{
  "data": {
    "a": {
      "slug": "cosmos-reason2-2b",
      "name": "Cosmos-Reason2-2B",
      "vendor": "NVIDIA",
      "vendorUrl": "https://github.com/nvidia-cosmos/cosmos-reason2",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Cosmos-Reason2-2B is NVIDIA's open-weight vision language model for physical AI and robotics, a 2.4B-parameter fine-tune of Qwen3-VL-2B-Instruct that reasons over video and images. The repository is gated behind a click-through licence.",
      "url": "https://www.anchorterminal.com/tools/cosmos-reason2-2b",
      "markdownUrl": "https://www.anchorterminal.com/tools/cosmos-reason2-2b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cosmos-reason2-2b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json",
      "repo": "https://huggingface.co/nvidia/Cosmos-Reason2-2B",
      "license": "NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "nvidia/Cosmos-Reason2-2B"
        }
      ],
      "auth": "none",
      "authNotes": "The repository is gated (gated: auto). Downloading needs a Hugging Face account and token and accepting the NVIDIA Open Model License on the card, which Hugging Face approves automatically. The card, the file list and the licence text are public. We didn't accept the terms (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the NVIDIA Open Model License, with a contact for a custom licence. Running it costs the hardware, 4.9 GB of BF16 safetensors by the Hub's file list; NVIDIA states a minimum of 24 GB of GPU memory (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://github.com/nvidia-cosmos/cosmos-reason2",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "vision",
        "video",
        "reasoning",
        "robotics",
        "physical-ai",
        "fine-tune",
        "safetensors",
        "gated",
        "self-hosted"
      ],
      "lastRelease": "2026-03-10",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 59.5,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 50,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 65,
          "reach": 65,
          "risk": 60,
          "upkeep": 39
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A small local cousin for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.",
        "bestFor": "Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces",
        "strengths": [
          "4.9 GB of BF16 safetensors with no remote code, loaded by Transformers' own Qwen3-VL class",
          "Runs on released Transformers, vLLM, SGLang and llama.cpp through the Qwen3-VL architecture",
          "NVIDIA's prompt files give JSON formats for bounding boxes, timed events and robot trajectories",
          "Reasoning is prompted with a documented think and answer format and parsed by vLLM's qwen3 parser",
          "Commercial use allowed, files in NVIDIA's own organisation with hashes"
        ],
        "weaknesses": [
          "Gated behind a click-through licence that needs a Hugging Face account",
          "The licence is revocable, can be updated by NVIDIA and ends if a guardrail is bypassed",
          "NVIDIA says the repository is no longer under active development and points to Cosmos 3",
          "No quantised build from NVIDIA, no hosted endpoint for the 2B, and no NVIDIA reply in its discussions",
          "No documented tool calling, no safety results and no training data sizes or cut-off"
        ],
        "agentNotes": [
          "Accept the licence on the Hugging Face card with a signed-in account and set HF_TOKEN before downloading",
          "Serve it with `vllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3`, keeping max-model-len between 8,192 and 16,384 as NVIDIA advises",
          "For local video or images, make a folder for them (`mkdir -p media`) and pass `--allowed-local-media-path \"$(pwd)/media\"`, so the server can read only that folder, not everything under the directory you start it from",
          "Sample video at 4 fps and allow at least 4,096 output tokens so the reasoning isn't cut off",
          "For reasoning, add the card's instruction to answer with a think block and then the answer; leave it out for a direct reply",
          "Use NVIDIA's prompt files (prompts/*.yaml in nvidia-cosmos/cosmos-reason2) when you want JSON boxes, events or trajectories, and validate the JSON yourself",
          "Check its plans before a robot acts on them, since NVIDIA's own safety card warns of collision and manipulation risks"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 59.5
          }
        ],
        "editorialScores": {
          "interface": 65,
          "reach": 65,
          "risk": 60,
          "upkeep": 39
        },
        "provenanceScore": 73,
        "checked": {
          "categories": {
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# accept the licence on the Hugging Face card first, then set HF_TOKEN\nvllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 \\\n  --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3 --port 8000",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"nvidia/Cosmos-Reason2-2B\", \"max_tokens\": 4096, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"image_url\", \"image_url\": {\"url\": \"file:///path/to/frame.jpg\"}}, {\"type\": \"text\", \"text\": \"Is it safe to turn right?\"}]}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/cosmos-reason2-2b"
      },
      "sameCompany": [
        "nemotron-3-5-super-vl",
        "nvidia-nemo-retriever",
        "nemo-guardrails",
        "nemotron-3-5-asr-streaming-0-6b",
        "parakeet-tdt-0-6b-v3",
        "nemotron-3-nano-30b-a3b",
        "nemotron-3-nano-4b",
        "nemotron-3-nano-omni-30b-a3b-reasoning",
        "nemotron-3-super-120b-a12b",
        "nemotron-3-ultra-550b-a55b",
        "nemotron-3-5-lightning-30b-a3b"
      ],
      "weights": {
        "trainedBy": "NVIDIA",
        "builtOn": "Qwen/Qwen3-VL-2B-Instruct (fine-tune, Apache 2.0)",
        "params": "2.44B",
        "context": 262144,
        "goodFor": "Small vision language model for physical AI, reasoning over video and images for robots, driving and smart spaces, with point and box outputs.",
        "runtimes": [
          "Transformers",
          "vLLM",
          "SGLang",
          "llama.cpp"
        ],
        "builds": [
          {
            "name": "Cosmos-Reason2-2B",
            "url": "https://huggingface.co/nvidia/Cosmos-Reason2-2B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 4.9,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "Gated (click-through). NVIDIA states a minimum of 24 GB of GPU memory, more than the file size suggests, presumably for video input"
          }
        ],
        "run": "vllm serve nvidia/Cosmos-Reason2-2B --allowed-local-media-path \"$(pwd)/media\" --max-model-len 16384 --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3 --port 8000",
        "runBuild": "Cosmos-Reason2-2B",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "NVIDIA (Nemotron)",
        "family": "Cosmos-Reason2",
        "url": "https://www.anchorterminal.com/open-weights/#nvidia",
        "others": [
          {
            "name": "Cosmos-Reason2-8B",
            "url": "https://huggingface.co/nvidia/Cosmos-Reason2-8B",
            "params": "8B (8.77B per the safetensors count)"
          },
          {
            "name": "Cosmos-Reason2-32B",
            "url": "https://huggingface.co/nvidia/Cosmos-Reason2-32B",
            "params": "32B (33.36B per the safetensors count)"
          }
        ],
        "olderCount": 43,
        "unrestrictedCopies": 3
      },
      "area": "models",
      "provenance": {
        "legalEntity": "NVIDIA Corporation",
        "domain": "nvidia.com",
        "domainRegistered": "1993-04-20",
        "endpointOnVendorDomain": null,
        "terms": "https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://github.com/nvidia-cosmos/cosmos-reason2/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The card names NVIDIA as model developer and the licence names NVIDIA Corporation. The domain registration date is carried from the RDAP check made for nemotron-3-nano-30b-a3b on 21 October 2026.",
          "Nothing is hosted for this listing, so the NVIDIA Open Model License stands in for terms of service and no privacy policy is scored.",
          "The Hugging Face commit history is behind the gate, so the changelog is the GitHub repository's, whose README carries dated news entries from 19 December 2025 to 1 June 2026.",
          "www.nvidia.com/.well-known/security.txt answered 403 at the 21 October 2026 check for nemotron-3-nano-30b-a3b. The card links NVIDIA's security vulnerability form."
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/cosmos-reason2-2b.json"
    },
    "answer": "Spark-X2.6-4B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk.",
    "b": {
      "slug": "spark-x2-6-4b",
      "name": "Spark-X2.6-4B",
      "vendor": "SparkLLM (XHToken)",
      "vendorUrl": "https://huggingface.co/XHToken",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Spark-X2.6-4B is SparkLLM's open-weight 4B text model, Spark-X2.5-4B's architecture with new post-training, a 1M-token context and three thinking levels, on Hugging Face with FP8, INT8, INT4 and GGUF builds under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/spark-x2-6-4b",
      "markdownUrl": "https://www.anchorterminal.com/tools/spark-x2-6-4b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/spark-x2-6-4b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/spark-x2-6-4b.json",
      "repo": "https://huggingface.co/XHToken/Spark-X2.6-4B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "XHToken/Spark-X2.6-4B"
        },
        {
          "registry": "huggingface",
          "name": "XHToken/Spark-X2.6-4B-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "XHToken/Spark-X2.6-4B-FP8"
        },
        {
          "registry": "huggingface",
          "name": "XHToken/Spark-X2.6-4B-INT8"
        },
        {
          "registry": "huggingface",
          "name": "XHToken/Spark-X2.6-4B-INT4"
        },
        {
          "registry": "ollama",
          "name": "SparkLLM/Spark-X2.6-4B"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the six X2.6 repositories is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Nothing is hosted by SparkLLM or by an inference provider listed on Hugging Face. Running it yourself costs the hardware, 8.24 GB for the BF16 files and 3.19 GB for SparkLLM's Q4_K_M GGUF (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/XHToken/Spark-X2.6-4B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "small",
        "long-context",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "gguf",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2026-10-20",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 41,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 70,
          "reach": 85,
          "risk": 50,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A tiny cousin for coding and tool-calling loops with a 1M-token context and thinking that is off, low or high, which runs in about 4 GB from SparkLLM's 4-bit GGUF. Use llama.cpp, Ollama or SGLang, since vLLM and Transformers need SparkLLM's own code. The risks are no safety work or agent guidance and a thin, two-day-old card.",
        "bestFor": "Agents that want a tiny local model for tool loops and long documents on a laptop, CPU or small GPU.",
        "strengths": [
          "SparkLLM's Q4_K_M GGUF fits in about 4 GB, and FP8, INT8, INT4 and Q8_0 builds come from the publisher",
          "Plain Apache 2.0 on its own base, with no gate or account",
          "1,048,576 tokens of context with sliding-window layers that keep the cache small",
          "Released support in llama.cpp, SGLang and Ollama, with SGLang's own spark25 tool parser",
          "Thinking that turns off per request or runs at low or high effort, and several tool calls a turn",
          "A private security reporting route in SparkLLM's GitHub"
        ],
        "weaknesses": [
          "No safety results and no agent or prompt-injection guidance",
          "Transformers and vLLM need code from SparkLLM's repositories",
          "Tool format and structured output aren't documented, and the template uses its own arg_key format",
          "The card has no limitations, cut-off, architecture description or training data, and leans on X2.5's",
          "Released on 19 and 20 October 2026, with no downloads, discussions or independent results yet"
        ],
        "agentNotes": [
          "Quickest start is `llama-server -hf XHToken/Spark-X2.6-4B-GGUF:Q4_K_M --jinja`, which needs llama.cpp b10828 or later, or `ollama run SparkLLM/Spark-X2.6-4B` (8.2 GB, Ollama 0.34.1 or later)",
          "For parsed tool calls serve it with SGLang 0.5.22 or later, `--tool-call-parser spark25 --reasoning-parser qwen3`, since the calls come back as tool_call blocks with arg_key and arg_value pairs",
          "Thinking is on by default. Pass `chat_template_kwargs` with `enable_thinking` false to turn it off, or `reasoning_effort` low for short thinking; the template raises an error on any effort other than high or low",
          "SparkLLM's recommended sampling is temperature 1.0, top_p 0.95 and top_k -1",
          "The template always opens with its own default system line, with the effort instruction, and puts your system message after the tool list",
          "The template raises an error if tool_call arguments are a JSON string, so pass them as an object",
          "Set the context yourself, the card's 1,048,576-token example needs far more memory than the weights"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 70,
          "reach": 85,
          "risk": 50,
          "upkeep": 41
        },
        "provenanceScore": 40,
        "checked": {
          "categories": {
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "llama-server -hf XHToken/Spark-X2.6-4B-GGUF:Q8_0 --jinja -c 131072\n# or, with SGLang 0.5.22 or later:\npython -m sglang.launch_server --model-path XHToken/Spark-X2.6-4B \\\n  --tool-call-parser spark25 --reasoning-parser qwen3 --context-length 131072",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"XHToken/Spark-X2.6-4B\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"temperature\": 1.0, \"top_p\": 0.95}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/spark-x2-6-4b"
      },
      "weights": {
        "trainedBy": "SparkLLM (XHToken)",
        "builtOn": "XHToken/Spark-X2.6-4B-Base (SparkLLM's own checkpoint, Apache 2.0, declared as the base in the card's metadata). The card's text says X2.6 builds on Spark-X2.5-4B with improved post-training. The Base repository's card is a cut-down copy of this card that calls its files the post-trained model",
        "params": "4.11B",
        "context": 1048576,
        "goodFor": "Small dense text model for coding, tool use and agent loops on a laptop or small GPU, with a 1M-token context and thinking that is off, low or high per request.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "SGLang"
        ],
        "builds": [
          {
            "name": "Spark-X2.6-4B-FP8",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 4.47,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "compressed-tensors float-quantized"
          },
          {
            "name": "Spark-X2.6-4B-INT8",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B-INT8",
            "who": "publisher",
            "precision": "int8",
            "sizeGB": 4.47,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "compressed-tensors int-quantized, 8-bit weights and activations"
          },
          {
            "name": "Spark-X2.6-4B-INT4",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B-INT4",
            "who": "publisher",
            "precision": "int4",
            "sizeGB": 3.43,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "compressed-tensors pack-quantized, 4-bit weights in groups of 32 on the attention and MLP projections, the rest in BF16"
          },
          {
            "name": "Spark-X2.6-4B-Q4_K_M.gguf",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B-GGUF/blob/main/Spark-X2.6-4B-Q4_K_M.gguf",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 3.19,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp",
              "Ollama"
            ],
            "note": "The smallest build at 4-bit or better. 0.59 GB larger than X2.5's Q4_K_M"
          },
          {
            "name": "Spark-X2.6-4B-Q8_0.gguf",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B-GGUF/blob/main/Spark-X2.6-4B-Q8_0.gguf",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 4.38,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp",
              "Ollama"
            ]
          },
          {
            "name": "Spark-X2.6-4B",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 8.24,
            "memoryGB": 12,
            "format": "safetensors",
            "runsOn": [
              "SGLang"
            ],
            "note": "Transformers loads it only with trust_remote_code (modeling_spark.py), and vLLM only with SparkLLM's out-of-tree plugin"
          },
          {
            "name": "Spark-X2.6-4B.gguf",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B-GGUF/blob/main/Spark-X2.6-4B.gguf",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 8.23,
            "memoryGB": 12,
            "format": "gguf"
          },
          {
            "name": "ollama SparkLLM/Spark-X2.6-4B:latest",
            "url": "https://ollama.com/SparkLLM/Spark-X2.6-4B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 8.2,
            "memoryGB": 12,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "SparkLLM's own namespace on Ollama, not Ollama's library. The only tag is 8.2 GB (digest 44ca4d700630), so it is the unquantised build; needs Ollama 0.34.1 or later. Size as Ollama shows it"
          }
        ],
        "run": "llama-server -hf XHToken/Spark-X2.6-4B-GGUF:Q8_0 --jinja -c 131072",
        "runBuild": "Spark-X2.6-4B-Q8_0.gguf",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "SparkLLM (XHToken)",
        "family": "Spark-X2 (X2.5, X2.6)",
        "url": "https://www.anchorterminal.com/open-weights/#sparkllm",
        "others": [
          {
            "name": "Spark-X2.6-4B-Base",
            "url": "https://huggingface.co/XHToken/Spark-X2.6-4B-Base",
            "params": "4B (Hub safetensors count 4.11B)"
          },
          {
            "name": "Spark-X2.5-4B-Base",
            "url": "https://huggingface.co/XHToken/Spark-X2.5-4B-Base",
            "params": "4B (Hub safetensors count 4.11B)"
          },
          {
            "name": "Spark-X2.5-1.7B-Base",
            "url": "https://huggingface.co/XHToken/Spark-X2.5-1.7B-Base",
            "params": "1.7B (Hub safetensors count 1.71B)"
          },
          {
            "name": "Spark-X2.5-4B",
            "url": "https://huggingface.co/XHToken/Spark-X2.5-4B",
            "params": "4B (Hub safetensors count 4.11B)"
          },
          {
            "name": "Spark-X2.5-1.7B",
            "url": "https://huggingface.co/XHToken/Spark-X2.5-1.7B",
            "params": "1.7B (Hub safetensors count 1.71B)"
          }
        ]
      },
      "area": "models",
      "provenance": {
        "legalEntity": "XHToken (the licence's copyright line); the Hugging Face organisation's name is SparkLLM",
        "domain": "",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The Hugging Face organisation XHToken (fullname SparkLLM, 18 members) isn't verified. No company website was found on the card or the organisation page; the card links Slack, Discord, YouTube, dev.to, Bluesky, X, Zhihu and WeChat, and SparkLLM's GitHub repositories.",
          "SparkLLM's GitHub organisation XHToken documents its Hugging Face repositories by name (Spark-MLX-LLM's README), and the X2.6 card points to Spark-plugin, Spark-MLX-LLM and XHToken/LlamaFactory there, which ties the two together.",
          "XHToken/community on GitHub has a SECURITY.md with a private advisory route and a security email, which Spark-plugin's SECURITY.md points to.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "No changelog. The commits from 19 and 20 October 2026 are uploads titled only \"Upload Spark-X2.6-4B model files\"."
        ],
        "score": 40
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/spark-x2-6-4b.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "NVIDIA",
        "b": "SparkLLM (XHToken)",
        "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": "NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-03-10",
        "b": "2026-10-20",
        "name": "Last release"
      },
      {
        "a": "",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "2.5/5 (4)",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Spark-X2.6-4B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk.",
        "question": "Which is better for AI agents, Cosmos-Reason2-2B or Spark-X2.6-4B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 60 against 50"
        ],
        "also": null,
        "goodFor": "Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces",
        "slug": "cosmos-reason2-2b",
        "watchFor": "Gated behind a click-through licence that needs a Hugging Face account"
      },
      {
        "aheadOn": [
          "Reach, 85 against 65",
          "Agent interface, 70 against 65"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.0 against 2.5 out of 5"
        ],
        "goodFor": "Agents that want a tiny local model for tool loops and long documents on a laptop, CPU or small GPU.",
        "slug": "spark-x2-6-4b",
        "watchFor": "No safety results and no agent or prompt-injection guidance"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-cosmos-reason2-2b.json",
        "title": "Agents-A1-4B vs Cosmos-Reason2-2B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-cosmos-reason2-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-spark-x2-6-4b.json",
        "title": "Agents-A1-4B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-cosmos-reason2-2b.json",
        "title": "Apertus v1.5 8B vs Cosmos-Reason2-2B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-cosmos-reason2-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-spark-x2-6-4b.json",
        "title": "Apertus v1.5 8B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-cosmos-reason2-2b.json",
        "title": "Apodex-1.1-mini vs Cosmos-Reason2-2B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-cosmos-reason2-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-spark-x2-6-4b.json",
        "title": "Apodex-1.1-mini vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-cosmos-reason2-2b.json",
        "title": "BigBang-v1 vs Cosmos-Reason2-2B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-cosmos-reason2-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-spark-x2-6-4b.json",
        "title": "BigBang-v1 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus.json",
        "title": "Cosmos-Reason2-2B vs Darwin-36B-Opus",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-darwin-36b-opus"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v3-2.json",
        "title": "Cosmos-Reason2-2B vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v3-2"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-1-flash.json",
        "title": "Cosmos-Reason2-2B vs DeepSeek V4.1 Flash",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-1-flash"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-flash-0731.json",
        "title": "Cosmos-Reason2-2B vs DeepSeek-V4-Flash-0731",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v4-flash-0731"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-diffusiongemma-26b-a4b-it.json",
        "title": "Cosmos-Reason2-2B vs DiffusionGemma 26B A4B IT",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-diffusiongemma-26b-a4b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-12b-it.json",
        "title": "Cosmos-Reason2-2B vs Gemma 4 12B IT",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-12b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it.json",
        "title": "Cosmos-Reason2-2B vs Gemma 4 26B A4B IT",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-26b-a4b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-31b-it.json",
        "title": "Cosmos-Reason2-2B vs Gemma 4 31B IT",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e2b-it.json",
        "title": "Cosmos-Reason2-2B vs Gemma 4 E2B IT",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e2b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e4b-it.json",
        "title": "Cosmos-Reason2-2B vs Gemma 4 E4B IT",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gemma-4-e4b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-5-air.json",
        "title": "Cosmos-Reason2-2B vs GLM-4.5-Air",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-5-air"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-7-flash.json",
        "title": "Cosmos-Reason2-2B vs GLM-4.7-Flash",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-4-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3.json",
        "title": "Cosmos-Reason2-2B vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3"
      },
      {
        "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/cosmos-reason2-2b-vs-gpt-oss-120b.json",
        "title": "Cosmos-Reason2-2B vs gpt-oss-120b",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-120b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b.json",
        "title": "Cosmos-Reason2-2B vs gpt-oss-20b",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-gpt-oss-20b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-3b.json",
        "title": "Cosmos-Reason2-2B vs Granite 4.2 3B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-granite-4-2-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-hy3.json",
        "title": "Cosmos-Reason2-2B vs Hy3",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-hy3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.json",
        "title": "Cosmos-Reason2-2B vs Inkling",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small.json",
        "title": "Cosmos-Reason2-2B vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "Cosmos-Reason2-2B vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-internvl3-5-gpt-oss-20b-a4b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3.json",
        "title": "Cosmos-Reason2-2B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kolibri-1.json",
        "title": "Cosmos-Reason2-2B vs Kolibri-1",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kolibri-1"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-m-1"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1.json",
        "title": "Cosmos-Reason2-2B vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm2-5-2-6b.json",
        "title": "Cosmos-Reason2-2B vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm2-5-2-6b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-0-tiny.json",
        "title": "Cosmos-Reason2-2B vs Ling-3.0-tiny",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ling-3-0-tiny"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Cosmos-Reason2-2B vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mimo-v2-6-distill-qwen-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5.json",
        "title": "Cosmos-Reason2-2B vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b.json",
        "title": "Cosmos-Reason2-2B vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5.json",
        "title": "Cosmos-Reason2-2B vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-7.json",
        "title": "Cosmos-Reason2-2B vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-7"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-muse-glimmer-30b.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-muse-glimmer-30b"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-5-lightning-30b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-5-lightning-30b-a3b"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-30b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-30b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-4b.json",
        "title": "Cosmos-Reason2-2B vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-4b"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-super-120b-a12b.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-super-120b-a12b"
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      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-ultra-550b-a55b.json",
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-nemotron-3-ultra-550b-a55b"
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        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0.json",
        "title": "Cosmos-Reason2-2B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-olmo-3-7b-think.json",
        "title": "Cosmos-Reason2-2B vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ornith-1-5-35b-a3b.json",
        "title": "Cosmos-Reason2-2B vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ornith-1-5-35b-a3b"
      },
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-spark-x2-6-4b.json",
        "title": "Ornith-1.5-35B-A3B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-spark-x2-6-4b.json",
        "title": "Ornith-1.5-397B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-spark-x2-6-4b.json",
        "title": "Ornith-1.5-9B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-spark-x2-6-4b.json",
        "title": "Qwen3-30B-A3B-Instruct-2507 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-spark-x2-6-4b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.5-0.8B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.5-122B-A10B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.5-2B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.5-397B-A17B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.5-4B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.5-9B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.6-27B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.6-35B-A3B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-spark-x2-6-4b.json",
        "title": "Qwen3.8-27B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-spark-x2-6-4b.json",
        "title": "Qwen3.8-Flash-Next vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-Coder-30B-A3B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-spark-x2-6-4b.json",
        "title": "Qwen3-Coder-Next vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-Omni-30B-A3B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-VL-2B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-VL-30B-A3B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-VL-32B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-VL-4B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-spark-x2-6-4b.json",
        "title": "Qwen3-VL-8B-Instruct vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-spark-x2-6-4b.json",
        "title": "Qwopus3.8-27B-Flash-V2 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-spark-x2-6-4b.json",
        "title": "SmolLM3-3B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Spark-X2.6-4B vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Spark-X2.6-4B vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Spark-X2.6-4B vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 20,
        "cosmos-reason2-2b": 65,
        "edge": "spark-x2-6-4b",
        "key": "reach",
        "name": "Reach",
        "spark-x2-6-4b": 85,
        "weight": 25
      },
      {
        "by": 10,
        "cosmos-reason2-2b": 60,
        "edge": "cosmos-reason2-2b",
        "key": "risk",
        "name": "Risk",
        "spark-x2-6-4b": 50,
        "weight": 20
      },
      {
        "by": 5,
        "cosmos-reason2-2b": 65,
        "edge": "spark-x2-6-4b",
        "key": "interface",
        "name": "Agent interface",
        "spark-x2-6-4b": 70,
        "weight": 10
      },
      {
        "by": 2,
        "cosmos-reason2-2b": 39,
        "edge": "spark-x2-6-4b",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "spark-x2-6-4b": 41,
        "weight": 10
      }
    ],
    "summary": "Spark-X2.6-4B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "cosmos-reason2-2b": "A small local cousin for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.",
      "spark-x2-6-4b": "A tiny cousin for coding and tool-calling loops with a 1M-token context and thinking that is off, low or high, which runs in about 4 GB from SparkLLM's 4-bit GGUF. Use llama.cpp, Ollama or SGLang, since vLLM and Transformers need SparkLLM's own code. The risks are no safety work or agent guidance and a thin, two-day-old card."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-spark-x2-6-4b",
    "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-spark-x2-6-4b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-spark-x2-6-4b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-spark-x2-6-4b.min.md"
  },
  "markdown": "Spark-X2.6-4B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk. Both do open-weight models you run yourself.\n\n- Cosmos-Reason2-2B: grade C, 59.5/100, rank #59 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/cosmos-reason2-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json\n- Spark-X2.6-4B: grade C, 61/100, rank #48 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/spark-x2-6-4b.md · JSON https://www.anchorterminal.com/api/v1/tools/spark-x2-6-4b.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Cosmos-Reason2-2B (C)\n\nGood for: Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces\n\nAhead on:\n- Risk, 60 against 50\n\nWatch for: Gated behind a click-through licence that needs a Hugging Face account\n\n### Spark-X2.6-4B (C)\n\nGood for: Agents that want a tiny local model for tool loops and long documents on a laptop, CPU or small GPU.\n\nAhead on:\n- Reach, 85 against 65\n- Agent interface, 70 against 65\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.0 against 2.5 out of 5\n\nWatch for: No safety results and no agent or prompt-injection guidance\n\n\n## Score by category\n\n| Category | Weight | Cosmos-Reason2-2B | Spark-X2.6-4B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 65 | 85 | Spark-X2.6-4B +20 |\n| Risk | 20% (20 this run) | 60 | 50 | Cosmos-Reason2-2B +10 |\n| Agent interface | 10% (10 this run) | 65 | 70 | Spark-X2.6-4B +5 |\n| Documentation and upkeep | 10% (10 this run) | 39 | 41 | Spark-X2.6-4B +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59.5 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Cosmos-Reason2-2B | Spark-X2.6-4B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | NVIDIA | SparkLLM (XHToken) |\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 | NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-03-10 | 2026-10-20 |\n| Terms last updated |  | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 2.5/5 (4) | 3/5 (4) |\n\n## Verdicts\n\n**Cosmos-Reason2-2B.** A small local cousin for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.\n\n**Spark-X2.6-4B.** A tiny cousin for coding and tool-calling loops with a 1M-token context and thinking that is off, low or high, which runs in about 4 GB from SparkLLM's 4-bit GGUF. Use llama.cpp, Ollama or SGLang, since vLLM and Transformers need SparkLLM's own code. The risks are no safety work or agent guidance and a thin, two-day-old card.\n\n## Before you call either\n\n### Cosmos-Reason2-2B\n\n1. Accept the licence on the Hugging Face card with a signed-in account and set HF_TOKEN before downloading\n2. Serve it with `vllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 --media-io-kwargs '{\"video\": {\"num_frames\": -1}}' --reasoning-parser qwen3`, keeping max-model-len between 8,192 and 16,384 as NVIDIA advises\n3. For local video or images, make a folder for them (`mkdir -p media`) and pass `--allowed-local-media-path \"$(pwd)/media\"`, so the server can read only that folder, not everything under the directory you start it from\n4. Sample video at 4 fps and allow at least 4,096 output tokens so the reasoning isn't cut off\n5. For reasoning, add the card's instruction to answer with a think block and then the answer; leave it out for a direct reply\n6. Use NVIDIA's prompt files (prompts/*.yaml in nvidia-cosmos/cosmos-reason2) when you want JSON boxes, events or trajectories, and validate the JSON yourself\n7. Check its plans before a robot acts on them, since NVIDIA's own safety card warns of collision and manipulation risks\n\n### Spark-X2.6-4B\n\n1. Quickest start is `llama-server -hf XHToken/Spark-X2.6-4B-GGUF:Q4_K_M --jinja`, which needs llama.cpp b10828 or later, or `ollama run SparkLLM/Spark-X2.6-4B` (8.2 GB, Ollama 0.34.1 or later)\n2. For parsed tool calls serve it with SGLang 0.5.22 or later, `--tool-call-parser spark25 --reasoning-parser qwen3`, since the calls come back as tool_call blocks with arg_key and arg_value pairs\n3. Thinking is on by default. Pass `chat_template_kwargs` with `enable_thinking` false to turn it off, or `reasoning_effort` low for short thinking; the template raises an error on any effort other than high or low\n4. SparkLLM's recommended sampling is temperature 1.0, top_p 0.95 and top_k -1\n5. The template always opens with its own default system line, with the effort instruction, and puts your system message after the tool list\n6. The template raises an error if tool_call arguments are a JSON string, so pass them as an object\n7. Set the context yourself, the card's 1,048,576-token example needs far more memory than the weights\n\n## Questions\n\n### Which is better for AI agents, Cosmos-Reason2-2B or Spark-X2.6-4B?\n\nSpark-X2.6-4B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-spark-x2-6-4b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-spark-x2-6-4b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cosmos-reason2-2b\", \"b\": \"spark-x2-6-4b\"}`. From a terminal: `anchor compare cosmos-reason2-2b spark-x2-6-4b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cosmos-reason2-2b.json and https://www.anchorterminal.com/api/v1/tools/spark-x2-6-4b.json\n\n## Other comparisons with Cosmos-Reason2-2B or Spark-X2.6-4B\n\n- [Agents-A1-4B vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-cosmos-reason2-2b.md)\n- [Agents-A1-4B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-spark-x2-6-4b.md)\n- [Apertus v1.5 8B vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-cosmos-reason2-2b.md)\n- [Apertus v1.5 8B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-spark-x2-6-4b.md)\n- [Apodex-1.1-mini vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-cosmos-reason2-2b.md)\n- [Apodex-1.1-mini vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-spark-x2-6-4b.md)\n- 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