{ "data": { "a": { "slug": "ling-3-1-flash-1019", "name": "Ling-3.1-flash-1019", "vendor": "inclusionAI (Ant Group)", "vendorUrl": "https://www.inclusion-ai.org", "kind": "weights", "category": "open-weights", "summary": "Ling-3.1-flash-1019 is inclusionAI's open-weight hybrid reasoning mixture of experts with 560B parameters and 25B active, a post-trained update of Ling-3.1-flash, with switchable thinking, tool calling and a 262,144-token native context, published in FP8 under MIT.", "url": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019", "markdownUrl": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ling-3-1-flash-1019.json", "dns": "ling-3-1-flash-1019.grade.anchorterminal.com", "repo": "https://huggingface.co/inclusionAI/Ling-3.1-flash-1019", "license": "MIT", "transports": [], "packages": [ { "registry": "huggingface", "name": "inclusionAI/Ling-3.1-flash-1019" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under MIT (named in the card's metadata; the repository holds no LICENSE file). Running it yourself costs the hardware, 573.8 GB of FP8 files, which the card serves on 8 H200 or 4 GB300 GPUs (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/inclusionAI/Ling-3.1-flash-1019", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "hybrid-attention", "reasoning", "tool-calling", "long-context", "mit", "safetensors", "fp8", "self-hosted" ], "lastRelease": "2026-11-04", "graded": true, "anchor": { "graded": true, "score": 54.8, "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": 94, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 60, "reach": 60, "risk": 45, "upkeep": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "inclusionAI's newest flagship, a 560B hybrid mixture of experts under plain MIT that vLLM, SGLang, Transformers and llama.cpp run in released versions. It ships only as 574 GB of FP8, so it needs a multi-GPU server. The card overstates the context, documents little about tool calls, and has no safety results.", "bestFor": "Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding", "strengths": [ "Plain MIT, ungated, with a hash for every shard", "Released vLLM, SGLang, Transformers and llama.cpp all have the architecture", "A 262,144-token native context, and 1M with YaRN per SGLang's cookbook", "A training-content summary that names source categories, the size band and a collection date", "Updated a week before this check" ], "weaknesses": [ "574 GB in FP8 with no smaller build from inclusionAI, so no single machine under 690 GB of GPU memory runs it", "The card says 1M tokens of context where the files give 262,144", "The tool-call format is only in the template", "No safety results, no agent guidance and no security contact", "No inference provider mapped for this release, only for the earlier one", "Neither question on the repository has a reply" ], "agentNotes": [ "Serve it with SGLang 0.5.23 or later on 8 H200 or 4 GB300 GPUs, per the card, and use this repository's name as the model path, not the earlier one the card's command shows", "With vLLM pass `--trust-remote-code`, `--tool-call-parser ling3` and `--reasoning-parser ling3`", "Set `chat_template_kwargs` `enable_thinking` false for direct answers. Reasoning comes back in `reasoning_content` per SGLang's cookbook", "Plan on 262,144 tokens of context. The 1M figure needs the YaRN override in SGLang's cookbook", "Use temperature 1.0, top_p 0.95 and top_k 20, per the card", "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": 54.8 } ], "editorialScores": { "interface": 60, "reach": 60, "risk": 45, "upkeep": 56 }, "provenanceScore": 61, "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": "# with SGLang 0.5.23 or later, on 8 H200 GPUs:\npython3 -m sglang.launch_server --model-path inclusionAI/Ling-3.1-flash-1019 \\\n --tp 8 --ep 8 --speculative-algorithm NEXTN --host 0.0.0.0 --port 30000\n# or with vLLM 0.33.0, per the card's serve command:\nvllm serve inclusionAI/Ling-3.1-flash-1019 --trust-remote-code --tensor-parallel-size 8 \\\n --enable-prefix-caching --enable-expert-parallel --mamba-cache-mode align \\\n --enable-auto-tool-choice --tool-call-parser ling3 --reasoning-parser ling3\n# or, with llama.cpp and bartowski's GGUF, a third party's conversion:\nllama-server -hf bartowski/Ling-3.1-flash-1019-GGUF:Q4_K_M --jinja", "http": "curl http://localhost:30000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"inclusionAI/Ling-3.1-flash-1019\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"enable_thinking\": false}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/ling-3-1-flash-1019" }, "sameCompany": [ "ming-3-0-asr-tiny", "ming-3-0-audio-flash", "ming-3-0-audio-tiny", "ming-3-0-tts-tiny", "lbs-27b", "ling-3-0-tiny" ], "weights": { "trainedBy": "inclusionAI (Ant Group)", "builtOn": "inclusionAI/Ling-3.1-flash, post-trained further (named on the card; the metadata names no base model)", "params": "560B (25B active)", "context": 262144, "goodFor": "Large hybrid reasoning model for agents, office work and software engineering on a multi-GPU server, with thinking switchable per request. It needs about 690 GB of GPU memory in FP8.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "bartowski Ling-3.1-flash-1019-GGUF (Q4_K_M)", "url": "https://huggingface.co/bartowski/Ling-3.1-flash-1019-GGUF", "who": "bartowski", "precision": "q4_k_m", "sizeGB": 357.97, "memoryGB": 512, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "From bartowski, a third party's conversion and not inclusionAI's. 357.97 GB of Q4_K_M weights, from the Hub's model information on 10 November 2026. Reach doesn't count it" }, { "name": "Ling-3.1-flash-1019", "url": "https://huggingface.co/inclusionAI/Ling-3.1-flash-1019", "who": "publisher", "precision": "fp8", "sizeGB": 573.78, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ], "note": "The release itself, FP8 E4M3 weights in 128×128 blocks. inclusionAI publishes no smaller build" } ], "run": "python3 -m sglang.launch_server --model-path inclusionAI/Ling-3.1-flash-1019 --tp 8 --ep 8 --speculative-algorithm NEXTN", "runBuild": "Ling-3.1-flash-1019", "checked": "2026-11-10", "minMemoryGB": 512 }, "family": { "lab": "inclusionAI (Ant Group)", "family": "Ling 3", "url": "https://www.anchorterminal.com/open-weights/#inclusionai", "others": [ { "name": "Ling-3.0-flash", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-base", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-base-30T", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base-30T", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-base-midtrain", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-base-midtrain", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-Fin", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-Fin", "params": "124B total, 5.1B active" }, { "name": "Ling-3.0-flash-VL", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-VL", "params": "124B total, 5.5B active" }, { "name": "Ling-3.0-flash-dspark", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-dspark", "params": "1.36B (draft)" }, { "name": "Ling-3.0-flash-singprobe", "url": "https://huggingface.co/inclusionAI/Ling-3.0-flash-singprobe", "params": "5.18M (probe)" }, { "name": "Ling-3.0-tiny", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny", "params": "7.9B total, 1.3B active", "listing": "https://www.anchorterminal.com/tools/ling-3-0-tiny" }, { "name": "Ling-3.0-tiny-base", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base", "params": "7.9B total, 1.3B active" }, { "name": "Ling-3.0-tiny-base-30T", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-30T", "params": "7.9B total, 1.3B active" }, { "name": "Ling-3.0-tiny-base-midtrain", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-midtrain", "params": "7.9B total, 1.3B active" }, { "name": "Ling-3.0-tiny-singprobe", "url": "https://huggingface.co/inclusionAI/Ling-3.0-tiny-singprobe", "params": "3.22M (probe)" }, { "name": "Ling-3.1-flash", "url": "https://huggingface.co/inclusionAI/Ling-3.1-flash", "params": "560B total, 25B active" }, { "name": "Ling-3.1-flash-base", "url": "https://huggingface.co/inclusionAI/Ling-3.1-flash-base", "params": "560B total, 25B active" } ], "olderCount": 54 }, "area": "models", "provenance": { "legalEntity": "Ant Intelligence (Hang Zhou) Technology Co., Ltd (named as provider in the training-content summary); inclusionAI, Ant Group in the site footer of inclusion-ai.org", "domain": "inclusion-ai.org", "domainRegistered": "2025-04-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/inclusionAI/Ling-3.1-flash-1019/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "inclusion-ai.org links to huggingface.co/inclusionAI and github.com/inclusionAI. The domain registration date is carried from the RDAP check made for the Ming 3.0 listings on 21 October 2026.", "Nothing is hosted by the publisher, so the MIT licence stands in for terms of service and no privacy policy is scored.", "The changelog is the Hugging Face commit history, 8 commits from 27 October to 4 November 2026, the last three card edits.", "www.inclusion-ai.org/.well-known/security.txt answered 404 on 10 November 2026." ], "score": 61 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ling-3-1-flash-1019.json" }, "answer": "ZAYA1-8B scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 2 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep.", "b": { "slug": "zaya1-8b", "name": "ZAYA1-8B", "vendor": "Zyphra", "vendorUrl": "https://www.zyphra.com", "kind": "weights", "category": "open-weights", "summary": "ZAYA1-8B is Zyphra's open-weight reasoning model, a mixture of experts of 8.4B parameters with 760M active, trained from scratch for maths and coding. Apache 2.0. Zyphra's 4-bit build is 5.9 GB. Released SGLang and Transformers run it.", "url": "https://www.anchorterminal.com/tools/zaya1-8b", "markdownUrl": "https://www.anchorterminal.com/tools/zaya1-8b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/zaya1-8b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json", "dns": "zaya1-8b.grade.anchorterminal.com", "repo": "https://huggingface.co/Zyphra/ZAYA1-8B", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "Zyphra/ZAYA1-8B" }, { "registry": "huggingface", "name": "Zyphra/ZAYA1-8B-FP8-Experts" }, { "registry": "huggingface", "name": "Zyphra/ZAYA1-8B-MXFP4-Experts" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the repositories is gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use under Apache 2.0, per the main repository's metadata. Running it yourself costs little: 5.9 GB with the experts at 4 bits (MXFP4), 9.6 GB in FP8 or 17.7 GB in BF16 (checked 2026-11-10).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://huggingface.co/Zyphra/ZAYA1-8B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "small", "reasoning", "maths", "coding", "tool-calling", "apache-2.0", "safetensors", "fp8", "mxfp4", "self-hosted" ], "lastRelease": "2026-07-02", "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": 67, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 60, "reach": 80, "risk": 55, "upkeep": 50 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.", "bestFor": "People who want a small, fast reasoning model for maths and code and can live without tool calling", "strengths": [ "Apache 2.0, ungated", "5.9 GB at 4 bits, 760M parameters active", "Released Transformers and SGLang carry the architecture", "Zyphra replied in most of the recent discussions", "The original checkpoint is kept beside the reshaped one" ], "weaknesses": [ "Tool calling needs a parser that only Zyphra's vLLM fork has", "Released vLLM and llama.cpp don't run it, and there's no GGUF", "The card's install steps use forks", "No limitations, context length, languages, data or safety results on the card", "Benchmarks on the card are all from Zyphra's own harness" ], "agentNotes": [ "Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork", "Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in", "Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work", "Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes", "The quantised repositories have no licence tag. The main one is Apache 2.0" ], "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": 60, "reach": 80, "risk": 55, "upkeep": 50 }, "provenanceScore": 56, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install \"sglang\u003e=0.5.23\"\npython -m sglang.launch_server --model-path Zyphra/ZAYA1-8B --reasoning-parser qwen3\n# the card's own route is vLLM from Zyphra's fork, with --tool-call-parser zaya_xml", "http": "# SGLang serves an OpenAI-compatible API at http://localhost:30000/v1. The card recommends temperature 1.0\n# and top_p 0.95 in general, and temperature 0.6 for agent and code work" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/zaya1-8b" }, "weights": { "trainedBy": "Zyphra", "builtOn": "ZAYA1-reasoning-base, Zyphra's own pre-trained model, per the card", "params": "8.4B", "active": "760M", "context": 131072, "goodFor": "Long step-by-step reasoning in maths and code on a small machine, and as the model inside a test-time compute harness.", "runtimes": [ "SGLang", "Transformers" ], "builds": [ { "name": "ZAYA1-8B-MXFP4-Experts", "url": "https://huggingface.co/Zyphra/ZAYA1-8B-MXFP4-Experts", "who": "publisher", "precision": "mxfp4", "sizeGB": 5.85, "memoryGB": 8, "format": "safetensors", "note": "Zyphra's build with the experts at 4 bits. Which released runtime loads it wasn't established" }, { "name": "ZAYA1-8B-FP8-Experts", "url": "https://huggingface.co/Zyphra/ZAYA1-8B-FP8-Experts", "who": "publisher", "precision": "fp8", "sizeGB": 9.64, "memoryGB": 12, "format": "safetensors", "note": "Zyphra's build with the experts in FP8" }, { "name": "ZAYA1-8B (BF16 safetensors)", "url": "https://huggingface.co/Zyphra/ZAYA1-8B", "who": "publisher", "precision": "bf16", "sizeGB": 17.68, "memoryGB": 24, "format": "safetensors", "runsOn": [ "SGLang", "Transformers" ], "note": "Four shards, reshaped for Transformers" } ], "run": "python -m sglang.launch_server --model-path Zyphra/ZAYA1-8B --reasoning-parser qwen3", "runBuild": "ZAYA1-8B (BF16 safetensors)", "checked": "2026-11-10", "minMemoryGB": 8 }, "family": { "lab": "Zyphra", "family": "ZAYA1", "url": "https://www.anchorterminal.com/open-weights/#zyphra", "others": [ { "name": "ZAYA1-VL-8B", "url": "https://huggingface.co/Zyphra/ZAYA1-VL-8B" }, { "name": "ZAYA1-74B-preview", "url": "https://huggingface.co/Zyphra/ZAYA1-74B-preview" } ] }, "area": "models", "provenance": { "legalEntity": "Zyphra, named on the card and its site. The legal entity wasn't looked up", "domain": "zyphra.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/Zyphra/ZAYA1-8B/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "www.zyphra.com's robots.txt allows reading outside /studio and /api. Its about page gives a San Francisco address and names no people in the text read.", "The domain's registration date wasn't looked up. www.zyphra.com has no security.txt (404 on 10 November 2026).", "Nothing is hosted under this listing, so Apache 2.0 stands in for terms of service and no privacy policy is scored. Zyphra's site lists a cloud product for its open models, which wasn't read.", "The changelog is the commit history, 41 commits from 4 May to 26 June 2026." ], "score": 56 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/zaya1-8b.json" }, "edges": [ { "by": 20, "category": "reach", "leads": "zaya1-8b", "name": "Reach", "reasons": { "a": "Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build. Runtimes 25, Released model code in Transformers 5.22.2 (bailing_hybrid), vLLM 0.33.0 (BailingMoeV3ForCausalLM, with ling3 tool and reasoning parsers), SGLang 0.5.23 (bailing_moe_v3.py, its bailing_hybrid config and MTP module) and llama.cpp b12242 (bailingmoe3), and Ollama, credited through its pinned llama.cpp as on the Ling-3.0-tiny listing: v0.40.16 sets LLAMA_CPP_VERSION to b12177. Builds 10, the release is FP8, the one quantised precision inclusionAI publishes for it. Terms 15, MIT in the card's metadata, with no use policy or other terms added on the card or in the repository. Download 10, the Hub API's model info gives gated false on 10 November 2026, so the files download with no account and no terms to accept. Hosted 0, the Hub API's provider mapping is empty for this repository on 10 November 2026. 0 + 25 + 10 + 15 + 10 + 0 = 60.", "b": "Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80." }, "scores": { "a": 60, "b": 80 } }, { "by": 10, "category": "risk", "leads": "zaya1-8b", "name": "Risk", "reasons": { "a": "File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the repository's configuration_bailing_moe_v3.py, since vLLM 0.33.0 registers no bailing_hybrid config of its own. Provenance 15, files in the inclusionAI organisation that inclusion-ai.org links to, per the Ling-3.0-tiny listing (10). Safety evaluation 0, no safety results for the model on its card or in the training-content summary. Agent guidance 0, the card has nothing on prompt injection, refusals or safeguards, and inclusionAI publishes no guardrail probe for this model as it did for Ling 3.0. Licence risk 15, MIT with no use policy, no field-of-use limits, no threshold and no clause letting inclusionAI change or revoke it. Security programme 0, www.inclusion-ai.org answers 404 for security.txt on 10 November 2026, and the Ling-3.0-tiny listing found no SECURITY.md or disclosure policy in the inclusionAI .github repository. 15 + 15 + 0 + 0 + 15 + 0 = 45.", "b": "File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55." }, "scores": { "a": 45, "b": 55 } }, { "by": 6, "category": "upkeep", "leads": "ling-3-1-flash-1019", "name": "Documentation and upkeep", "reasons": { "a": "Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claimed) are on the card. Training data 15, the training-content summary the card links names the source categories (Common Crawl and other public datasets, commercially licensed data, the Ant Spider crawler, synthetic data), the size band (over 10 trillion text tokens), data collected up to about July 2026 and the filtering, without listing datasets with sizes. Last change 20, the newest commit, on 4 November 2026, edited the card, six days before this check, and the files went up on 27 October. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (both opened on 27 October 2026) has a reply from an inclusionAI member. Version policy 5, the update went into a repository of its own and Ling-3.1-flash and Ling 3.0 stay in theirs. File health 5, the card states a 1M-token context while config.json gives 262,144 with no rope scaling, and its serve commands name the earlier repository as the model path. 11 + 15 + 20 + 0 + 5 + 5 = 56.", "b": "Model card 5, Intended use and the parameter counts are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the main repository last changed on 26 June 2026 (the checkpoint reshaped for Transformers), 137 days before this check, and the quantised repositories on 2 July, 131 days. Responsiveness 20, Of the 16 most recent discussions that aren't pull requests (7 May to 14 August 2026), 10 have a reply from a Zyphra member, which is most. Version policy 5, the original checkpoint is kept as ZAYA1-8B-legacy and the card says so at the top, without a date. File health 10, Config, template and card agree on the architecture after the reshape. 5 + 0 + 10 + 20 + 5 + 10 = 50." }, "scores": { "a": 56, "b": 50 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "inclusionAI (Ant Group)", "b": "Zyphra", "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": "2026-11-04", "b": "2026-07-02", "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" } ], "faq": [ { "answer": "ZAYA1-8B scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 2 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep.", "question": "Which is better for AI agents, Ling-3.1-flash-1019 or ZAYA1-8B?" } ], "goodFor": [ { "aheadOn": [ "Documentation and upkeep, 56 against 50" ], "also": null, "goodFor": "Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding", "slug": "ling-3-1-flash-1019", "watchFor": "574 GB in FP8 with no smaller build from inclusionAI, so no single machine under 690 GB of GPU memory runs it" }, { "aheadOn": [ "Reach, 80 against 60", "Risk, 55 against 45" ], "also": null, "goodFor": "People who want a small, fast reasoning model for maths and code and can live without tool calling", "slug": "zaya1-8b", "watchFor": "Tool calling needs a parser that only Zyphra's vLLM fork has" } ], "history": null, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": 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"Qwen3-VL-2B-Instruct vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-zaya1-8b.json", "title": "Qwen3-VL-30B-A3B-Instruct vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-zaya1-8b.json", "title": "Qwen3-VL-32B-Instruct vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-zaya1-8b.json", "title": "Qwen3-VL-4B-Instruct vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-zaya1-8b.json", "title": "Qwen3-VL-8B-Instruct vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-zaya1-8b.json", "title": "Qwopus3.8-27B-Flash-V2 vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-zaya1-8b.json", "title": "Recursive Flint vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/ripple-65b-preview-vs-zaya1-8b.json", "title": "Ripple-65B Preview vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/ripple-65b-preview-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.json", "title": "SenseNova-Loop-9B-Preview vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-zaya1-8b.json", "title": "SmolLM3-3B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b.json", "title": "Spark-X2.6-4B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-zaya1-8b.json", "title": "Step 3.7 Flash vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/step-3-7-flash-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-zaya1-8b.json", "title": "Swift 1.5 Qwen3.8-27B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-zaya1-8b.json", "title": "Swift 1.5 Qwen3.8-Flash-Next vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-zaya1-8b.json", "title": "ThinkingCap (Qwen3.8 27B) vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/thinkingcap-qwen3-8-27b-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-zaya1-8b.json", "title": "Baidu Unlimited-OCR-2 vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-zaya1-8b.json", "title": "WeVisOne-VL-2B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b.json", "title": "WeVisOne-VL-4B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 20, "edge": "zaya1-8b", "key": "reach", "ling-3-1-flash-1019": 60, "name": "Reach", "weight": 25, "zaya1-8b": 80 }, { "by": 10, "edge": "zaya1-8b", "key": "risk", "ling-3-1-flash-1019": 45, "name": "Risk", "weight": 20, "zaya1-8b": 55 }, { "by": 0, "edge": "", "key": "interface", "ling-3-1-flash-1019": 60, "name": "Agent interface", "weight": 10, "zaya1-8b": 60 }, { "by": 6, "edge": "ling-3-1-flash-1019", "key": "upkeep", "ling-3-1-flash-1019": 56, "name": "Documentation and upkeep", "weight": 10, "zaya1-8b": 50 } ], "summary": "ZAYA1-8B scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 2 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "ling-3-1-flash-1019": "inclusionAI's newest flagship, a 560B hybrid mixture of experts under plain MIT that vLLM, SGLang, Transformers and llama.cpp run in released versions. It ships only as 574 GB of FP8, so it needs a multi-GPU server. The card overstates the context, documents little about tool calls, and has no safety results.", "zaya1-8b": "A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b", "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.min.md" }, "markdown": "ZAYA1-8B scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 2 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep. Both do open-weight models you run yourself.\n\n- Ling-3.1-flash-1019: grade C, 54.8/100, rank #126 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/ling-3-1-flash-1019.md · JSON https://www.anchorterminal.com/api/v1/tools/ling-3-1-flash-1019.json\n- ZAYA1-8B: grade C, 61/100, rank #85 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/zaya1-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/zaya1-8b.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### Ling-3.1-flash-1019 (C)\n\nGood for: Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding\n\nAhead on:\n- Documentation and upkeep, 56 against 50\n\nWatch for: 574 GB in FP8 with no smaller build from inclusionAI, so no single machine under 690 GB of GPU memory runs it\n\n### ZAYA1-8B (C)\n\nGood for: People who want a small, fast reasoning model for maths and code and can live without tool calling\n\nAhead on:\n- Reach, 80 against 60\n- Risk, 55 against 45\n\nWatch for: Tool calling needs a parser that only Zyphra's vLLM fork has\n\n\n## Why the edge\n\n### Reach: ZAYA1-8B +20\n\n- Ling-3.1-flash-1019 (60): Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build. Runtimes 25, Released model code in Transformers 5.22.2 (bailing_hybrid), vLLM 0.33.0 (BailingMoeV3ForCausalLM, with ling3 tool and reasoning parsers), SGLang 0.5.23 (bailing_moe_v3.py, its bailing_hybrid config and MTP module) and llama.cpp b12242 (bailingmoe3), and Ollama, credited through its pinned llama.cpp as on the Ling-3.0-tiny listing: v0.40.16 sets LLAMA_CPP_VERSION to b12177. Builds 10, the release is FP8, the one quantised precision inclusionAI publishes for it. Terms 15, MIT in the card's metadata, with no use policy or other terms added on the card or in the repository. Download 10, the Hub API's model info gives gated false on 10 November 2026, so the files download with no account and no terms to accept. Hosted 0, the Hub API's provider mapping is empty for this repository on 10 November 2026. 0 + 25 + 10 + 15 + 10 + 0 = 60.\n- ZAYA1-8B (80): Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80.\n\n### Risk: ZAYA1-8B +10\n\n- Ling-3.1-flash-1019 (45): File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the repository's configuration_bailing_moe_v3.py, since vLLM 0.33.0 registers no bailing_hybrid config of its own. Provenance 15, files in the inclusionAI organisation that inclusion-ai.org links to, per the Ling-3.0-tiny listing (10). Safety evaluation 0, no safety results for the model on its card or in the training-content summary. Agent guidance 0, the card has nothing on prompt injection, refusals or safeguards, and inclusionAI publishes no guardrail probe for this model as it did for Ling 3.0. Licence risk 15, MIT with no use policy, no field-of-use limits, no threshold and no clause letting inclusionAI change or revoke it. Security programme 0, www.inclusion-ai.org answers 404 for security.txt on 10 November 2026, and the Ling-3.0-tiny listing found no SECURITY.md or disclosure policy in the inclusionAI .github repository. 15 + 15 + 0 + 0 + 15 + 0 = 45.\n- ZAYA1-8B (55): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55.\n\n### Documentation and upkeep: Ling-3.1-flash-1019 +6\n\n- Ling-3.1-flash-1019 (56): Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claimed) are on the card. Training data 15, the training-content summary the card links names the source categories (Common Crawl and other public datasets, commercially licensed data, the Ant Spider crawler, synthetic data), the size band (over 10 trillion text tokens), data collected up to about July 2026 and the filtering, without listing datasets with sizes. Last change 20, the newest commit, on 4 November 2026, edited the card, six days before this check, and the files went up on 27 October. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (both opened on 27 October 2026) has a reply from an inclusionAI member. Version policy 5, the update went into a repository of its own and Ling-3.1-flash and Ling 3.0 stay in theirs. File health 5, the card states a 1M-token context while config.json gives 262,144 with no rope scaling, and its serve commands name the earlier repository as the model path. 11 + 15 + 20 + 0 + 5 + 5 = 56.\n- ZAYA1-8B (50): Model card 5, Intended use and the parameter counts are on the card. Training data 0, Nothing on the card about the training data. Last change 10, the main repository last changed on 26 June 2026 (the checkpoint reshaped for Transformers), 137 days before this check, and the quantised repositories on 2 July, 131 days. Responsiveness 20, Of the 16 most recent discussions that aren't pull requests (7 May to 14 August 2026), 10 have a reply from a Zyphra member, which is most. Version policy 5, the original checkpoint is kept as ZAYA1-8B-legacy and the card says so at the top, without a date. File health 10, Config, template and card agree on the architecture after the reshape. 5 + 0 + 10 + 20 + 5 + 10 = 50.\n\n## Score by category\n\n| Category | Weight | Ling-3.1-flash-1019 | ZAYA1-8B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 60 | 80 | ZAYA1-8B +20 |\n| Risk | 20% (20 this run) | 45 | 55 | ZAYA1-8B +10 |\n| Agent interface | 10% (10 this run) | 60 | 60 | even |\n| Documentation and upkeep | 10% (10 this run) | 56 | 50 | Ling-3.1-flash-1019 +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **54.8 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Ling-3.1-flash-1019 | ZAYA1-8B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | inclusionAI (Ant Group) | Zyphra |\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 | 2026-11-04 | 2026-07-02 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n\n## Verdicts\n\n**Ling-3.1-flash-1019.** inclusionAI's newest flagship, a 560B hybrid mixture of experts under plain MIT that vLLM, SGLang, Transformers and llama.cpp run in released versions. It ships only as 574 GB of FP8, so it needs a multi-GPU server. The card overstates the context, documents little about tool calls, and has no safety results.\n\n**ZAYA1-8B.** A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.\n\n## Before you call either\n\n### Ling-3.1-flash-1019\n\n1. Serve it with SGLang 0.5.23 or later on 8 H200 or 4 GB300 GPUs, per the card, and use this repository's name as the model path, not the earlier one the card's command shows\n2. With vLLM pass `--trust-remote-code`, `--tool-call-parser ling3` and `--reasoning-parser ling3`\n3. Set `chat_template_kwargs` `enable_thinking` false for direct answers. Reasoning comes back in `reasoning_content` per SGLang's cookbook\n4. Plan on 262,144 tokens of context. The 1M figure needs the YaRN override in SGLang's cookbook\n5. Use temperature 1.0, top_p 0.95 and top_k 20, per the card\n6. Validate JSON output yourself, since structured output isn't documented\n\n### ZAYA1-8B\n\n1. Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork\n2. Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in\n3. Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work\n4. Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes\n5. The quantised repositories have no licence tag. The main one is Apache 2.0\n\n## Questions\n\n### Which is better for AI agents, Ling-3.1-flash-1019 or ZAYA1-8B?\n\nZAYA1-8B scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 2 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-zaya1-8b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"ling-3-1-flash-1019\", \"b\": \"zaya1-8b\"}`. From a terminal: `anchor compare ling-3-1-flash-1019 zaya1-8b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/ling-3-1-flash-1019.json and https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json\n\n## Other comparisons with Ling-3.1-flash-1019 or ZAYA1-8B\n\n- [Agents-A1-4B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/agents-a1-4b-vs-ling-3-1-flash-1019.md)\n- [Agents-A1-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-zaya1-8b.md)\n- [Apertus v1.5 8B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ling-3-1-flash-1019.md)\n- [Apertus v1.5 8B vs ZAYA1-8B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-zaya1-8b.md)\n- [Apodex-1.1-mini vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ling-3-1-flash-1019.md)\n- [Apodex-1.1-mini vs ZAYA1-8B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-zaya1-8b.md)\n- [Arete-27B vs 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Unlimited-OCR-2 vs ZAYA1-8B](https://www.anchorterminal.com/compare/unlimited-ocr-2-vs-zaya1-8b.md)\n- [WeVisOne-VL-2B vs ZAYA1-8B](https://www.anchorterminal.com/compare/wevisone-vl-2b-vs-zaya1-8b.md)\n- [WeVisOne-VL-4B vs ZAYA1-8B](https://www.anchorterminal.com/compare/wevisone-vl-4b-vs-zaya1-8b.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-11", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": 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