{
  "data": {
    "a": {
      "slug": "kronos",
      "name": "Kronos",
      "vendor": "Yu Shi (shiyu-coder, NeoQuasar), Tsinghua University",
      "vendorUrl": "https://github.com/shiyu-coder/Kronos",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Kronos is an open-weight family of small forecasting models for financial candlestick (K-line) series, from Tsinghua University researchers. It reads open, high, low, close, volume and amount bars with timestamps and generates forecast bars, under MIT.",
      "url": "https://www.anchorterminal.com/tools/kronos",
      "markdownUrl": "https://www.anchorterminal.com/tools/kronos.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/kronos.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/kronos.json",
      "dns": "kronos.grade.anchorterminal.com",
      "repo": "https://github.com/shiyu-coder/Kronos",
      "license": "MIT",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "NeoQuasar/Kronos-mini"
        },
        {
          "registry": "huggingface",
          "name": "NeoQuasar/Kronos-small"
        },
        {
          "registry": "huggingface",
          "name": "NeoQuasar/Kronos-base"
        },
        {
          "registry": "huggingface",
          "name": "NeoQuasar/Kronos-Tokenizer-base"
        },
        {
          "registry": "huggingface",
          "name": "NeoQuasar/Kronos-Tokenizer-2k"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for all five NeoQuasar repositories, and the code is in a public GitHub repository (checked 2026-10-25).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the MIT licence named in each card's metadata and in the GitHub repository's LICENSE. Nobody sells per-call access and no inference provider serves it. Running it costs the hardware, 0.03 GB for Kronos-mini with its tokeniser and 0.43 GB for Kronos-base with its tokeniser, in FP32 (checked 2026-10-25).",
      "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 2026-10-25).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 43000,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-25"
      },
      "docsUrl": "https://github.com/shiyu-coder/Kronos",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "time-series",
        "forecasting",
        "finance",
        "candlestick",
        "k-line",
        "mit",
        "safetensors",
        "self-hosted"
      ],
      "lastRelease": "2026-04-13",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 55.2,
        "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": 91,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 60,
          "reach": 55,
          "risk": 50,
          "upkeep": 61
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-04"
        },
        "negative": 0,
        "verdict": "Forecasts the next price bars from a history of up to 512 candlestick bars. Every size fits in under 0.5 GB and runs on a CPU, but only through the publisher's own Python package. Nobody has benchmarked it independently, its quickstart data was deleted from the repository, and the publisher hasn't replied since November 2025.",
        "bestFor": "Agents that need a quick local forecast or synthetic sample of a candlestick series on modest hardware, for research or as one input among others.",
        "strengths": [
          "MIT with nothing added, ungated, safetensors only with SHA-256 hashes",
          "Under 0.5 GB for every public size, so it runs on a CPU, Apple MPS or a small GPU",
          "Input and output documented as plain DataFrames, with batch prediction over many series",
          "Training data listed by exchange with observation counts, filtering and a June 2024 end"
        ],
        "weaknesses": [
          "Runs only through the publisher's own PyTorch code from GitHub, in no named runtime and with no quantised build",
          "A 512-bar context for the small and base sizes, and the mean forecast only, without quantiles",
          "The sample data the quickstart reads was deleted on 13 April 2026, and the cards' licence link points at a missing branch",
          "No safety results, no security contact and no publisher reply in its Hugging Face discussions since November 2025",
          "The publisher's forecasting results come from its own paper, with no independent benchmark found"
        ],
        "agentNotes": [
          "Clone https://github.com/shiyu-coder/Kronos and `pip install -r requirements.txt`, then load `Kronos.from_pretrained(\"NeoQuasar/Kronos-small\")` and `KronosTokenizer.from_pretrained(\"NeoQuasar/Kronos-Tokenizer-base\")` and wrap them in KronosPredictor",
          "Pair Kronos-mini with Kronos-Tokenizer-2k and Kronos-small or Kronos-base with Kronos-Tokenizer-base, the cards' pairing",
          "The examples read examples/data/XSHG_5min_600977.csv, which no longer exists; point them at tests/data/regression_input.csv, 2,500 five-minute bars",
          "Keep the lookback at or under max_context, 512 bars, and pass the future timestamps you want as y_timestamp, since the calendar fields come from them",
          "Raise sample_count for a steadier forecast, but expect only the mean back; call the lower-level auto_regressive_inference yourself if you need the paths",
          "Treat forecasts as model output to check, not signals; the README says its own backtest pipeline isn't a production trading system"
        ],
        "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": 55.2
          }
        ],
        "editorialScores": {
          "interface": 60,
          "reach": 55,
          "risk": 50,
          "upkeep": 61
        },
        "provenanceScore": 50,
        "checked": {
          "categories": {
            "interface": "2026-11-04",
            "reach": "2026-11-04",
            "risk": "2026-11-04",
            "upkeep": "2026-11-04"
          },
          "last": "2026-11-04",
          "oldest": "2026-11-04",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "git clone https://github.com/shiyu-coder/Kronos \u0026\u0026 cd Kronos\npip install -r requirements.txt   # Python 3.10+, PyTorch 2.0+\npython - \u003c\u003c'EOF'\nimport pandas as pd\nfrom model import Kronos, KronosTokenizer, KronosPredictor\ntok = KronosTokenizer.from_pretrained(\"NeoQuasar/Kronos-Tokenizer-base\")\nmodel = Kronos.from_pretrained(\"NeoQuasar/Kronos-small\")\np = KronosPredictor(model, tok, max_context=512)   # picks cuda, mps or cpu\ndf = pd.read_csv(\"tests/data/regression_input.csv\", parse_dates=[\"timestamps\"])\nx, y = df.iloc[:400], df[\"timestamps\"].iloc[400:520]\ncols = [\"open\", \"high\", \"low\", \"close\", \"volume\", \"amount\"]\nprint(p.predict(df=x[cols], x_timestamp=x[\"timestamps\"], y_timestamp=y, pred_len=120, T=1.0, top_p=0.9, sample_count=1).head())\nEOF"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/kronos"
      },
      "weights": {
        "trainedBy": "Yu Shi and co-authors, Tsinghua University",
        "params": "4.1M to 102.3M",
        "context": 512,
        "goodFor": "Forecasting the next bars of a financial candlestick series, or sampling synthetic ones, on any machine, from a short history of open, high, low, close, volume and amount.",
        "runtimes": [],
        "builds": [
          {
            "name": "Kronos-mini",
            "url": "https://huggingface.co/NeoQuasar/Kronos-mini",
            "who": "publisher",
            "precision": "fp32",
            "sizeGB": 0.03,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "PyTorch"
            ],
            "note": "32,304,418 bytes with Kronos-Tokenizer-2k, which it needs (16,451,361 for the model repository and 15,853,057 for the tokeniser). 2,048-bar context per the card"
          },
          {
            "name": "Kronos-small",
            "url": "https://huggingface.co/NeoQuasar/Kronos-small",
            "who": "publisher",
            "precision": "fp32",
            "sizeGB": 0.11,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "PyTorch"
            ],
            "note": "114,844,309 bytes with Kronos-Tokenizer-base (98,991,258 and 15,853,051). The model the card's and README's examples load"
          },
          {
            "name": "Kronos-base",
            "url": "https://huggingface.co/NeoQuasar/Kronos-base",
            "who": "publisher",
            "precision": "fp32",
            "sizeGB": 0.43,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "PyTorch"
            ],
            "note": "425,127,647 bytes with Kronos-Tokenizer-base (409,274,596 and 15,853,051). The largest public size"
          }
        ],
        "run": "git clone https://github.com/shiyu-coder/Kronos \u0026\u0026 cd Kronos \u0026\u0026 pip install -r requirements.txt, then in Python: KronosPredictor(Kronos.from_pretrained(\"NeoQuasar/Kronos-small\"), KronosTokenizer.from_pretrained(\"NeoQuasar/Kronos-Tokenizer-base\"), max_context=512).predict(df=..., x_timestamp=..., y_timestamp=..., pred_len=120)",
        "runBuild": "Kronos-small",
        "checked": "2026-10-25",
        "minMemoryGB": 8
      },
      "area": "models",
      "provenance": {
        "legalEntity": "No company. Yu Shi publishes it from the GitHub account shiyu-coder and the Hugging Face user account NeoQuasar (named ShiYu), with co-authors at Tsinghua University per the paper",
        "domain": "github.com",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-25",
        "notes": [
          "NeoQuasar is a Hugging Face user account (fullname ShiYu), not an organisation. The GitHub README and the paper link it, so it's the publisher's own account.",
          "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.",
          "No SECURITY.md, security contact or disclosure policy was found in the GitHub repository or on the cards.",
          "No changelog and no GitHub releases. The README's News section has three dated items, the last on 10 November 2025."
        ],
        "score": 50
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/kronos.json",
      "live": {
        "slug": "kronos",
        "githubStars": 47440,
        "securityTxt": {
          "url": "https://github.com/.well-known/security.txt",
          "state": "valid",
          "expires": "2026-12-10T16:07:34z",
          "checkedAt": "2026-11-10T16:07:34.352094479Z"
        },
        "domain": {
          "domain": "github.com",
          "registered": "2007-10-09",
          "source": "https://rdap.verisign.com/com/v1/domain/github.com",
          "checkedAt": "2026-11-08T15:13:35.342098516Z"
        },
        "github": {
          "repo": "shiyu-coder/kronos",
          "checkedAt": "2026-11-09T10:02:46.822302547Z",
          "stars": 47378,
          "archived": false,
          "issuesEnabled": true,
          "pushedAt": "2026-04-13T12:38:49Z",
          "openIssues": 221,
          "openPRs": 77,
          "issuesOpened90d": 17,
          "issuesClosed90d": 3,
          "prsMerged90d": 0,
          "replies": {
            "sampled": 25,
            "unanswered": 21,
            "medianDays": 0.5
          }
        },
        "updatedAt": "2026-11-10T16:07:34.352094479Z"
      }
    },
    "answer": "MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against Kronos's 55.2 (C), and leads in every scored category.",
    "b": {
      "slug": "minicpm-v-4-7-35b-a3b",
      "name": "MiniCPM-V 4.7 35B-A3B",
      "vendor": "OpenBMB",
      "vendorUrl": "https://openbmb.cn",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniCPM-V 4.7 35B-A3B is OpenBMB's open-weight vision-language model, a 35B mixture of experts with about 3B active per token that reads images and video, calls tools, and ships in BF16, FP8, 4-bit and GGUF builds under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b",
      "markdownUrl": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minicpm-v-4-7-35b-a3b.json",
      "dns": "minicpm-v-4-7-35b-a3b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-gguf"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-FP8"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-AWQ"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-GPTQ"
        },
        {
          "registry": "huggingface",
          "name": "openbmb/MiniCPM-V-4.7-35B-A3B-int4"
        },
        {
          "registry": "ollama",
          "name": "openbmb/minicpm-v4.7:35b-a3b"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The main repository and OpenBMB's GGUF, FP8, AWQ, GPTQ and int4 repositories are not gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, named in the card's metadata and carried as a LICENSE file in OpenBMB's GitHub repository. Running it yourself costs the hardware, about 70 GB for the BF16 files, 22.7 GB for the 4-bit safetensors builds or 18.7 GB for the IQ4_XS GGUF (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://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "video",
        "on-device",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "gguf",
        "fp8",
        "awq",
        "gptq",
        "self-hosted"
      ],
      "lastRelease": "2026-11-03",
      "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": 61,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 90,
          "risk": 55,
          "upkeep": 68
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it.",
        "bestFor": "Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence",
        "strengths": [
          "Fits about 24 GB from OpenBMB's IQ4_XS GGUF and 32 GB from its Q4_K_M, 4-bit safetensors or Ollama builds",
          "Runs in llama.cpp, Ollama, vLLM, SGLang and Transformers from their released versions, with llama.cpp's own guide",
          "Plain Apache 2.0, ungated, safetensors and GGUF only, no remote code",
          "OpenBMB answered 8 of 12 discussions and dates its releases",
          "Images, several images and video in one model, with thinking off by default"
        ],
        "weaknesses": [
          "No limitations section, safety results, agent-use guidance or security contact",
          "Training data isn't described, and the card gives no context length, languages or knowledge cut-off",
          "The card shows a tool-calling request but not the reply, and names no parser",
          "OpenBMB's cookbook is behind the runtimes on SGLang and Ollama support",
          "No inference provider is mapped on Hugging Face"
        ],
        "agentNotes": [
          "Start it with `llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja`, or `ollama run openbmb/minicpm-v4.7:35b-a3b`",
          "For image input in llama.cpp add `mmproj-model-f16.gguf`, or the 4x projector for more visual detail at a higher cost",
          "The GGUF files at the repository root have thinking off. Use the files in `thinking/` when you want the trace",
          "With Transformers pass `enable_thinking` to `apply_chat_template`, and pass `downsample_mode` to both `apply_chat_template` and `generate`",
          "Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends",
          "Check tool calls in your runtime first, since the card names no parser. The template uses the Qwen3.5 function-block format",
          "Validate JSON output yourself, since structured output isn't documented"
        ],
        "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": 70,
          "reach": 90,
          "risk": 55,
          "upkeep": 68
        },
        "provenanceScore": 58,
        "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": "ollama run openbmb/minicpm-v4.7:35b-a3b\n# or, with llama.cpp and OpenBMB's own GGUF:\nllama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja\n# or, with Transformers' server, as the card gives it:\npip install \"transformers[serving]\u003e=5.18.0\"\ntransformers serve openbmb/MiniCPM-V-4.7-35B-A3B --port 8000 --host 0.0.0.0",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"openbmb/minicpm-v4.7:35b-a3b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minicpm-v-4-7-35b-a3b"
      },
      "sameCompany": [
        "minicpm-v-4-7-1b",
        "minicpm-o-4-5",
        "minicpm5-2b"
      ],
      "weights": {
        "trainedBy": "OpenBMB (ModelBest and Tsinghua NLP Lab)",
        "builtOn": "Qwen3.5 and Qwen3.6 as the language backbone and SigLIP2 as the vision module, per the card's acknowledgements. Not declared in the metadata. The text config is qwen3_5_moe_text with 40 layers and 256 experts",
        "params": "35.2B (3B active)",
        "context": 262144,
        "goodFor": "Vision-language mixture-of-experts model for images, several images and video, with tool calling and thinking off by default, fast for its size with about 3B active parameters.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "MiniCPM-V-4_7-35B-A3B-IQ4_XS",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-IQ4_XS.gguf",
            "who": "publisher",
            "precision": "iq4_xs",
            "sizeGB": 18.7,
            "memoryGB": 24,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "The smallest file at 4 bits. IQ3_M and IQ3_XS (15.4 and 14.5 GB) are below the 4-bit line and are not listed"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-AWQ",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-AWQ",
            "who": "publisher",
            "precision": "w4a16",
            "sizeGB": 22.7,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "AWQ, 4-bit weights with 16-bit activations"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-GPTQ",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-GPTQ",
            "who": "publisher",
            "precision": "w4a16",
            "sizeGB": 22.7,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "GPTQ, 4-bit weights with 16-bit activations"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-int4",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-int4",
            "who": "publisher",
            "precision": "int4",
            "sizeGB": 22.7,
            "memoryGB": 32,
            "format": "safetensors",
            "runsOn": [
              "vLLM"
            ],
            "note": "Listed on the card with the FP8 build under llm-compressor's FP8 and INT4 guide"
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q5_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q5_K_M.gguf",
            "who": "publisher",
            "precision": "q5_k_m",
            "sizeGB": 24.7,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q4_K_M",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 21.2,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ],
            "note": "Add mmproj-model-f16.gguf (1.1 GB) or mmproj-model-f16-4x.gguf (0.9 GB) for image input. The same file with thinking on is in the thinking/ folder"
          },
          {
            "name": "ollama openbmb/minicpm-v4.7:35b-a3b",
            "url": "https://ollama.com/openbmb/minicpm-v4.7",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 22,
            "memoryGB": 32,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "OpenBMB's own namespace on Ollama, not Ollama's library. Q4_K_M, 22 GB as the tags page shows it, with q8_0 (38 GB) and fp16 (70 GB) tags beside it"
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B-FP8",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 38,
            "memoryGB": 48,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q8_0",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 36.9,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-Q6_K",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-Q6_K.gguf",
            "who": "publisher",
            "precision": "q6_k",
            "sizeGB": 28.5,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          },
          {
            "name": "MiniCPM-V-4.7-35B-A3B",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 70.4,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)",
              "Transformers"
            ]
          },
          {
            "name": "MiniCPM-V-4_7-35B-A3B-F16",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf/blob/main/MiniCPM-V-4_7-35B-A3B-F16.gguf",
            "who": "publisher",
            "precision": "f16",
            "sizeGB": 69.4,
            "memoryGB": 96,
            "format": "gguf",
            "runsOn": [
              "llama.cpp (Vulkan)",
              "llama.cpp (ROCm)"
            ]
          }
        ],
        "run": "llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja",
        "runBuild": "MiniCPM-V-4_7-35B-A3B-Q4_K_M",
        "checked": "2026-11-10",
        "minMemoryGB": 24
      },
      "family": {
        "lab": "OpenBMB (MiniCPM)",
        "family": "MiniCPM-V 4",
        "url": "https://www.anchorterminal.com/open-weights/#openbmb",
        "others": [
          {
            "name": "MiniCPM-V 4.7 1B",
            "url": "https://huggingface.co/openbmb/MiniCPM-V-4.7-1B",
            "params": "1.55B (1,554,476,272 per the safetensors count)",
            "listing": "https://www.anchorterminal.com/tools/minicpm-v-4-7-1b"
          }
        ],
        "olderCount": 22
      },
      "area": "models",
      "provenance": {
        "legalEntity": "OpenBMB (named in the GitHub LICENSE's copyright line)",
        "domain": "openbmb.cn",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/OpenBMB/MiniCPM-V",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "No legal entity is named on the card. OpenBMB is the open-source organisation of ModelBest and Tsinghua University's NLP lab, as the MiniCPM5-2B listing records.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the GitHub README's dated news list (the release on 12 October 2026, DSpark heads on 15 October) and the repositories' commit messages, which say what changed.",
          "openbmb.cn/.well-known/security.txt returns 404 and github.com/OpenBMB/MiniCPM-V has no SECURITY.md.",
          "unchecked: the domain's registration date."
        ],
        "score": 58
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.json"
    },
    "edges": [
      {
        "by": 35,
        "category": "reach",
        "leads": "minicpm-v-4-7-35b-a3b",
        "name": "Reach",
        "reasons": {
          "a": "Memory 30, the publisher's Kronos-mini with its tokeniser is 0.03 GB and even Kronos-base is 0.43 GB in FP32. Runtimes 0, it runs only through the publisher's own PyTorch package from GitHub, and none of the six named runtimes supports it. Builds 0, FP32 safetensors only. Terms 15, MIT with nothing added. Download 10, nothing is gated. Hosted 0, no inference provider or publisher API serves it (provider mapping still empty on 4 November).",
          "b": "Memory 25, since OpenBMB's IQ4_XS GGUF with its vision projector is 19.6 GB and needs about 23.6 GB with the fifth added, which fits 24 GB, while its Q4_K_M GGUF, 4-bit safetensors builds and Ollama entry need 32 GB. Runtimes 25, from vLLM 0.33.0, SGLang 0.5.23, Transformers 5.18.0 and later, llama.cpp's own MiniCPM-V 4.7 support and OpenBMB's entry on Ollama. Builds 15, OpenBMB publishes FP8, three 4-bit safetensors builds and GGUF. Terms 15, Apache 2.0 with nothing added. Download 10, nothing is gated. Hosted 0, no inference provider is mapped. 25 + 25 + 15 + 15 + 10 + 0 = 90."
        },
        "scores": {
          "a": 55,
          "b": 90
        }
      },
      {
        "by": 10,
        "category": "interface",
        "leads": "minicpm-v-4-7-35b-a3b",
        "name": "Agent interface",
        "reasons": {
          "a": "Read for a forecasting model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. The card documents the DataFrame and timestamps it takes and the DataFrame it returns, and the publisher's KronosPredictor builds and parses them (25). It was trained on six K-line fields with calendar fields, one series per forecast (10). Output is a typed DataFrame indexed by the requested timestamps, the mean of the sampled paths (15). The input format is given only as code (10). Reasoning control and context score 0, with no reasoning and a 512-bar context (2,048 for Kronos-mini).",
          "b": "Chat template 20, a Jinja file in the repository. Tool-calling format 10, the card shows the tools array going in but not the call coming back, and names no parser. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, enable_thinking per request, off by default, with the trace between markers. Context 10, 262,144 tokens native."
        },
        "scores": {
          "a": 60,
          "b": 70
        }
      },
      {
        "by": 7,
        "category": "upkeep",
        "leads": "minicpm-v-4-7-35b-a3b",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 11, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 20, the paper lists every exchange with asset and observation counts, the filtering and a June 2024 end. Last change 5, the reference code on 13 April 2026 (still the newest commit on 4 November, 205 days) and the Hub repositories on 9 September 2025. Responsiveness 20, the publisher answered 10 of 18 Hugging Face discussions (recounted by script on 4 November), though none since 24 November 2025, and the seven opened since April 2026 have no reply from it. Version policy 5, a first release. File health 0, the cards point to example data the repository has deleted and to licence and requirements links on a branch that doesn't exist.",
          "b": "Model card 8, it covers intended use, architecture and parameters but not limitations, context length, languages or a knowledge cut-off. Training data 0, none described. Last change 20, a commit on 3 November 2026. Responsiveness 20, OpenBMB answered 8 of 12 discussions. Version policy 10, earlier versions keep their repositories and the changes are dated and described. File health 10, the files agree. 8 + 0 + 20 + 20 + 10 + 10 = 68."
        },
        "scores": {
          "a": 61,
          "b": 68
        }
      },
      {
        "by": 5,
        "category": "risk",
        "leads": "minicpm-v-4-7-35b-a3b",
        "name": "Risk",
        "reasons": {
          "a": "File safety 15, safetensors only, but the only documented loading path is the publisher's Python package in place of a runtime. Provenance 15, the files are in the NeoQuasar account the publisher's README links, with SHA-256 hashes. Safety evaluation 0, none published. Agent guidance 5, the README's general cautions that the fine-tuning pipeline isn't a production trading system. Licence risk 15, plain MIT; the broken licence link is charged to file health. Security programme 0, no reporting route found.",
          "b": "File safety 25, safetensors and GGUF only, no Python in the main repository and no remote code needed. Provenance 15, the files come from the openbmb organisation OpenBMB's GitHub README links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published on either, and the card has no limitations section. Licence risk 15, plain Apache 2.0. Security programme 0, no security.txt or SECURITY.md."
        },
        "scores": {
          "a": 50,
          "b": 55
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Yu Shi (shiyu-coder, NeoQuasar), Tsinghua University",
        "b": "OpenBMB",
        "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": "MIT",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-04-13",
        "b": "2026-11-03",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "43k stars",
        "b": "none",
        "name": "Popularity"
      }
    ],
    "faq": [
      {
        "answer": "MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against Kronos's 55.2 (C), and leads in every scored category.",
        "question": "Which is better for AI agents, Kronos or MiniCPM-V 4.7 35B-A3B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Agents that need a quick local forecast or synthetic sample of a candlestick series on modest hardware, for research or as one input among others.",
        "slug": "kronos",
        "watchFor": "Runs only through the publisher's own PyTorch code from GitHub, in no named runtime and with no quantised build"
      },
      {
        "aheadOn": [
          "Reach, 90 against 55",
          "Risk, 55 against 50",
          "Agent interface, 70 against 60",
          "Documentation and upkeep, 68 against 61"
        ],
        "also": null,
        "goodFor": "Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence",
        "slug": "minicpm-v-4-7-35b-a3b",
        "watchFor": "No limitations section, safety results, agent-use guidance or security contact"
      }
    ],
    "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-kronos.json",
        "title": "Agents-A1-4B vs Kronos",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Agents-A1-4B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-kronos.json",
        "title": "Apertus v1.5 8B vs Kronos",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Apertus v1.5 8B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-kronos.json",
        "title": "Apodex-1.1-mini vs Kronos",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Apodex-1.1-mini vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-kronos.json",
        "title": "Arete-27B vs Kronos",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Arete-27B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-kronos.json",
        "title": "BigBang-v1 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "BigBang-v1 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-kronos.json",
        "title": "Carbon-X vs Kronos",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Carbon-X vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-kronos.json",
        "title": "Cola2 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Cola2 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kronos.json",
        "title": "Cosmos-Reason2-2B vs Kronos",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Cosmos-Reason2-2B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kronos.json",
        "title": "Darwin-36B-Opus vs Kronos",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Darwin-36B-Opus vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kronos.json",
        "title": "DeepSeek-V3.2 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "DeepSeek-V3.2 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-kronos.json",
        "title": "DeepSeek V4.1 Flash vs Kronos",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "DeepSeek V4.1 Flash vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kronos.json",
        "title": "DeepSeek-V4-Flash-0731 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "DeepSeek-V4-Flash-0731 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-kronos.json",
        "title": "Devstral Small 2 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Devstral Small 2 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-minicpm-v-4-7-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-kronos.json",
        "title": "DiffusionGemma 26B A4B IT vs Kronos",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-kronos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "DiffusionGemma 26B A4B IT vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minicpm-v-4-7-35b-a3b"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minicpm-v-4-7-35b-a3b"
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-kronos.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "GLM-5.3 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kronos.json",
        "title": "gpt-oss-120b vs Kronos",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "gpt-oss-120b vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-kronos.json",
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "gpt-oss-20b vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-kronos.json",
        "title": "Granite 4.2 30B vs Kronos",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Granite 4.2 30B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-kronos.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Granite 4.2 3B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-kronos.json",
        "title": "Granite 4.2 8B vs Kronos",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Granite 4.2 8B vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-kronos.json",
        "title": "Hy-Memory-30B-A3B vs Kronos",
        "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Hy-Memory-30B-A3B vs MiniCPM-V 4.7 35B-A3B",
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-kronos.json",
        "title": "Hy3 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Hy3 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-kronos.json",
        "title": "Inkling-Small vs Kronos",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Inkling-Small vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-kronos.json",
        "title": "Inkling vs Kronos",
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Inkling vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kronos.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Kronos",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-kronos.json",
        "title": "Kimi K3.1 Pro vs Kronos",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Kimi K3.1 Pro vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-kronos.json",
        "title": "Kimi K3 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Kimi K3 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-kronos.json",
        "title": "Kolibri-1 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-kronos"
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        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm-v-4-7-35b-a3b.json",
        "title": "Kolibri-1 vs MiniCPM-V 4.7 35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-minicpm-v-4-7-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-laguna-m-1.json",
        "title": "Kronos vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-laguna-s-2-1.json",
        "title": "Kronos vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-laguna-s-2-1"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-laguna-xs-2-1.json",
        "title": "Kronos vs Laguna XS 2.1",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-lbs-27b.json",
        "title": "Kronos vs LBS-27B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-lbs-27b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-lfm2-5-2-6b.json",
        "title": "Kronos vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-lfm2-5-2-6b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-lfm3-1-7b.json",
        "title": "Kronos vs LFM3-1.7B",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-lfm3-audio-2b.json",
        "title": "Kronos vs LFM3-Audio-2B",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-lfm3-omni-2b.json",
        "title": "Kronos vs LFM3-Omni-2B",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-lfm3-vl-2b.json",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-ling-3-0-tiny.json",
        "title": "Kronos vs Ling-3.0-tiny",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-ling-3-1-flash-1019.json",
        "title": "Kronos vs Ling-3.1-flash-1019",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-ling-3-1-flash-1019"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-longcat-2-5.json",
        "title": "Kronos vs LongCat-2.5",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-longcat-2-5"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Kronos vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-mimo-v2-6-distill-qwen-9b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-mimo-v2-6-flash-rl.json",
        "title": "Kronos vs MiMo-V2.6-Flash-RL",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-mimo-v2-6-flash-rl"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-minicpm-o-4-5.json",
        "title": "Kronos vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-minicpm-v-4-7-1b.json",
        "title": "Kronos vs MiniCPM-V 4.7 1B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-minicpm-v-4-7-1b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-minicpm5-2b.json",
        "title": "Kronos vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-minicpm5-2b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-minimax-m2-5.json",
        "title": "Kronos vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-minimax-m2-5"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-minimax-m2-7.json",
        "title": "Kronos vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-minimax-m2-7"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-minimax-m3-1-flash.json",
        "title": "Kronos vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-minimax-m3-1-flash"
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      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-mistral-large-4.json",
        "title": "Kronos vs Mistral Large 4",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-mistral-large-4"
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      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-muse-glimmer-30b.json",
        "title": "Kronos vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-muse-glimmer-30b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-nanbeige-4-2-3b.json",
        "title": "Kronos vs Nanbeige4.2-3B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nanbeige-4-2-3b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-nanbeige-4-3-33b.json",
        "title": "Kronos vs Nanbeige4.3-33B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nanbeige-4-3-33b"
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      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-5-bolt-e4b-4gb.json",
        "title": "Kronos vs NVIDIA Nemotron 3.5 Bolt E4B 4GB",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-5-bolt-e4b-4gb"
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      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Kronos vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Kronos vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-4b.json",
        "title": "Kronos vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Kronos vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-super-120b-a12b.json",
        "title": "Kronos vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-super-120b-a12b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Kronos vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-ultra-550b-a55b"
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      {
        "json": "https://www.anchorterminal.com/compare/kronos-vs-north-mini-code-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-north-mini-code-1-0"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-occamy-1-0.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-occamy-1-0"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-olmo-3-7b-think.json",
        "title": "Kronos vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-olmo-3-7b-think"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-122b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-122b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-397b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-397b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-9b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-9b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-otel-2-0-llm-31b-it.json",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-30b-a3b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-30b-a3b-instruct-2507"
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      {
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-0-8b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-0-8b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-122b-a10b.json",
        "title": "Kronos vs Qwen3.5-122B-A10B",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-2b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-397b-a17b.json",
        "title": "Kronos vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-397b-a17b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-4b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-4b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-9b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-5-9b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-6-27b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-6-27b"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-6-35b-a3b.json",
        "title": "Kronos vs Qwen3.6-35B-A3B",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-8-27b.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-8-27b"
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-coder-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-omni-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-vl-2b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-vl-30b-a3b-instruct"
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-vl-32b-instruct"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-vl-4b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-vl-4b-instruct"
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwen3-vl-8b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-qwopus3-8-27b-flash-v2.json",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-recursive-flint.json",
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        "json": "https://www.anchorterminal.com/compare/kronos-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-qwen3-5-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-wevisone-vl-2b.json",
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        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-wevisone-vl-4b.json",
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        "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-zaya1-8b.json",
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    "panel": null,
    "scores": [
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        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
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      {
        "by": 35,
        "edge": "minicpm-v-4-7-35b-a3b",
        "key": "reach",
        "kronos": 55,
        "minicpm-v-4-7-35b-a3b": 90,
        "name": "Reach",
        "weight": 25
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      {
        "by": 5,
        "edge": "minicpm-v-4-7-35b-a3b",
        "key": "risk",
        "kronos": 50,
        "minicpm-v-4-7-35b-a3b": 55,
        "name": "Risk",
        "weight": 20
      },
      {
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        "edge": "minicpm-v-4-7-35b-a3b",
        "key": "interface",
        "kronos": 60,
        "minicpm-v-4-7-35b-a3b": 70,
        "name": "Agent interface",
        "weight": 10
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        "edge": "minicpm-v-4-7-35b-a3b",
        "key": "upkeep",
        "kronos": 61,
        "minicpm-v-4-7-35b-a3b": 68,
        "name": "Documentation and upkeep",
        "weight": 10
      }
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    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "kronos": "Forecasts the next price bars from a history of up to 512 candlestick bars. Every size fits in under 0.5 GB and runs on a CPU, but only through the publisher's own Python package. Nobody has benchmarked it independently, its quickstart data was deleted from the repository, and the publisher hasn't replied since November 2025.",
      "minicpm-v-4-7-35b-a3b": "A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it."
    }
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  "links": {
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    "slim": "https://www.anchorterminal.com/compare/kronos-vs-minicpm-v-4-7-35b-a3b.min.md"
  },
  "markdown": "MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against Kronos's 55.2 (C), and leads in every scored category. Both do open-weight models you run yourself.\n\n- Kronos: grade C, 55.2/100, rank #122 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/kronos.md · JSON https://www.anchorterminal.com/api/v1/tools/kronos.json\n- MiniCPM-V 4.7 35B-A3B: grade C, 61/100, rank #77 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm-v-4-7-35b-a3b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm-v-4-7-35b-a3b.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### Kronos (C)\n\nGood for: Agents that need a quick local forecast or synthetic sample of a candlestick series on modest hardware, for research or as one input among others.\n\nWatch for: Runs only through the publisher's own PyTorch code from GitHub, in no named runtime and with no quantised build\n\n### MiniCPM-V 4.7 35B-A3B (C)\n\nGood for: Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence\n\nAhead on:\n- Reach, 90 against 55\n- Risk, 55 against 50\n- Agent interface, 70 against 60\n- Documentation and upkeep, 68 against 61\n\nWatch for: No limitations section, safety results, agent-use guidance or security contact\n\n\n## Why the edge\n\n### Reach: MiniCPM-V 4.7 35B-A3B +35\n\n- Kronos (55): Memory 30, the publisher's Kronos-mini with its tokeniser is 0.03 GB and even Kronos-base is 0.43 GB in FP32. Runtimes 0, it runs only through the publisher's own PyTorch package from GitHub, and none of the six named runtimes supports it. Builds 0, FP32 safetensors only. Terms 15, MIT with nothing added. Download 10, nothing is gated. Hosted 0, no inference provider or publisher API serves it (provider mapping still empty on 4 November).\n- MiniCPM-V 4.7 35B-A3B (90): Memory 25, since OpenBMB's IQ4_XS GGUF with its vision projector is 19.6 GB and needs about 23.6 GB with the fifth added, which fits 24 GB, while its Q4_K_M GGUF, 4-bit safetensors builds and Ollama entry need 32 GB. Runtimes 25, from vLLM 0.33.0, SGLang 0.5.23, Transformers 5.18.0 and later, llama.cpp's own MiniCPM-V 4.7 support and OpenBMB's entry on Ollama. Builds 15, OpenBMB publishes FP8, three 4-bit safetensors builds and GGUF. Terms 15, Apache 2.0 with nothing added. Download 10, nothing is gated. Hosted 0, no inference provider is mapped. 25 + 25 + 15 + 15 + 10 + 0 = 90.\n\n### Agent interface: MiniCPM-V 4.7 35B-A3B +10\n\n- Kronos (60): Read for a forecasting model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. The card documents the DataFrame and timestamps it takes and the DataFrame it returns, and the publisher's KronosPredictor builds and parses them (25). It was trained on six K-line fields with calendar fields, one series per forecast (10). Output is a typed DataFrame indexed by the requested timestamps, the mean of the sampled paths (15). The input format is given only as code (10). Reasoning control and context score 0, with no reasoning and a 512-bar context (2,048 for Kronos-mini).\n- MiniCPM-V 4.7 35B-A3B (70): Chat template 20, a Jinja file in the repository. Tool-calling format 10, the card shows the tools array going in but not the call coming back, and names no parser. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, enable_thinking per request, off by default, with the trace between markers. Context 10, 262,144 tokens native.\n\n### Documentation and upkeep: MiniCPM-V 4.7 35B-A3B +7\n\n- Kronos (61): Model card 11, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 20, the paper lists every exchange with asset and observation counts, the filtering and a June 2024 end. Last change 5, the reference code on 13 April 2026 (still the newest commit on 4 November, 205 days) and the Hub repositories on 9 September 2025. Responsiveness 20, the publisher answered 10 of 18 Hugging Face discussions (recounted by script on 4 November), though none since 24 November 2025, and the seven opened since April 2026 have no reply from it. Version policy 5, a first release. File health 0, the cards point to example data the repository has deleted and to licence and requirements links on a branch that doesn't exist.\n- MiniCPM-V 4.7 35B-A3B (68): Model card 8, it covers intended use, architecture and parameters but not limitations, context length, languages or a knowledge cut-off. Training data 0, none described. Last change 20, a commit on 3 November 2026. Responsiveness 20, OpenBMB answered 8 of 12 discussions. Version policy 10, earlier versions keep their repositories and the changes are dated and described. File health 10, the files agree. 8 + 0 + 20 + 20 + 10 + 10 = 68.\n\n### Risk: MiniCPM-V 4.7 35B-A3B +5\n\n- Kronos (50): File safety 15, safetensors only, but the only documented loading path is the publisher's Python package in place of a runtime. Provenance 15, the files are in the NeoQuasar account the publisher's README links, with SHA-256 hashes. Safety evaluation 0, none published. Agent guidance 5, the README's general cautions that the fine-tuning pipeline isn't a production trading system. Licence risk 15, plain MIT; the broken licence link is charged to file health. Security programme 0, no reporting route found.\n- MiniCPM-V 4.7 35B-A3B (55): File safety 25, safetensors and GGUF only, no Python in the main repository and no remote code needed. Provenance 15, the files come from the openbmb organisation OpenBMB's GitHub README links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published on either, and the card has no limitations section. Licence risk 15, plain Apache 2.0. Security programme 0, no security.txt or SECURITY.md.\n\n## Score by category\n\n| Category | Weight | Kronos | MiniCPM-V 4.7 35B-A3B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 55 | 90 | MiniCPM-V 4.7 35B-A3B +35 |\n| Risk | 20% (20 this run) | 50 | 55 | MiniCPM-V 4.7 35B-A3B +5 |\n| Agent interface | 10% (10 this run) | 60 | 70 | MiniCPM-V 4.7 35B-A3B +10 |\n| Documentation and upkeep | 10% (10 this run) | 61 | 68 | MiniCPM-V 4.7 35B-A3B +7 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.2 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Kronos | MiniCPM-V 4.7 35B-A3B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Yu Shi (shiyu-coder, NeoQuasar), Tsinghua University | OpenBMB |\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 | MIT | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-04-13 | 2026-11-03 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Popularity | 43k stars | none |\n\n## Verdicts\n\n**Kronos.** Forecasts the next price bars from a history of up to 512 candlestick bars. Every size fits in under 0.5 GB and runs on a CPU, but only through the publisher's own Python package. Nobody has benchmarked it independently, its quickstart data was deleted from the repository, and the publisher hasn't replied since November 2025.\n\n**MiniCPM-V 4.7 35B-A3B.** A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it.\n\n## Before you call either\n\n### Kronos\n\n1. Clone https://github.com/shiyu-coder/Kronos and `pip install -r requirements.txt`, then load `Kronos.from_pretrained(\"NeoQuasar/Kronos-small\")` and `KronosTokenizer.from_pretrained(\"NeoQuasar/Kronos-Tokenizer-base\")` and wrap them in KronosPredictor\n2. Pair Kronos-mini with Kronos-Tokenizer-2k and Kronos-small or Kronos-base with Kronos-Tokenizer-base, the cards' pairing\n3. The examples read examples/data/XSHG_5min_600977.csv, which no longer exists; point them at tests/data/regression_input.csv, 2,500 five-minute bars\n4. Keep the lookback at or under max_context, 512 bars, and pass the future timestamps you want as y_timestamp, since the calendar fields come from them\n5. Raise sample_count for a steadier forecast, but expect only the mean back; call the lower-level auto_regressive_inference yourself if you need the paths\n6. Treat forecasts as model output to check, not signals; the README says its own backtest pipeline isn't a production trading system\n\n### MiniCPM-V 4.7 35B-A3B\n\n1. Start it with `llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja`, or `ollama run openbmb/minicpm-v4.7:35b-a3b`\n2. For image input in llama.cpp add `mmproj-model-f16.gguf`, or the 4x projector for more visual detail at a higher cost\n3. The GGUF files at the repository root have thinking off. Use the files in `thinking/` when you want the trace\n4. With Transformers pass `enable_thinking` to `apply_chat_template`, and pass `downsample_mode` to both `apply_chat_template` and `generate`\n5. Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends\n6. Check tool calls in your runtime first, since the card names no parser. The template uses the Qwen3.5 function-block format\n7. Validate JSON output yourself, since structured output isn't documented\n\n## Questions\n\n### Which is better for AI agents, Kronos or MiniCPM-V 4.7 35B-A3B?\n\nMiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against Kronos's 55.2 (C), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/kronos-vs-minicpm-v-4-7-35b-a3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/kronos-vs-minicpm-v-4-7-35b-a3b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"kronos\", \"b\": \"minicpm-v-4-7-35b-a3b\"}`. 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