier reasoning in the prompt", "On a 128 GB machine only third-party low-bit builds come near fitting, none of them from Z.ai" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 65.1 } ], "editorialScores": { "capability": 75, "interface": 70, "reach": 60, "risk": 55, "upkeep": 58 }, "provenanceScore": 61, "checked": { "categories": { "capability": "2026-11-02", "interface": "2026-11-02", "reach": "2026-11-02", "risk": "2026-11-02", "upkeep": "2026-11-02" }, "last": "2026-11-02", "oldest": "2026-11-02", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# vLLM 0.32.0 or later, per vLLM's recipe (FP8, about 386 GB of GPU memory)\nvllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 \\\n --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47\n# or, with llama.cpp and llama.cpp's own GGUF:\nllama-server -hf ggml-org/GLM-5.3-Flash-GGUF:Q4_K --jinja", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"zai-org/GLM-5.3-Flash\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"reasoning_effort\": \"low\"}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/glm-5-3-flash" }, "sameCompany": [ "glm-4-5-air", "glm-4-7-flash", "glm-5-3" ], "weights": { "trainedBy": "Z.ai", "params": "320B", "active": "18B", "context": 1048576, "goodFor": "Multimodal agent and coding model: text, images and video in, text out, with tool calling and always-on reasoning.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "GLM-5.3-Flash-FP4-Local", "url": "https://huggingface.co/nvidia/GLM-5.3-Flash-FP4-Local", "who": "NVIDIA", "precision": "nvfp4", "sizeGB": 177.5, "memoryGB": 256, "format": "safetensors", "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026." }, { "name": "GLM-5.3-Flash-NVFP4", "url": "https://huggingface.co/nvidia/GLM-5.3-Flash-NVFP4", "who": "NVIDIA", "precision": "nvfp4", "sizeGB": 204.4, "memoryGB": 256, "format": "safetensors", "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026." }, { "name": "ggml-org GLM-5.3-Flash-GGUF (Q4_K)", "url": "https://huggingface.co/ggml-org/GLM-5.3-Flash-GGUF", "who": "llama.cpp", "precision": "q4_k", "sizeGB": 182.03, "memoryGB": 256, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "From ggml-org, the llama.cpp project's organisation. 181.37 GB of Q4_K weights plus the 0.65 GB Q8_0 vision projector, from the Hub's model information on 10 November 2026. The 2-bit files (Q2_K 133.8 GB, Q2_K_S 110.0 GB) are below the 4-bit line and aren't listed. Recorded after the last grading, so Reach doesn't count it yet" }, { "name": "GLM-5.3-Flash", "url": "https://huggingface.co/zai-org/GLM-5.3-Flash", "who": "publisher", "precision": "fp8", "sizeGB": 328.3, "memoryGB": 512, "format": "safetensors" }, { "name": "GLM-5.3-Flash-BF16", "url": "https://huggingface.co/zai-org/GLM-5.3-Flash-BF16", "who": "publisher", "precision": "bf16", "sizeGB": 642.7, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47", "runBuild": "GLM-5.3-Flash", "checked": "2026-10-21", "minMemoryGB": 256 }, "family": { "lab": "Z.ai (Zhipu AI)", "family": "GLM-5", "url": "https://www.anchorterminal.com/open-weights/#zai", "others": [ { "name": "GLM-5", "url": "https://huggingface.co/zai-org/GLM-5", "params": "744B-A40B" }, { "name": "GLM-5.1", "url": "https://huggingface.co/zai-org/GLM-5.1", "params": "744B-A40B" }, { "name": "GLM-5.2", "url": "https://huggingface.co/zai-org/GLM-5.2", "params": "744B-A40B" }, { "name": "GLM-5.3", "url": "https://huggingface.co/zai-org/GLM-5.3", "params": "744B-A40B", "listing": "https://www.anchorterminal.com/tools/glm-5-3" } ], "olderCount": 19, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "Z.AI Co., Ltd (named in the licence's copyright line)", "domain": "z.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/zai-org/GLM-5.3-Flash/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The LICENSE file reads Copyright (c) 2026 Z.AI Co., Ltd. The registration date of z.ai couldn't be read, since the RDAP service answered 429 on 21 October 2026.", "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history. Early messages say only \"update\"; later ones say what changed (a chat template fix on 4 September, evaluation results on 7 September and 12 October, a chat template speed-up on 15 October).", "z.ai/.well-known/security.txt and docs.z.ai/.well-known/security.txt answered 404 on 21 October 2026." ], "score": 61 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.json", "live": { "slug": "glm-5-3-flash", "securityTxt": { "url": "https://z.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:09:36.154640571Z" }, "domain": { "domain": "z.ai", "registered": "2017-12-15", "source": "https://rdap.identitydigital.services/rdap/domain/z.ai", "checkedAt": "2026-11-08T15:05:18.801433245Z" }, "pages": [ { "url": "https://huggingface.co/zai-org/GLM-5.3-Flash/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:24:02.708352819Z", "changedAt": "2026-11-10T16:24:02.708352819Z", "fingerprint": "108904f1a213" } ], "updatedAt": "2026-11-10T16:24:02.708352819Z" } }, "edges": [ { "by": 15, "category": "interface", "leads": "exaone-4-5-33b", "name": "Agent interface", "reasons": { "a": "Chat template 20, chat_template.jinja in the repository (5,930 characters). Tool-calling format 25, the card's vLLM command names the parser, hermes with auto tool choice, and its agentic example calls tools from MCP servers through the OpenAI-compatible API, so declaration and return follow that API. Trained tool calling 20, the card reports agentic tool use among its language results and shows an agent run with several tool servers, and the template renders every call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, enable_thinking is on by default and the card says to set it false for the non-reasoning mode, with an example of each. Context 10, 262,144 tokens per the card's configuration table and config.json, and the card's serve commands run at that length. 20 + 25 + 20 + 0 + 10 + 10 = 85.", "b": "A Jinja chat template sits in both repositories, for 20. The tool-calling format is 10, because it is defined only by the template and the glm47 parser is named by vLLM and SGLang rather than by Z.ai. The template takes several calls in one turn, for 20. Structured output is 0, with nothing on the card and only the hosted API documented for JSON. Reasoning control is 10, a per-request budget through reasoning_effort, with the reasoning coming back in a think block, though thinking can't be turned off. Context is 10, 1,048,576 tokens native with no rotary scaling." }, "scores": { "a": 85, "b": 70 } }, { "by": 8, "category": "upkeep", "leads": "glm-5-3-flash", "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": "The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 5, a 30T-token corpus described with no sources or cut-off. The last change, a chat template speed-up on 15 October in both repositories, is within 30 days on 2 November, for 20; Z.ai's GLM-5 GitHub repository has changed only its docs since. Responsiveness is 10, as zai-org answered 14 of the 38 recent discussions others opened (26 August to 30 October), the last on 28 September, which is some but not most. Version policy is 5 for a first release, and file health is the full 10, with files and card agreeing and no broken-file report waiting as far as the research record shows." }, "scores": { "a": 50, "b": 58 } }, { "by": 5, "category": "reach", "leads": "exaone-4-5-33b", "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 earns nothing, since Z.ai's smallest build is the 328.4 GB FP8 one, about 394 GB with the fifth added, and neither Ollama nor LM Studio has a local build (both list it as cloud only). Four runtimes run it in a released version, llama.cpp, vLLM, SGLang and Transformers, for 20, while Ollama and LM Studio don't. Z.ai publishes one quantised build, FP8, for 10. The MIT licence with nothing added gives the full 15, the files download with no account or gate for 10, and Z.ai's own API plus six providers on Hugging Face serve it, for 5." }, "scores": { "a": 65, "b": 60 } }, { "by": 5, "category": "risk", "leads": "glm-5-3-flash", "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 is full, with safetensors only, no Python and no remote code needed in Transformers 5.16.1 or later. Provenance is full, files in the zai-org organisation Z.ai links from GitHub with a SHA-256 for every shard. Safety evaluation and agent guidance are 0, as nothing is published on either. Licence risk is the full 15, since MIT adds no policy, threshold or changeable terms. The security programme is 0, with no security.txt on z.ai or docs.z.ai, no SECURITY.md on GitHub and no advisories found." }, "scores": { "a": 50, "b": 55 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "LG AI Research", "b": "Z.ai", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "EXAONE AI Model License Agreement 1.2 - NC (research and education only)", "b": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-06", "b": "2026-08-26", "name": "Last release" }, { "a": "not read yet", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "none", "b": "2.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against EXAONE 4.5 33B's 61 (C), and leads in 2 of 4 scored categories. EXAONE 4.5 33B leads on reach and agent interface.", "question": "Which is better for AI agents, EXAONE 4.5 33B or GLM-5.3-Flash?" } ], "goodFor": [ { "aheadOn": [ "Reach, 65 against 60", "Agent interface, 85 against 70" ], "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": [ "Risk, 55 against 50", "Documentation and upkeep, 58 against 50" ], "also": null, "goodFor": "Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider", "slug": "glm-5-3-flash", "watchFor": "Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists" } ], "history": null, "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-glm-5-3-flash.json", "title": "Agents-A1-4B vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Apertus v1.5 8B vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Apodex-1.1-mini vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Arete-27B vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "BigBang-v1 vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Carbon-X vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Cola2 vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/cola2-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Cosmos-Reason2-2B vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Darwin-36B-Opus vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "DeepSeek-V3.2 vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "DeepSeek V4.1 Flash vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "DeepSeek-V4-Flash-0731 vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "Devstral Small 2 vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-glm-5-3-flash" }, { "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-glm-5-3-flash.json", "title": "DiffusionGemma 26B A4B IT vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3-flash" }, { "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-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-m-1.json", "title": "EXAONE 4.5 33B vs Laguna M.1", "url": "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-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-glm-5-3-flash.json", "title": "Gemma 4 12B IT vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3-flash.json", "title": "Gemma 4 26B A4B IT vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3-flash.json", "title": "Gemma 4 31B IT vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3-flash.json", "title": "Gemma 4 E2B IT vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3-flash.json", "title": "Gemma 4 E4B IT vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3-flash.json", "title": "GLM-4.5-Air vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3-flash.json", "title": "GLM-4.7-Flash vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-120b.json", "title": "GLM-5.3-Flash vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-120b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-20b.json", "title": "GLM-5.3-Flash vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-30b.json", "title": "GLM-5.3-Flash vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-3b.json", "title": "GLM-5.3-Flash vs Granite 4.2 3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-8b.json", "title": "GLM-5.3-Flash vs Granite 4.2 8B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-8b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy-memory-30b-a3b.json", "title": "GLM-5.3-Flash vs Hy-Memory-30B-A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy-memory-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy3.json", "title": "GLM-5.3-Flash vs Hy3", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling.json", "title": "GLM-5.3-Flash vs Inkling", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-small.json", "title": "GLM-5.3-Flash vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "GLM-5.3-Flash vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3.json", "title": "GLM-5.3-Flash vs Kimi K3", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3-1-pro.json", "title": "GLM-5.3-Flash vs Kimi K3.1 Pro", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3-1-pro" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kolibri-1.json", "title": "GLM-5.3-Flash vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kronos.json", "title": "GLM-5.3-Flash vs Kronos", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kronos" }, { "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-flash-vs-laguna-s-2-1.json", "title": "GLM-5.3-Flash vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-xs-2-1.json", "title": "GLM-5.3-Flash vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lbs-27b.json", "title": "GLM-5.3-Flash vs LBS-27B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm2-5-2-6b.json", "title": "GLM-5.3-Flash vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-1-7b.json", "title": "GLM-5.3-Flash vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-audio-2b.json", "title": "GLM-5.3-Flash vs LFM3-Audio-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-audio-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-omni-2b.json", "title": "GLM-5.3-Flash vs LFM3-Omni-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-omni-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-vl-2b.json", "title": "GLM-5.3-Flash vs LFM3-VL-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-0-tiny.json", "title": "GLM-5.3-Flash vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-1-flash-1019.json", "title": "GLM-5.3-Flash vs Ling-3.1-flash-1019", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-1-flash-1019" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-longcat-2-5.json", "title": "GLM-5.3-Flash vs LongCat-2.5", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-longcat-2-5" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-distill-qwen-9b.json", "title": "GLM-5.3-Flash vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-flash-rl.json", "title": "GLM-5.3-Flash vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-o-4-5.json", "title": "GLM-5.3-Flash vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-1b.json", "title": "GLM-5.3-Flash vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-35b-a3b.json", "title": "GLM-5.3-Flash vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b.json", "title": "GLM-5.3-Flash vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-5.json", "title": "GLM-5.3-Flash vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-7.json", "title": "GLM-5.3-Flash vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m3-1-flash.json", "title": "GLM-5.3-Flash vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mistral-large-4.json", "title": "GLM-5.3-Flash vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-muse-glimmer-30b.json", "title": "GLM-5.3-Flash vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nanbeige-4-2-3b.json", "title": "GLM-5.3-Flash vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nanbeige-4-3-33b.json", "title": "GLM-5.3-Flash vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "GLM-5.3-Flash vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "GLM-5.3-Flash vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-30b-a3b.json", "title": "GLM-5.3-Flash vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-4b.json", "title": "GLM-5.3-Flash vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "GLM-5.3-Flash vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-super-120b-a12b.json", "title": "GLM-5.3-Flash vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-ultra-550b-a55b.json", "title": "GLM-5.3-Flash vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-north-mini-code-1-0.json", "title": "GLM-5.3-Flash vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0.json", "title": "GLM-5.3-Flash vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.json", "title": "GLM-5.3-Flash vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-122b.json", "title": "GLM-5.3-Flash vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-35b-a3b.json", "title": "GLM-5.3-Flash vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-397b.json", "title": "GLM-5.3-Flash vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-9b.json", "title": "GLM-5.3-Flash vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-otel-2-0-llm-31b-it.json", "title": "GLM-5.3-Flash vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen-agentworld-35b-a3b.json", "title": "GLM-5.3-Flash vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-30b-a3b-instruct-2507.json", "title": "GLM-5.3-Flash vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-4b-instruct-2507.json", "title": "GLM-5.3-Flash vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-0-8b.json", "title": "GLM-5.3-Flash vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-122b-a10b.json", "title": "GLM-5.3-Flash vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-2b.json", "title": "GLM-5.3-Flash vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-397b-a17b.json", "title": "GLM-5.3-Flash vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-4b.json", "title": "GLM-5.3-Flash vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-9b.json", "title": "GLM-5.3-Flash vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-6-27b.json", "title": "GLM-5.3-Flash vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-6-35b-a3b.json", "title": "GLM-5.3-Flash vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-27b.json", "title": "GLM-5.3-Flash vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-flash-next.json", "title": "GLM-5.3-Flash vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-30b-a3b-instruct.json", "title": "GLM-5.3-Flash vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-next.json", "title": "GLM-5.3-Flash vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-omni-30b-a3b-instruct.json", "title": "GLM-5.3-Flash vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-2b-instruct.json", "title": "GLM-5.3-Flash vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-30b-a3b-instruct.json", "title": "GLM-5.3-Flash vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-32b-instruct.json", "title": "GLM-5.3-Flash vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-4b-instruct.json", "title": "GLM-5.3-Flash vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-8b-instruct.json", "title": "GLM-5.3-Flash vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwopus3-8-27b-flash-v2.json", "title": "GLM-5.3-Flash vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-recursive-flint.json", "title": "GLM-5.3-Flash vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ripple-65b-preview.json", "title": "GLM-5.3-Flash vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-sensenova-loop-9b-preview.json", "title": "GLM-5.3-Flash vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-smollm3-3b.json", "title": "GLM-5.3-Flash vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-spark-x2-6-4b.json", "title": "GLM-5.3-Flash vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-step-3-7-flash.json", "title": "GLM-5.3-Flash vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-27b.json", "title": "GLM-5.3-Flash vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-flash-next.json", "title": "GLM-5.3-Flash vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-thinkingcap-qwen3-8-27b.json", "title": "GLM-5.3-Flash vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-unlimited-ocr-2.json", "title": "GLM-5.3-Flash vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-wevisone-vl-2b.json", "title": "GLM-5.3-Flash vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-wevisone-vl-4b.json", "title": "GLM-5.3-Flash vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-zaya1-8b.json", "title": "GLM-5.3-Flash vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash.json", "title": "GLM-5.3 vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 5, "edge": "exaone-4-5-33b", "exaone-4-5-33b": 65, "glm-5-3-flash": 60, "key": "reach", "name": "Reach", "weight": 25 }, { "by": 5, "edge": "glm-5-3-flash", "exaone-4-5-33b": 50, "glm-5-3-flash": 55, "key": "risk", "name": "Risk", "weight": 20 }, { "by": 15, "edge": "exaone-4-5-33b", "exaone-4-5-33b": 85, "glm-5-3-flash": 70, "key": "interface", "name": "Agent interface", "weight": 10 }, { "by": 8, "edge": "glm-5-3-flash", "exaone-4-5-33b": 50, "glm-5-3-flash": 58, "key": "upkeep", "name": "Documentation and upkeep", "weight": 10 } ], "summary": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against EXAONE 4.5 33B's 61 (C), and leads in 2 of 4 scored categories. EXAONE 4.5 33B leads on reach and agent interface. 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.", "glm-5-3-flash": "An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "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-glm-5-3-flash.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash.min.md" }, "markdown": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against EXAONE 4.5 33B's 61 (C), and leads in 2 of 4 scored categories. EXAONE 4.5 33B leads on reach and agent interface. 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- GLM-5.3-Flash: grade B, 65.1/100, rank #18 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/glm-5-3-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/glm-5-3-flash.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- Reach, 65 against 60\n- Agent interface, 85 against 70\n\nWatch for: Research and education only. No commercial use of the model or its output\n\n### GLM-5.3-Flash (B)\n\nGood for: Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider\n\nAhead on:\n- Risk, 55 against 50\n- Documentation and upkeep, 58 against 50\n\nWatch for: Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists\n\n\n## Why the edge\n\n### Agent interface: EXAONE 4.5 33B +15\n\n- EXAONE 4.5 33B (85): Chat template 20, chat_template.jinja in the repository (5,930 characters). Tool-calling format 25, the card's vLLM command names the parser, hermes with auto tool choice, and its agentic example calls tools from MCP servers through the OpenAI-compatible API, so declaration and return follow that API. Trained tool calling 20, the card reports agentic tool use among its language results and shows an agent run with several tool servers, and the template renders every call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, enable_thinking is on by default and the card says to set it false for the non-reasoning mode, with an example of each. Context 10, 262,144 tokens per the card's configuration table and config.json, and the card's serve commands run at that length. 20 + 25 + 20 + 0 + 10 + 10 = 85.\n- GLM-5.3-Flash (70): A Jinja chat template sits in both repositories, for 20. The tool-calling format is 10, because it is defined only by the template and the glm47 parser is named by vLLM and SGLang rather than by Z.ai. The template takes several calls in one turn, for 20. Structured output is 0, with nothing on the card and only the hosted API documented for JSON. Reasoning control is 10, a per-request budget through reasoning_effort, with the reasoning coming back in a think block, though thinking can't be turned off. Context is 10, 1,048,576 tokens native with no rotary scaling.\n\n### Documentation and upkeep: GLM-5.3-Flash +8\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- GLM-5.3-Flash (58): The card covers architecture, parameters and languages and misses four of the seven items, for 8. Training data is 5, a 30T-token corpus described with no sources or cut-off. The last change, a chat template speed-up on 15 October in both repositories, is within 30 days on 2 November, for 20; Z.ai's GLM-5 GitHub repository has changed only its docs since. Responsiveness is 10, as zai-org answered 14 of the 38 recent discussions others opened (26 August to 30 October), the last on 28 September, which is some but not most. Version policy is 5 for a first release, and file health is the full 10, with files and card agreeing and no broken-file report waiting as far as the research record shows.\n\n### Reach: EXAONE 4.5 33B +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- GLM-5.3-Flash (60): Memory earns nothing, since Z.ai's smallest build is the 328.4 GB FP8 one, about 394 GB with the fifth added, and neither Ollama nor LM Studio has a local build (both list it as cloud only). Four runtimes run it in a released version, llama.cpp, vLLM, SGLang and Transformers, for 20, while Ollama and LM Studio don't. Z.ai publishes one quantised build, FP8, for 10. The MIT licence with nothing added gives the full 15, the files download with no account or gate for 10, and Z.ai's own API plus six providers on Hugging Face serve it, for 5.\n\n### Risk: GLM-5.3-Flash +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- GLM-5.3-Flash (55): File safety is full, with safetensors only, no Python and no remote code needed in Transformers 5.16.1 or later. Provenance is full, files in the zai-org organisation Z.ai links from GitHub with a SHA-256 for every shard. Safety evaluation and agent guidance are 0, as nothing is published on either. Licence risk is the full 15, since MIT adds no policy, threshold or changeable terms. The security programme is 0, with no security.txt on z.ai or docs.z.ai, no SECURITY.md on GitHub and no advisories found.\n\n## Score by category\n\n| Category | Weight | EXAONE 4.5 33B | GLM-5.3-Flash | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 60 | EXAONE 4.5 33B +5 |\n| Risk | 20% (20 this run) | 50 | 55 | GLM-5.3-Flash +5 |\n| Agent interface | 10% (10 this run) | 85 | 70 | EXAONE 4.5 33B +15 |\n| Documentation and upkeep | 10% (10 this run) | 50 | 58 | GLM-5.3-Flash +8 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **65.1 · B** | |\n\n## Facts side by side\n\n| Fact | EXAONE 4.5 33B | GLM-5.3-Flash |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | LG AI Research | Z.ai |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | EXAONE AI Model License Agreement 1.2 - NC (research and education only) | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-06 | 2026-08-26 |\n| Terms last updated | not read yet | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | none | 2.8/5 (4) |\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**GLM-5.3-Flash.** An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.\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### GLM-5.3-Flash\n\n1. Start it with `vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47` (vLLM 0.32.0 or later, about 386 GB of GPU memory per vLLM's recipe)\n2. Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; calls come back as tool_call blocks with arg_key and arg_value pairs\n3. Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max\n4. Don't rely on `thinking: false` from SGLang's cookbook, since the template has no such switch and always opens a think block\n5. Set `clear_thinking: true` in chat use, since the default keeps earlier reasoning in the prompt\n6. On a 128 GB machine only third-party low-bit builds come near fitting, none of them from Z.ai\n\n## Questions\n\n### Which is better for AI agents, EXAONE 4.5 33B or GLM-5.3-Flash?\n\nGLM-5.3-Flash scores 65.1 (B) on agent readiness against EXAONE 4.5 33B's 61 (C), and leads in 2 of 4 scored categories. EXAONE 4.5 33B leads on reach and agent interface.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash.json, and with the fewest tokens: https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"exaone-4-5-33b\", \"b\": \"glm-5-3-flash\"}`. From a terminal: `anchor compare exaone-4-5-33b glm-5-3-flash`\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/glm-5-3-flash.json\n\n## Other comparisons with EXAONE 4.5 33B or GLM-5.3-Flash\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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/carbon-x-vs-glm-5-3-flash.md)\n- [Cola2 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/cola2-vs-exaone-4-5-33b.md)\n- [Cola2 vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/cola2-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/devstral-small-2-vs-glm-5-3-flash.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3-flash.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 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 M.1](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-m-1.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 GLM-5.3-Flash](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3-flash.md)\n- [Gemma 4 26B A4B IT vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3-flash.md)\n- [Gemma 4 31B IT vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3-flash.md)\n- [Gemma 4 E2B IT vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3-flash.md)\n- [Gemma 4 E4B IT vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3-flash.md)\n- [GLM-4.5-Air vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3-flash.md)\n- [GLM-4.7-Flash vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3-flash.md)\n- [GLM-5.3-Flash vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-120b.md)\n- [GLM-5.3-Flash vs gpt-oss-20b](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-gpt-oss-20b.md)\n- [GLM-5.3-Flash vs Granite 4.2 30B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-30b.md)\n- [GLM-5.3-Flash vs Granite 4.2 3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-3b.md)\n- [GLM-5.3-Flash vs Granite 4.2 8B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-granite-4-2-8b.md)\n- [GLM-5.3-Flash vs Hy-Memory-30B-A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy-memory-30b-a3b.md)\n- [GLM-5.3-Flash vs Hy3](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy3.md)\n- [GLM-5.3-Flash vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling.md)\n- [GLM-5.3-Flash vs Inkling-Small](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-small.md)\n- [GLM-5.3-Flash vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [GLM-5.3-Flash vs Kimi K3](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3.md)\n- [GLM-5.3-Flash vs Kimi K3.1 Pro](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3-1-pro.md)\n- [GLM-5.3-Flash vs Kolibri-1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kolibri-1.md)\n- [GLM-5.3-Flash vs Kronos](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kronos.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-Flash vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1.md)\n- [GLM-5.3-Flash vs Laguna XS 2.1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-xs-2-1.md)\n- [GLM-5.3-Flash vs LBS-27B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lbs-27b.md)\n- [GLM-5.3-Flash vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm2-5-2-6b.md)\n- [GLM-5.3-Flash vs LFM3-1.7B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-1-7b.md)\n- [GLM-5.3-Flash vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-audio-2b.md)\n- [GLM-5.3-Flash vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-omni-2b.md)\n- [GLM-5.3-Flash vs LFM3-VL-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-vl-2b.md)\n- [GLM-5.3-Flash vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-0-tiny.md)\n- [GLM-5.3-Flash vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ling-3-1-flash-1019.md)\n- [GLM-5.3-Flash vs LongCat-2.5](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-longcat-2-5.md)\n- [GLM-5.3-Flash vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-distill-qwen-9b.md)\n- [GLM-5.3-Flash vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-flash-rl.md)\n- [GLM-5.3-Flash vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-o-4-5.md)\n- [GLM-5.3-Flash vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-1b.md)\n- [GLM-5.3-Flash vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-35b-a3b.md)\n- [GLM-5.3-Flash vs MiniCPM5-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm5-2b.md)\n- [GLM-5.3-Flash vs MiniMax-M2.5](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-5.md)\n- [GLM-5.3-Flash vs MiniMax-M2.7](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-7.md)\n- [GLM-5.3-Flash vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m3-1-flash.md)\n- [GLM-5.3-Flash vs Mistral Large 4](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mistral-large-4.md)\n- [GLM-5.3-Flash vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-muse-glimmer-30b.md)\n- [GLM-5.3-Flash vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nanbeige-4-2-3b.md)\n- [GLM-5.3-Flash vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nanbeige-4-3-33b.md)\n- [GLM-5.3-Flash vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [GLM-5.3-Flash vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [GLM-5.3-Flash vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-30b-a3b.md)\n- [GLM-5.3-Flash vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-4b.md)\n- [GLM-5.3-Flash vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [GLM-5.3-Flash vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-super-120b-a12b.md)\n- [GLM-5.3-Flash vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-nemotron-3-ultra-550b-a55b.md)\n- [GLM-5.3-Flash vs North Mini Code 1.0](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-north-mini-code-1-0.md)\n- [GLM-5.3-Flash vs occamy-1.0](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0.md)\n- [GLM-5.3-Flash vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.md)\n- [GLM-5.3-Flash vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-122b.md)\n- [GLM-5.3-Flash vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-35b-a3b.md)\n- [GLM-5.3-Flash vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-397b.md)\n- [GLM-5.3-Flash vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-9b.md)\n- [GLM-5.3-Flash vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-otel-2-0-llm-31b-it.md)\n- [GLM-5.3-Flash vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen-agentworld-35b-a3b.md)\n- [GLM-5.3-Flash vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-30b-a3b-instruct-2507.md)\n- [GLM-5.3-Flash vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-4b-instruct-2507.md)\n- [GLM-5.3-Flash vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-0-8b.md)\n- [GLM-5.3-Flash vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-122b-a10b.md)\n- [GLM-5.3-Flash vs Qwen3.5-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-2b.md)\n- [GLM-5.3-Flash vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-397b-a17b.md)\n- [GLM-5.3-Flash vs Qwen3.5-4B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-4b.md)\n- [GLM-5.3-Flash vs Qwen3.5-9B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-5-9b.md)\n- [GLM-5.3-Flash vs Qwen3.6-27B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-6-27b.md)\n- [GLM-5.3-Flash vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-6-35b-a3b.md)\n- [GLM-5.3-Flash vs Qwen3.8-27B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-27b.md)\n- [GLM-5.3-Flash vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-8-flash-next.md)\n- [GLM-5.3-Flash vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-30b-a3b-instruct.md)\n- [GLM-5.3-Flash vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-coder-next.md)\n- [GLM-5.3-Flash vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-omni-30b-a3b-instruct.md)\n- [GLM-5.3-Flash vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-2b-instruct.md)\n- [GLM-5.3-Flash vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-30b-a3b-instruct.md)\n- [GLM-5.3-Flash vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-32b-instruct.md)\n- [GLM-5.3-Flash vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-4b-instruct.md)\n- [GLM-5.3-Flash vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwen3-vl-8b-instruct.md)\n- [GLM-5.3-Flash vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-qwopus3-8-27b-flash-v2.md)\n- [GLM-5.3-Flash vs Recursive Flint](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-recursive-flint.md)\n- [GLM-5.3-Flash vs Ripple-65B Preview](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ripple-65b-preview.md)\n- [GLM-5.3-Flash vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-sensenova-loop-9b-preview.md)\n- [GLM-5.3-Flash vs SmolLM3-3B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-smollm3-3b.md)\n- [GLM-5.3-Flash vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-spark-x2-6-4b.md)\n- [GLM-5.3-Flash vs Step 3.7 Flash](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-step-3-7-flash.md)\n- [GLM-5.3-Flash vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-27b.md)\n- [GLM-5.3-Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-5.3-Flash vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-thinkingcap-qwen3-8-27b.md)\n- [GLM-5.3-Flash vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-unlimited-ocr-2.md)\n- [GLM-5.3-Flash vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-wevisone-vl-2b.md)\n- [GLM-5.3-Flash vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-wevisone-vl-4b.md)\n- [GLM-5.3-Flash vs ZAYA1-8B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-zaya1-8b.md)\n- [GLM-5.3 vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash.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 GLM-5.3-Flash", "url": "" } ], "description": "GLM-5.3-Flash scores 65.1 (B) to EXAONE 4.5 33B's 61 (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", "GLM-5.3-Flash B 65.1", "scores" ], "h1": "EXAONE 4.5 33B vs GLM-5.3-Flash", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/exaone-4-5-33b-vs-glm-5-3-flash", "published": "2026-10-01", "section": "tools", "title": "EXAONE 4.5 33B vs GLM-5.3-Flash for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-glm-5-3-flash" }, "tokens": { "markdown": 9650, "slim": 830 }, "version": 1 }