{ "data": { "a": { "slug": "jais-3", "name": "Jais 3", "vendor": "Institute of Foundation Models (MBZUAI) and Inception42", "vendorUrl": "https://ifm.ai/blog/jais3/", "kind": "model", "category": "inference", "summary": "Jais 3 is an open-weight family of Arabic and English reasoning models from MBZUAI's Institute of Foundation Models and Inception42, from 0.9B to 375B parameters with up to 512K tokens of context, released under Apache-2.0 for self-hosting.", "url": "https://www.anchorterminal.com/tools/jais-3", "markdownUrl": "https://www.anchorterminal.com/tools/jais-3.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/jais-3.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/jais-3.json", "dns": "jais-3.grade.anchorterminal.com", "repo": "https://huggingface.co/inception42/Jais-3-375B-A23B", "license": "Apache-2.0, declared in the metadata of every model card read. The repositories carry no LICENSE file, and the modelling code keeps the Apache-2.0 header of the Qwen3-MoE code it was generated from", "transports": [ "http" ], "packages": [], "auth": "none", "authNotes": "No account or key. The inception42 and IFM repositories on Hugging Face are not gated and download anonymously. A local server has whatever authentication the owner adds, such as vLLM's `--api-key`. The cards' examples call the local server with `api_key=\"EMPTY\"`.", "pricing": "free", "pricingNotes": "Free to download and run under Apache-2.0, with the owner's GPUs as the cost. No hosted endpoint from IFM or Inception42 was found, OpenRouter lists no Jais model, and Hugging Face shows no inference provider for the main repositories (checked 2026-10-17).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402. Jais 3 is a set of weights the owner serves, with no payment route and no hosted API from the makers found (checked 2026-10-17).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-17" }, "docsUrl": "https://huggingface.co/inception42/Jais-3-375B-A23B", "capabilities": [ "inference.llm", "inference.open-weights", "inference.local" ], "tags": [ "model", "open-weights", "self-hosted", "local", "free", "no-card", "apache-2.0", "openai-compatible", "gpu", "apple-silicon", "mlx", "new" ], "lastRelease": "2026-10-15", "graded": true, "anchor": { "graded": true, "score": 52.1, "grade": "D", "agentReady": false, "rank": 906, "ranked": true, "rankOf": 1260, "categoryRank": 27, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 62, "payments": 60, "reliability": 48, "schema": 54, "security": 31, "transparency": 55 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-17" }, "negative": 0, "verdict": "Jais 3 runs on the owner's hardware through OpenAI-compatible servers in vLLM and SGLang, with tool calls, three reasoning levels and a 512K context, from a 2.2 GB 0.9B model to a 758 GB 375B one. The weights download without sign-up under Apache-2.0, but every launch command trusts remote code, and no technical report or security contact is published.", "bestFor": "An agent or team that needs Arabic and English reasoning and tool use on its own hardware, from a laptop-sized 0.9B to a cluster-sized 375B, under Apache-2.0.", "strengths": [ "Six checkpoints from 0.9B (2.2 GB) to 375B-A23B (758 GB), with FP8, GGUF and MLX builds from IFM", "Apache-2.0 on every card read, ungated downloads, and the CPT, Cooldown, SFT and FTPO training checkpoints published as branches", "With the `k2_horizon` parsers, reasoning returns in `reasoning_content` and tool calls as `tool_calls`, in JSON, XML or typed XML formats", "Launch recipes in the vLLM and SGLang projects' own docs, and K2 Horizon support merged into llama.cpp's master branch", "The chat template validates tool schemas and rejects unknown options with named errors, such as an unsupported `reasoning_effort`" ], "weaknesses": [ "Every documented vLLM, SGLang, Transformers and MLX command passes `--trust-remote-code`, so the repository's Python runs on the host", "The 375B-A23B reference deployment is 16 H100 GPUs across two nodes, or one 8-GPU H200 node", "The technical report and code repository are marked 'coming soon', and IFM's own blog and press release sit behind a bot check", "No LICENSE file in the repositories, no changelog, no deprecation policy and no security contact or security.txt found", "Released on 15 October 2026, with template fixes on 14 and 15 October, and mlx-lm doesn't yet parse its reasoning or tool calls" ], "agentNotes": [ "Start vLLM or SGLang with `--reasoning-parser k2_horizon`, and add `--tool-call-parser k2_horizon` (vLLM also `--enable-auto-tool-choice`) for tools, or tool calls come back as raw text", "Pass `reasoning_effort` (`high`, `medium` or `low`) and `tool_call_format` inside `chat_template_kwargs`. Other values return a template error", "Send each earlier assistant turn back with `reasoning_content` as a string, even an empty one. A missing or null thinking field makes the template raise an error", "Send your own system message, or set `default_system_prompt` to an empty string. Without one the template inserts an identity prompt naming IFM, Inception42 and Cerebras", "Budget at least 32,768 output tokens at `high` effort, which the cards recommend for every request" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.1 } ], "editorialScores": { "ergonomics": 65, "maintenance": 62, "payments": 60, "reliability": 48, "schema": 54, "security": 31, "transparency": 51 }, "provenanceScore": 58, "checked": { "categories": { "ergonomics": "2026-10-17", "maintenance": "2026-10-17", "payments": "2026-10-17", "reliability": "2026-10-17", "schema": "2026-10-17", "security": "2026-10-17", "transparency": "2026-10-17" }, "last": "2026-10-17", "lastMoved": "2026-10-27", "oldest": "2026-10-17", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "vllm serve inception42/Jais-3-32B \\\n --trust-remote-code \\\n --dtype bfloat16 \\\n --tensor-parallel-size 2 \\\n --reasoning-parser k2_horizon \\\n --enable-auto-tool-choice \\\n --tool-call-parser k2_horizon", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"model\": \"inception42/Jais-3-32B\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Summarise this contract in Arabic.\"}],\n \"max_tokens\": 32768,\n \"chat_template_kwargs\": {\"reasoning_effort\": \"high\"}\n }'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/jais-3" }, "area": "models", "provenance": { "legalEntity": "Mohamed bin Zayed University of Artificial Intelligence (Institute of Foundation Models), with Inception42 (a G42 company)", "domain": "ifm.ai", "domainRegistered": "2022-09-06", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-17", "notes": [ "The chat template's default system prompt names the Institute of Foundation Models (IFM) at MBZUAI, with Inception42 (a G42 company) and Cerebras, and gives MBZUAI's Arabic name, Mohamed bin Zayed University of Artificial Intelligence. The citation names the IFM, Inception42 and Cerebras teams. No registered company name for Inception42 was read first-hand.", "RDAP gives a registration date of 6 September 2022 for ifm.ai. The weights are on huggingface.co under the inception42 and IFM organisations.", "The licence is Apache-2.0 in each card's metadata. There is no LICENSE file and no terms or privacy document governing the weights, and no input reaches the makers when the owner serves them.", "ifm.ai answered our reader with a Cloudflare bot check on the press release, the blog post and the sitemap, so they weren't read. inceptionai.ai and mbzuai.ac.ae answered with bot or firewall pages too. ifm.ai/.well-known/security.txt returned 404 on 17 October 2026.", "No hosted endpoint, so no status page. No changelog. The Hugging Face commit history is public and was read." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/jais-3.json", "live": { "slug": "jais-3", "securityTxt": { "url": "https://ifm.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-01T15:42:31.484081501Z" }, "domain": { "domain": "ifm.ai", "registered": "2022-09-06", "source": "https://rdap.identitydigital.services/rdap/domain/ifm.ai", "checkedAt": "2026-11-01T14:11:01.629779131Z" }, "updatedAt": "2026-11-01T15:42:31.484081501Z" } }, "answer": "Tencent Cloud TokenHub scores 59.5 (C) on agent readiness against Jais 3's 52.1 (D), and leads in 4 of 7 scored categories. Jais 3 leads on payments \u0026 pricing.", "b": { "slug": "tencent-tokenhub", "name": "Tencent Cloud TokenHub", "vendor": "Tencent Cloud", "vendorUrl": "https://cloud.tencent.com", "kind": "router", "category": "inference", "summary": "Tencent Cloud TokenHub is a hosted model gateway serving Tencent's Hy models and third-party models such as DeepSeek, Kimi, GLM and MiniMax through OpenAI-compatible and Anthropic-compatible endpoints in Guangzhou and Singapore, with per-key scopes and quotas.", "url": "https://www.anchorterminal.com/tools/tencent-tokenhub", "markdownUrl": "https://www.anchorterminal.com/tools/tencent-tokenhub.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/tencent-tokenhub.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/tencent-tokenhub.json", "dns": "tencent-tokenhub.grade.anchorterminal.com", "repo": "https://github.com/TencentCloud/THCLI", "license": "Proprietary service under the TokenHub Terms of Service, the TokenHub SLA and the Tencent Cloud Service Agreement, with a special note for third-party deployed models. The `tencent-tokenhub-cli` package is Apache-2.0", "transports": [ "http" ], "remoteUrl": "https://tokenhub.tencentmaas.com/v1", "packages": [ { "registry": "npm", "name": "tencent-tokenhub-cli" } ], "auth": "api-key", "authNotes": "Bearer API key from the TokenHub console, or `x-api-key` on the Anthropic-style `/v1/messages`. Keys are long-lived, belong to one region (Guangzhou or Singapore), can be limited to chosen models and inference services, up to 200 IP ranges and token quotas, and can be disabled or deleted. They can also be created through the CreateApiKey control-plane call with signed Tencent Cloud credentials, or by `thcli auth login`. The account needs real-name verification first.", "pricing": "usage", "pricingNotes": "Pay per token in CNY, billed hourly. Hy4 preview costs 6 CNY in, 18 CNY out and 0.3 CNY cached per 1M tokens, Hy3 1, 4 and 0.25 CNY. DeepSeek models double at weekday peak hours. Batch is half price for Hy3 and Hy4 preview. Each account gets 1M free tokens per language model for a year, in a campaign to 31 December 2026. Token Plan subscriptions run from 28 to 599 CNY a month (https://cloud.tencent.com/document/product/1823/130055, checked 2026-11-01).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs table of contents, the billing pages or the API usage page. Payment is from a Tencent Cloud account balance, billed hourly (checked 2026-11-01).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 204, "pypiWeekly": null, "asOf": "2026-11-01" }, "docsUrl": "https://cloud.tencent.com/document/product/1823/130058", "rateLimitsUrl": "https://cloud.tencent.com/document/product/1823/136028", "llmsTxt": "https://cloud.tencent.com/document/product/1823/llms.txt", "capabilities": [ "inference.router", "inference.llm", "inference.open-weights", "embed.text", "embed.multimodal", "image.generate", "video.generate", "speech.tts", "speech.stt", "audio.music", "translate.text", "web.search", "obs.gateway" ], "tags": [ "hosted", "router", "usage-based", "free-credit", "openai-compatible", "anthropic-compatible", "llms-txt", "cli", "sla", "batch", "bug-bounty", "no-status-page", "regional-endpoints", "singapore", "chinese", "subscription" ], "lastRelease": "2026-10-24", "graded": true, "anchor": { "graded": true, "score": 59.5, "grade": "C", "agentReady": false, "rank": 646, "ranked": true, "rankOf": 1260, "categoryRank": 18, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 83, "maintenance": 73, "payments": 35, "reliability": 46, "schema": 73, "security": 71, "transparency": 54 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -3, "negativeNotes": [ "2026-10-17. -3, a breaking change without notice. DeepSeek-V4.1-Flash (directly supplied) was moved to its 1017 version under the same model ids and prices on 17 October 2026, and the notice came two days later (https://cloud.tencent.com/announce/detail/2516). Callers pinned to the id got a different model's behaviour with no warning. One term at the floor: the API didn't change. The founder's decision, 1 November 2026." ], "verdict": "Keys can be limited to chosen models, source IPs and token quotas, errors name their source and code, and a 99.5% SLA covers paid use of models Tencent runs. Sign-up needs a Tencent Cloud account with real-name verification, prices are in CNY, no public status page was found, and 18 model retirement notices ran from April to October 2026.", "bestFor": "Teams in or near Tencent Cloud that want one key and bill for Tencent's Hy models and Chinese open-weight models (DeepSeek, Kimi, GLM, MiniMax, Qwen, MiMo) with per-key limits and CNY billing.", "strengths": [ "API keys can be limited to chosen models and inference services, up to 200 source IP ranges, and daily, monthly or total token quotas", "One base URL answers OpenAI Chat Completions, OpenAI Responses and Anthropic Messages calls, and `GET /v1/models` marks models due to retire as `pre-offline`", "Error bodies carry a six-digit code, English and Chinese messages, the source (client, gateway or upstream) and a request ID, and 429s can carry `Retry-After`", "A published SLA promises 99.5% monthly availability with voucher credits of 10 to 50 per cent of the month's fee, for paid use of models Tencent runs", "Per-call audit logs (request ID, key, client IP, status, tokens, latency) can be delivered to the customer's own Tencent Cloud CLS log service" ], "weaknesses": [ "Sign-up needs a Tencent Cloud account with real-name verification. The international site answered with a bot check, so access from outside China was not established", "No public status page was found. A four-hour outage of DeepSeek's directly supplied models on 15 October 2026 appears only as a compensation notice", "18 model retirement notices from 21 April to 22 October 2026. Those read gave 21 to 33 days, and eligible callers are switched to a successor at its price", "DeepSeek's directly supplied models send inputs to DeepSeek under its own terms, and the TokenHub SLA does not cover them", "Per-model RPM and TPM limits for chat models are shown in the console and the quota API, not in the public docs" ], "agentNotes": [ "Use `https://tokenhub.tencentmaas.com/v1` with keys made for Guangzhou and `https://tokenhub-intl.tencentmaas.com/v1` with keys made for Singapore. Keys do not work across the two", "Send the key as `Authorization: Bearer` on the OpenAI paths and as `x-api-key` on `/v1/messages`", "Parse `error.code` as a string or a number, since 429 codes can come back as integers, and wait for `Retry-After` before retrying", "Take model ids from `GET /v1/models` and watch for `pre-offline`. The quickstart's `deepseek-v3` example is not in the current model list", "Expect DeepSeek prices to double on weekdays from 9am to noon and 2pm to 6pm Beijing time, when the peak rate applies" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 59.5 } ], "editorialScores": { "ergonomics": 83, "maintenance": 73, "payments": 35, "reliability": 46, "schema": 73, "security": 71, "transparency": 59 }, "provenanceScore": 49, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "npm i -g tencent-tokenhub-cli", "http": "curl https://tokenhub.tencentmaas.com/v1/models \\\n -H \"Authorization: Bearer $TOKENHUB_API_KEY\"", "claudeCode": "{\n \"env\": {\n \"ANTHROPIC_BASE_URL\": \"https://tokenhub.tencentmaas.com\",\n \"ANTHROPIC_AUTH_TOKEN\": \"YOUR_API_KEY\",\n \"ANTHROPIC_MODEL\": \"hy3\"\n }\n}" }, "letme": { "capability": "https://letme.dev/inference.router", "tool": "https://letme.dev/tencent-tokenhub" }, "area": "models", "provenance": { "legalEntity": "Tencent Cloud Computing (Beijing) Co., Ltd. (腾讯云计算（北京）有限责任公司)", "domain": "tencentmaas.com", "domainRegistered": "2026-03-13", "endpointOnVendorDomain": false, "terms": "https://cloud.tencent.com/document/product/301/129852", "privacy": "https://privacy.qq.com/document/preview/91d5fd3c98ce4468ae462ac59233bba2", "statusPage": "", "changelog": "https://cloud.tencent.com/document/product/1823/130675", "securityTxt": "none", "checked": "2026-11-01", "notes": [ "The TokenHub Terms of Service (effective 14 September 2026), the SLA (effective 23 April 2026) and the special note on third-party deployed models (effective 14 September 2026) name 腾讯云计算（北京）有限责任公司. The docs footer also names 深圳市腾讯计算机系统有限公司 as ICP licence holder.", "The TokenHub privacy policy is linked from the docs to privacy.qq.com, which renders only with JavaScript, so it was not read. privacy.qq.com has no robots.txt (404).", "No public status page was found. status.cloud.tencent.com did not answer, and the Tencent Cloud health dashboard documentation answered with a bot check.", "security.txt answered 404 on cloud.tencent.com, www.tencent.com and tokenhub.tencentmaas.com. Tencent's bug bounty policy at en.security.tencent.com lists Tencent Cloud in scope.", "RDAP at Verisign gives tencentmaas.com a registration date of 13 March 2026 with no registrant. The API answers at tokenhub.tencentmaas.com and tokenhub-intl.tencentmaas.com, named in Tencent Cloud's API usage page.", "cloud.tencent.com allows these docs in robots.txt. Its pages answered some requests with a JavaScript bot check, which was not passed. The pages were read when a later plain request returned them. www.tencentcloud.com answered robots.txt with a bot check, so the international site was not read." ], "score": 49 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/tencent-tokenhub.json", "live": { "slug": "tencent-tokenhub", "probe": { "target": "https://tokenhub.tencentmaas.com/v1", "method": "get", "lastAt": "2026-11-02T00:56:24.101434531Z", "lastOk": true, "lastStatus": 404, "lastMs": 795, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 826, "p95ms24h": 1067, "samples24h": 28, "samples30d": 28, "days": [ { "date": "2026-11-01", "probes": 18, "ok": 18 }, { "date": "2026-11-02", "probes": 10, "ok": 10 } ] }, "updatedAt": "2026-11-02T00:56:24.101434531Z" } }, "edges": [ { "by": 40, "category": "security", "leads": "tencent-tokenhub", "name": "Security \u0026 auth", "reasons": { "a": "Read as software the owner runs. No account or key, ungated downloads, and server authentication is the owner's to add (12 of 30). A model that calls whatever tools the operator wires in. The cards rule high-stakes decisions without human oversight out of scope, but nothing in the model or template enforces approval (6 of 20). The template renders tool results in their own `tool` role, but string results go in as raw text (only non-string content is serialised with `tojson`), no escaping of special-token sequences in caller or tool text was found, and no injection guidance or results are published (4 of 15). No call log of its own. Visibility depends on the serving stack (5 of 15). Every launch command passes `--trust-remote-code`, so `modeling_k2_horizon.py` from the repository runs on the host. We read it and found only torch and transformers imports. No security.txt on ifm.ai (404), no security contact on the cards, no safety evaluation published, and the technical report is 'coming soon' (4 of 20). 31.", "b": "Router, read on the model lines. Bearer keys can be limited to chosen models and inference services, up to 200 source IP ranges and daily, monthly or total token quotas, can be disabled or deleted, and can be created in code through CreateApiKey with signed Tencent Cloud credentials. Keys are long-lived with no expiry setting or built-in rotation (26 of 30). Clause 2.17 of the terms says inputs are not used to train Tencent Cloud's own models, and the FAQ says data is not used for training. Inputs to third-party deployed models (DeepSeek's directly supplied ones) go to DeepSeek under its terms (14 of 20). Clause 2.14 keeps data only as long as the service needs, with no periods stated. When a customer asks for generated content without AI labels, Tencent Cloud keeps logs of who received it for at least six months. No zero-retention option was found (7 of 15). Per-call audit logs (request ID, key, client IP, status, tokens, latency) and optional full call logs go to the customer's CLS, billed separately, with usage by key and a monitoring dashboard (14 of 15). No security.txt on cloud.tencent.com, www.tencent.com or tokenhub.tencentmaas.com (404). Tencent's bug bounty through TSRC lists Tencent Cloud in scope. No certification for TokenHub was checked (10 of 20)." }, "scores": { "a": 31, "b": 71 } }, { "by": 25, "category": "payments", "leads": "jais-3", "name": "Payments \u0026 pricing", "reasons": { "a": "Self-hosted rule. Apache-2.0 weights with nothing to buy and no hosted option from the makers (20). Free to run with no card (20). Downloads are ungated and anonymous, so an agent can fetch the weights with no sign-up (20). No payment protocol (0). 60.", "b": "No x402, MPP or L402 (0). Per-token prices for every model are public in CNY for Guangzhou and Singapore, with DeepSeek's peak and off-peak rates (20). Each account gets 1M free tokens per language model, valid for a year, in a campaign running to 31 December 2026. No card is mentioned, but the account needs real-name verification, so this line takes 15 of 20. A person signs up and completes real-name verification in a browser. Keys can then be created in code or by `thcli auth login`, but only from that account (0)." }, "scores": { "a": 60, "b": 35 } }, { "by": 19, "category": "schema", "leads": "tencent-tokenhub", "name": "Schema \u0026 documentation", "reasons": { "a": "Read for a model the owner serves. No specification of its own. The contract is the Jinja chat template, which validates tool JSON Schemas (required fields must exist in properties) and rejects unknown options, plus the OpenAI-compatible servers in vLLM and SGLang with the `k2_horizon` parsers (10 of 25). The cards are Markdown on Hugging Face, and SGLang's docs have an llms.txt, but no llms.txt or Markdown docs from IFM were found and ifm.ai couldn't be read (5 of 10). Each card states intended use, four out-of-scope uses, limitations and per-size serving advice (15 of 20). `reasoning_effort` and `tool_call_format` are enums enforced with errors, and tools take JSON Schema. The 375B card describes `low` as no reasoning and omits `medium`, which the template accepts, and structured output isn't documented (10 of 15). Python examples for a reasoning call and a tool loop, commands for five runtimes, and named template errors, but no error reference for a served model (11 of 15). No changelog or version scheme. Training-stage branches and public commit history (3 of 15). 54.", "b": "Router, scored on the API lines. No OpenAPI file for the inference routes. Field pages document the OpenAI Chat Completions, OpenAI Responses and Anthropic Messages formats as TokenHub implements them, and the control plane is a Tencent Cloud API 3.0 service (version 2026-03-22) with typed parameters, API Explorer and SDKs (12 of 25). An llms.txt at cloud.tencent.com/document/product/1823/llms.txt links a Markdown copy of each docs page (10). The docs say which models support thinking, tools, structured output and caching, how TokenHub departs from each standard protocol, and which DeepSeek model suits which job. The quickstart's examples still use `deepseek-v3`, which is not in the model list, and Qwen3.5 stays in the list with a past shutdown date (13 of 20). Protocol pages list each field with type, required flag and default, and control-plane parameters carry enums and required flags (10 of 15). Examples in curl, Python, Node.js, Java and Go, and an error page listing 30 codes with HTTP status, cause and fix (14 of 15). Paths carry `/v1`, release notes are dated monthly from 7 April to 24 October 2026, and the control-plane API has a dated history of 26 releases to 18 September 2026 (14 of 15)." }, "scores": { "a": 54, "b": 73 } }, { "by": 18, "category": "ergonomics", "leads": "tencent-tokenhub", "name": "Agent ergonomics", "reasons": { "a": "Model reading of the checklist (tool use, structured output, caching, context, throughput, defaults and SDKs, errors). OpenAI-format tools come back as `tool_calls` in three selectable wire formats, with a multi-turn loop example. Forced `tool_choice` and parallel calls aren't documented (15 of 20). JSON mode and schemas only through each runtime's guided decoding, not documented by the makers (5 of 15). Prefix caching is the runtime's, and SGLang's page covers HiCache (7 of 10). 524,288 tokens on five of six models, 131,072 on the 0.9B (14 of 15). Uno adapters claim 2.15 times faster decoding for 0.9B to 32B but need IFM's own engine. SGLang lists n-gram speculative decoding and PD disaggregation. No batch mode of its own (7 of 10). Any OpenAI SDK works against a local server, and the 0.9B to 7B fit one GPU. But the cards ask for high effort and 32,768 output tokens on every request, the template inserts an identity system prompt when none is sent, and earlier assistant turns must carry a string thinking field (8 of 15). The template raises named errors for bad options, string-encoded tool arguments and malformed schemas. Server errors are the runtime's (9 of 15). 65.", "b": "Router, read on the model lines. Function calling is marked on most chat models in the model list, with behaviour depending on the model routed (14 of 20). Structured output is marked per model and missing on the MiniMax and Qwen models, and an unsupported `response_format` returns code 400006 (12 of 15). Cache-hit prices are published per model, Kimi K3.1 Pro lists five-minute and one-hour cache writes, and a guide covers `prompt_cache_key` and the `X-Session-ID` header for instance affinity (14 of 15). Most listed chat models have contexts of one million tokens, a judgement call since a router has no default model (15). Batch at half price covers only Hy3 and Hy4 preview, reads and writes JSONL in the customer's own COS bucket and is documented for the Guangzhou endpoint (5 of 10). No TokenHub inference SDK. The OpenAI and Anthropic SDKs work with a changed base URL, and Tencent Cloud SDK 3.0 and the `thcli` CLI cover the control plane (8 of 10). Errors return a code, English and Chinese messages, the source, the upstream code and status and a request ID, and stream errors arrive as SSE error frames (15 of 15)." }, "scores": { "a": 65, "b": 83 } }, { "by": 11, "category": "maintenance", "leads": "tencent-tokenhub", "name": "Maintenance \u0026 community", "reasons": { "a": "Read for an open-weight model released two days before the check. Template changes on 15 October and a citation update on 16 October 2026 (30). One family release, with dated builds before it (FP8 from 29 September, MLX from 1 October, GGUF on 12 and 13 October) and template fixes on 14 and 15 October, but no deprecation notices or successor history to judge. K2 Horizon came on 1 September and Jais 2 in December 2025 (10 of 20). No outside discussions or issues yet on the main repositories, and IFM's GitHub repositories weren't read, so responsiveness can't be seen. The template fixes match the problem IFM's MLX cards describe (7 of 25). Recipes in vLLM's and SGLang's own docs, K2 Horizon support on llama.cpp master and FP8, GGUF and MLX builds from IFM, but no tagged llama.cpp release or native mlx-lm support (11 of 15). Current dependencies (Transformers 5.13 to 5.15, vLLM 0.30), with no CI visible (4 of 10). 62.", "b": "Closed service, read on the model lines. The newest release note is dated 24 October 2026 and the price page was updated on 31 October (30). The four retirement notices read gave 21 to 33 days, and eligible callers are switched to a successor at its price. No minimum notice period is written, and DeepSeek-V4.1-Flash (directly supplied) was moved to the 1017 version under the same ids on 17 October 2026 in a notice dated two days later (7 of 12). 18 retirement notices from 21 April to 22 October 2026, 12 of them since 3 August (3 of 8). Dated release notes and announcements, ticket and phone support around the clock and a Q\u0026A community (13 of 15). Replies on the THCLI repository were not sampled (3 of 10). Tencent Cloud SDK 3.0 in several languages covers the control plane and `tencent-tokenhub-cli` 1.0.2 was published on 30 October 2026. No inference SDK of its own (12 of 15). The CLI has four releases since 15 September 2026, lists no runtime dependencies and needs Node.js 18 or later. CI not checked (5 of 10)." }, "scores": { "a": 62, "b": 73 } } ], "facts": [ { "a": "Model API", "b": "Model router", "name": "Kind" }, { "a": "Institute of Foundation Models (MBZUAI) and Inception42", "b": "Tencent Cloud", "name": "Vendor" }, { "a": "no (local only)", "b": "https://tokenhub.tencentmaas.com/v1", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Pay per use", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0, declared in the metadata of every model card read. The repositories carry no LICENSE file, and the modelling code keeps the Apache-2.0 header of the Qwen3-MoE code it was generated from", "b": "Proprietary service under the TokenHub Terms of Service, the TokenHub SLA and the Tencent Cloud Service Agreement, with a special note for third-party deployed models. The `tencent-tokenhub-cli` package is Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-15", "b": "2026-10-24", "name": "Last release" }, { "a": "no document linked", "b": "couldn't be read", "name": "Terms last updated" }, { "a": "no document linked", "b": "couldn't be read", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "couldn't be read", "name": "Customer content may train models" }, { "a": "not read yet", "b": "couldn't be read", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "couldn't be read", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "couldn't be read", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "couldn't be read", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "204 npm/wk", "name": "Popularity" }, { "a": "2.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Tencent Cloud TokenHub scores 59.5 (C) on agent readiness against Jais 3's 52.1 (D), and leads in 4 of 7 scored categories. Jais 3 leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Jais 3 or Tencent Cloud TokenHub?" }, { "answer": "Jais 3 needs no key. Tencent Cloud TokenHub needs an API key.", "question": "Do Jais 3 and Tencent Cloud TokenHub need an API key?" }, { "answer": "No hosted endpoint is listed for Jais 3. Tencent Cloud TokenHub has a hosted endpoint at https://tokenhub.tencentmaas.com/v1.", "question": "Can an agent call Jais 3 and Tencent Cloud TokenHub without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 60 against 35" ], "also": [ "No key needed to call it", "Free to start without a card", "No incidents deducted, where Tencent Cloud TokenHub loses 3 points for them" ], "goodFor": "An agent or team that needs Arabic and English reasoning and tool use on its own hardware, from a laptop-sized 0.9B to a cluster-sized 375B, under Apache-2.0.", "slug": "jais-3", "watchFor": "Every documented vLLM, SGLang, Transformers and MLX command passes `--trust-remote-code`, so the repository's Python runs on the host" }, { "aheadOn": [ "Schema \u0026 documentation, 73 against 54", "Agent ergonomics, 83 against 65", "Security \u0026 auth, 71 against 31", "Maintenance \u0026 community, 73 against 62" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Teams in or near Tencent Cloud that want one key and bill for Tencent's Hy models and Chinese open-weight models (DeepSeek, Kimi, GLM, MiniMax, Qwen, MiMo) with per-key limits and CNY billing.", "slug": "tencent-tokenhub", "watchFor": "Sign-up needs a Tencent Cloud account with real-name verification. The international site answered with a bot check, so access from outside China was not established" } ], "history": { "jais-3": [ { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.4, "from": 51.7, "fromGrade": "D", "to": 52.1, "toGrade": "D" } ], "tencent-tokenhub": null }, "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.json", "title": "Claude API vs Jais 3", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub.json", "title": "Claude API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-jais-3.json", "title": "Antseed vs Jais 3", "url": "https://www.anchorterminal.com/compare/antseed-vs-jais-3" }, { "json": 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"title": "Jais 3 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/jais-3-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.json", "title": "Jais 3 vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway" }, { "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub.json", "title": "Meta Model API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/minimax-api-vs-tencent-tokenhub.json", "title": "MiniMax API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/minimax-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/mistral-api-vs-tencent-tokenhub.json", "title": "Mistral AI API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/mistral-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-tencent-tokenhub.json", "title": "Muse Spark Open vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/novita-ai-vs-tencent-tokenhub.json", "title": "Novita AI vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/novita-ai-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/openai-api-vs-tencent-tokenhub.json", "title": "OpenAI API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/openai-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/openrouter-vs-tencent-tokenhub.json", "title": "OpenRouter vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/openrouter-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub.json", "title": "Beam 1.0 vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/reflection-beam-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/sambanova-vs-tencent-tokenhub.json", "title": "SambaCloud vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/sambanova-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/siliconflow-vs-tencent-tokenhub.json", "title": "SiliconFlow vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/siliconflow-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/simplismart-vs-tencent-tokenhub.json", "title": "Simplismart vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/simplismart-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/stepfun-api-vs-tencent-tokenhub.json", "title": "StepFun API vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/stepfun-api-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference.json", "title": "Tencent Cloud TokenHub vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-tencent-tokenhub.json", "title": "Nemotron 3.5 Super VL vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-super-vl-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/prism-inference-vs-tencent-tokenhub.json", "title": "Prism Inference vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/prism-inference-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-tencent-tokenhub.json", "title": "Antseed vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/antseed-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/ramp-router-vs-tencent-tokenhub.json", "title": "Router.com (Ramp Router) vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/ramp-router-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/routerplus-vs-tencent-tokenhub.json", "title": "RouterPlus vs Tencent Cloud TokenHub", "url": "https://www.anchorterminal.com/compare/routerplus-vs-tencent-tokenhub" }, { "json": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vercel-ai-gateway.json", "title": "Tencent Cloud TokenHub vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/tencent-tokenhub-vs-vercel-ai-gateway" } ], "panel": null, "scores": [ { "by": 2, "edge": "jais-3", "jais-3": 48, "key": "reliability", "name": "Reliability", "tencent-tokenhub": 46, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 19, "edge": "tencent-tokenhub", "jais-3": 54, "key": "schema", "name": "Schema \u0026 documentation", "tencent-tokenhub": 73, "weight": 13 }, { "by": 18, "edge": "tencent-tokenhub", "jais-3": 65, "key": "ergonomics", "name": "Agent ergonomics", "tencent-tokenhub": 83, "weight": 13 }, { "by": 40, "edge": "tencent-tokenhub", "jais-3": 31, "key": "security", "name": "Security \u0026 auth", "tencent-tokenhub": 71, "weight": 14 }, { "by": 25, "edge": "jais-3", "jais-3": 60, "key": "payments", "name": "Payments \u0026 pricing", "tencent-tokenhub": 35, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 11, "edge": "tencent-tokenhub", "jais-3": 62, "key": "maintenance", "name": "Maintenance \u0026 community", "tencent-tokenhub": 73, "weight": 7 }, { "by": 1, "edge": "jais-3", "jais-3": 55, "key": "transparency", "name": "Transparency \u0026 trust", "tencent-tokenhub": 54, "weight": 7 } ], "summary": "Tencent Cloud TokenHub scores 59.5 (C) on agent readiness against Jais 3's 52.1 (D), and leads in 4 of 7 scored categories. Jais 3 leads on payments \u0026 pricing. Both do llm inference.", "tasks": null, "tutorials": [], "verdicts": { "jais-3": "Jais 3 runs on the owner's hardware through OpenAI-compatible servers in vLLM and SGLang, with tool calls, three reasoning levels and a 512K context, from a 2.2 GB 0.9B model to a 758 GB 375B one. The weights download without sign-up under Apache-2.0, but every launch command trusts remote code, and no technical report or security contact is published.", "tencent-tokenhub": "Keys can be limited to chosen models, source IPs and token quotas, errors name their source and code, and a 99.5% SLA covers paid use of models Tencent runs. Sign-up needs a Tencent Cloud account with real-name verification, prices are in CNY, no public status page was found, and 18 model retirement notices ran from April to October 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub", "json": "https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.min.md" }, "markdown": "Tencent Cloud TokenHub scores 59.5 (C) on agent readiness against Jais 3's 52.1 (D), and leads in 4 of 7 scored categories. Jais 3 leads on payments \u0026 pricing. Both do llm inference.\n\n- Jais 3: grade D, 52.1/100, rank #906 of 1260. Markdown https://www.anchorterminal.com/tools/jais-3.md · JSON https://www.anchorterminal.com/api/v1/tools/jais-3.json\n- Tencent Cloud TokenHub: grade C, 59.5/100, rank #646 of 1260. Markdown https://www.anchorterminal.com/tools/tencent-tokenhub.md · JSON https://www.anchorterminal.com/api/v1/tools/tencent-tokenhub.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 529 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Jais 3 (D)\n\nGood for: An agent or team that needs Arabic and English reasoning and tool use on its own hardware, from a laptop-sized 0.9B to a cluster-sized 375B, under Apache-2.0.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 35\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n- No incidents deducted, where Tencent Cloud TokenHub loses 3 points for them\n\nWatch for: Every documented vLLM, SGLang, Transformers and MLX command passes `--trust-remote-code`, so the repository's Python runs on the host\n\n### Tencent Cloud TokenHub (C)\n\nGood for: Teams in or near Tencent Cloud that want one key and bill for Tencent's Hy models and Chinese open-weight models (DeepSeek, Kimi, GLM, MiniMax, Qwen, MiMo) with per-key limits and CNY billing.\n\nAhead on:\n- Schema \u0026 documentation, 73 against 54\n- Agent ergonomics, 83 against 65\n- Security \u0026 auth, 71 against 31\n- Maintenance \u0026 community, 73 against 62\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Sign-up needs a Tencent Cloud account with real-name verification. The international site answered with a bot check, so access from outside China was not established\n\n\n## Why the edge\n\n### Security \u0026 auth: Tencent Cloud TokenHub +40\n\n- Jais 3 (31): Read as software the owner runs. No account or key, ungated downloads, and server authentication is the owner's to add (12 of 30). A model that calls whatever tools the operator wires in. The cards rule high-stakes decisions without human oversight out of scope, but nothing in the model or template enforces approval (6 of 20). The template renders tool results in their own `tool` role, but string results go in as raw text (only non-string content is serialised with `tojson`), no escaping of special-token sequences in caller or tool text was found, and no injection guidance or results are published (4 of 15). No call log of its own. Visibility depends on the serving stack (5 of 15). Every launch command passes `--trust-remote-code`, so `modeling_k2_horizon.py` from the repository runs on the host. We read it and found only torch and transformers imports. No security.txt on ifm.ai (404), no security contact on the cards, no safety evaluation published, and the technical report is 'coming soon' (4 of 20). 31.\n- Tencent Cloud TokenHub (71): Router, read on the model lines. Bearer keys can be limited to chosen models and inference services, up to 200 source IP ranges and daily, monthly or total token quotas, can be disabled or deleted, and can be created in code through CreateApiKey with signed Tencent Cloud credentials. Keys are long-lived with no expiry setting or built-in rotation (26 of 30). Clause 2.17 of the terms says inputs are not used to train Tencent Cloud's own models, and the FAQ says data is not used for training. Inputs to third-party deployed models (DeepSeek's directly supplied ones) go to DeepSeek under its terms (14 of 20). Clause 2.14 keeps data only as long as the service needs, with no periods stated. When a customer asks for generated content without AI labels, Tencent Cloud keeps logs of who received it for at least six months. No zero-retention option was found (7 of 15). Per-call audit logs (request ID, key, client IP, status, tokens, latency) and optional full call logs go to the customer's CLS, billed separately, with usage by key and a monitoring dashboard (14 of 15). No security.txt on cloud.tencent.com, www.tencent.com or tokenhub.tencentmaas.com (404). Tencent's bug bounty through TSRC lists Tencent Cloud in scope. No certification for TokenHub was checked (10 of 20).\n\n### Payments \u0026 pricing: Jais 3 +25\n\n- Jais 3 (60): Self-hosted rule. Apache-2.0 weights with nothing to buy and no hosted option from the makers (20). Free to run with no card (20). Downloads are ungated and anonymous, so an agent can fetch the weights with no sign-up (20). No payment protocol (0). 60.\n- Tencent Cloud TokenHub (35): No x402, MPP or L402 (0). Per-token prices for every model are public in CNY for Guangzhou and Singapore, with DeepSeek's peak and off-peak rates (20). Each account gets 1M free tokens per language model, valid for a year, in a campaign running to 31 December 2026. No card is mentioned, but the account needs real-name verification, so this line takes 15 of 20. A person signs up and completes real-name verification in a browser. Keys can then be created in code or by `thcli auth login`, but only from that account (0).\n\n### Schema \u0026 documentation: Tencent Cloud TokenHub +19\n\n- Jais 3 (54): Read for a model the owner serves. No specification of its own. The contract is the Jinja chat template, which validates tool JSON Schemas (required fields must exist in properties) and rejects unknown options, plus the OpenAI-compatible servers in vLLM and SGLang with the `k2_horizon` parsers (10 of 25). The cards are Markdown on Hugging Face, and SGLang's docs have an llms.txt, but no llms.txt or Markdown docs from IFM were found and ifm.ai couldn't be read (5 of 10). Each card states intended use, four out-of-scope uses, limitations and per-size serving advice (15 of 20). `reasoning_effort` and `tool_call_format` are enums enforced with errors, and tools take JSON Schema. The 375B card describes `low` as no reasoning and omits `medium`, which the template accepts, and structured output isn't documented (10 of 15). Python examples for a reasoning call and a tool loop, commands for five runtimes, and named template errors, but no error reference for a served model (11 of 15). No changelog or version scheme. Training-stage branches and public commit history (3 of 15). 54.\n- Tencent Cloud TokenHub (73): Router, scored on the API lines. No OpenAPI file for the inference routes. Field pages document the OpenAI Chat Completions, OpenAI Responses and Anthropic Messages formats as TokenHub implements them, and the control plane is a Tencent Cloud API 3.0 service (version 2026-03-22) with typed parameters, API Explorer and SDKs (12 of 25). An llms.txt at cloud.tencent.com/document/product/1823/llms.txt links a Markdown copy of each docs page (10). The docs say which models support thinking, tools, structured output and caching, how TokenHub departs from each standard protocol, and which DeepSeek model suits which job. The quickstart's examples still use `deepseek-v3`, which is not in the model list, and Qwen3.5 stays in the list with a past shutdown date (13 of 20). Protocol pages list each field with type, required flag and default, and control-plane parameters carry enums and required flags (10 of 15). Examples in curl, Python, Node.js, Java and Go, and an error page listing 30 codes with HTTP status, cause and fix (14 of 15). Paths carry `/v1`, release notes are dated monthly from 7 April to 24 October 2026, and the control-plane API has a dated history of 26 releases to 18 September 2026 (14 of 15).\n\n### Agent ergonomics: Tencent Cloud TokenHub +18\n\n- Jais 3 (65): Model reading of the checklist (tool use, structured output, caching, context, throughput, defaults and SDKs, errors). OpenAI-format tools come back as `tool_calls` in three selectable wire formats, with a multi-turn loop example. Forced `tool_choice` and parallel calls aren't documented (15 of 20). JSON mode and schemas only through each runtime's guided decoding, not documented by the makers (5 of 15). Prefix caching is the runtime's, and SGLang's page covers HiCache (7 of 10). 524,288 tokens on five of six models, 131,072 on the 0.9B (14 of 15). Uno adapters claim 2.15 times faster decoding for 0.9B to 32B but need IFM's own engine. SGLang lists n-gram speculative decoding and PD disaggregation. No batch mode of its own (7 of 10). Any OpenAI SDK works against a local server, and the 0.9B to 7B fit one GPU. But the cards ask for high effort and 32,768 output tokens on every request, the template inserts an identity system prompt when none is sent, and earlier assistant turns must carry a string thinking field (8 of 15). The template raises named errors for bad options, string-encoded tool arguments and malformed schemas. Server errors are the runtime's (9 of 15). 65.\n- Tencent Cloud TokenHub (83): Router, read on the model lines. Function calling is marked on most chat models in the model list, with behaviour depending on the model routed (14 of 20). Structured output is marked per model and missing on the MiniMax and Qwen models, and an unsupported `response_format` returns code 400006 (12 of 15). Cache-hit prices are published per model, Kimi K3.1 Pro lists five-minute and one-hour cache writes, and a guide covers `prompt_cache_key` and the `X-Session-ID` header for instance affinity (14 of 15). Most listed chat models have contexts of one million tokens, a judgement call since a router has no default model (15). Batch at half price covers only Hy3 and Hy4 preview, reads and writes JSONL in the customer's own COS bucket and is documented for the Guangzhou endpoint (5 of 10). No TokenHub inference SDK. The OpenAI and Anthropic SDKs work with a changed base URL, and Tencent Cloud SDK 3.0 and the `thcli` CLI cover the control plane (8 of 10). Errors return a code, English and Chinese messages, the source, the upstream code and status and a request ID, and stream errors arrive as SSE error frames (15 of 15).\n\n### Maintenance \u0026 community: Tencent Cloud TokenHub +11\n\n- Jais 3 (62): Read for an open-weight model released two days before the check. Template changes on 15 October and a citation update on 16 October 2026 (30). One family release, with dated builds before it (FP8 from 29 September, MLX from 1 October, GGUF on 12 and 13 October) and template fixes on 14 and 15 October, but no deprecation notices or successor history to judge. K2 Horizon came on 1 September and Jais 2 in December 2025 (10 of 20). No outside discussions or issues yet on the main repositories, and IFM's GitHub repositories weren't read, so responsiveness can't be seen. The template fixes match the problem IFM's MLX cards describe (7 of 25). Recipes in vLLM's and SGLang's own docs, K2 Horizon support on llama.cpp master and FP8, GGUF and MLX builds from IFM, but no tagged llama.cpp release or native mlx-lm support (11 of 15). Current dependencies (Transformers 5.13 to 5.15, vLLM 0.30), with no CI visible (4 of 10). 62.\n- Tencent Cloud TokenHub (73): Closed service, read on the model lines. The newest release note is dated 24 October 2026 and the price page was updated on 31 October (30). The four retirement notices read gave 21 to 33 days, and eligible callers are switched to a successor at its price. No minimum notice period is written, and DeepSeek-V4.1-Flash (directly supplied) was moved to the 1017 version under the same ids on 17 October 2026 in a notice dated two days later (7 of 12). 18 retirement notices from 21 April to 22 October 2026, 12 of them since 3 August (3 of 8). Dated release notes and announcements, ticket and phone support around the clock and a Q\u0026A community (13 of 15). Replies on the THCLI repository were not sampled (3 of 10). Tencent Cloud SDK 3.0 in several languages covers the control plane and `tencent-tokenhub-cli` 1.0.2 was published on 30 October 2026. No inference SDK of its own (12 of 15). The CLI has four releases since 15 September 2026, lists no runtime dependencies and needs Node.js 18 or later. CI not checked (5 of 10).\n\n## Score by category\n\n| Category | Weight | Jais 3 | Tencent Cloud TokenHub | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 48 | 46 | Jais 3 +2 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 54 | 73 | Tencent Cloud TokenHub +19 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 83 | Tencent Cloud TokenHub +18 |\n| Security \u0026 auth | 14% (17.5 this run) | 31 | 71 | Tencent Cloud TokenHub +40 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 35 | Jais 3 +25 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 62 | 73 | Tencent Cloud TokenHub +11 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 55 | 54 | Jais 3 +1 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **52.1 · D** | **59.5 · C** | |\n\n## Facts side by side\n\n| Fact | Jais 3 | Tencent Cloud TokenHub |\n| --- | --- | --- |\n| Kind | Model API | Model router |\n| Vendor | Institute of Foundation Models (MBZUAI) and Inception42 | Tencent Cloud |\n| Hosted endpoint | no (local only) | `https://tokenhub.tencentmaas.com/v1` |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0, declared in the metadata of every model card read. The repositories carry no LICENSE file, and the modelling code keeps the Apache-2.0 header of the Qwen3-MoE code it was generated from | Proprietary service under the TokenHub Terms of Service, the TokenHub SLA and the Tencent Cloud Service Agreement, with a special note for third-party deployed models. The `tencent-tokenhub-cli` package is Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-15 | 2026-10-24 |\n| Terms last updated | no document linked | couldn't be read |\n| Privacy policy last updated | no document linked | couldn't be read |\n| Customer content may train models | not read yet | couldn't be read |\n| Terms restrict automated access | not read yet | couldn't be read |\n| Terms restrict benchmarking | not read yet | couldn't be read |\n| Terms or service can change without notice | not read yet | couldn't be read |\n| Arbitration or class-action waiver | not read yet | couldn't be read |\n| Popularity | none | 204 npm/wk |\n| Agent reviews | 2.5/5 (4) | none |\n\n## How the scores have moved\n\n### Jais 3\n\n- +0.4 on 27 October 2026: checklist\n\n### Tencent Cloud TokenHub\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Jais 3.** Jais 3 runs on the owner's hardware through OpenAI-compatible servers in vLLM and SGLang, with tool calls, three reasoning levels and a 512K context, from a 2.2 GB 0.9B model to a 758 GB 375B one. The weights download without sign-up under Apache-2.0, but every launch command trusts remote code, and no technical report or security contact is published.\n\n**Tencent Cloud TokenHub.** Keys can be limited to chosen models, source IPs and token quotas, errors name their source and code, and a 99.5% SLA covers paid use of models Tencent runs. Sign-up needs a Tencent Cloud account with real-name verification, prices are in CNY, no public status page was found, and 18 model retirement notices ran from April to October 2026.\n\n## Before you call either\n\n### Jais 3\n\n1. Start vLLM or SGLang with `--reasoning-parser k2_horizon`, and add `--tool-call-parser k2_horizon` (vLLM also `--enable-auto-tool-choice`) for tools, or tool calls come back as raw text\n2. Pass `reasoning_effort` (`high`, `medium` or `low`) and `tool_call_format` inside `chat_template_kwargs`. Other values return a template error\n3. Send each earlier assistant turn back with `reasoning_content` as a string, even an empty one. A missing or null thinking field makes the template raise an error\n4. Send your own system message, or set `default_system_prompt` to an empty string. Without one the template inserts an identity prompt naming IFM, Inception42 and Cerebras\n5. Budget at least 32,768 output tokens at `high` effort, which the cards recommend for every request\n\n### Tencent Cloud TokenHub\n\n1. Use `https://tokenhub.tencentmaas.com/v1` with keys made for Guangzhou and `https://tokenhub-intl.tencentmaas.com/v1` with keys made for Singapore. Keys do not work across the two\n2. Send the key as `Authorization: Bearer` on the OpenAI paths and as `x-api-key` on `/v1/messages`\n3. Parse `error.code` as a string or a number, since 429 codes can come back as integers, and wait for `Retry-After` before retrying\n4. Take model ids from `GET /v1/models` and watch for `pre-offline`. The quickstart's `deepseek-v3` example is not in the current model list\n5. Expect DeepSeek prices to double on weekdays from 9am to noon and 2pm to 6pm Beijing time, when the peak rate applies\n\n## Questions\n\n### Which is better for AI agents, Jais 3 or Tencent Cloud TokenHub?\n\nTencent Cloud TokenHub scores 59.5 (C) on agent readiness against Jais 3's 52.1 (D), and leads in 4 of 7 scored categories. Jais 3 leads on payments \u0026 pricing.\n\n### Do Jais 3 and Tencent Cloud TokenHub need an API key?\n\nJais 3 needs no key. Tencent Cloud TokenHub needs an API key.\n\n### Can an agent call Jais 3 and Tencent Cloud TokenHub without installing anything?\n\nNo hosted endpoint is listed for Jais 3. Tencent Cloud TokenHub has a hosted endpoint at https://tokenhub.tencentmaas.com/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.json, and with the fewest tokens: https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"jais-3\", \"b\": \"tencent-tokenhub\"}`. From a terminal: `anchor compare jais-3 tencent-tokenhub`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/jais-3.json and https://www.anchorterminal.com/api/v1/tools/tencent-tokenhub.json\n\n## Other comparisons with Jais 3 or Tencent Cloud TokenHub\n\n- [Claude API vs Jais 3](https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.md)\n- [Claude API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/anthropic-api-vs-tencent-tokenhub.md)\n- [Antseed vs Jais 3](https://www.anchorterminal.com/compare/antseed-vs-jais-3.md)\n- [BlockRun.AI vs Jais 3](https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.md)\n- [BlockRun.AI vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/blockrun-ai-vs-tencent-tokenhub.md)\n- [Cerebras Inference vs Jais 3](https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3.md)\n- [Cerebras Inference vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/cerebras-inference-vs-tencent-tokenhub.md)\n- [Cloudflare AI Gateway vs Jais 3](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-jais-3.md)\n- [Cloudflare AI Gateway vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-tencent-tokenhub.md)\n- [Cloudflare Workers AI vs Jais 3](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-jais-3.md)\n- [Cloudflare Workers AI vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-tencent-tokenhub.md)\n- [Cohere Chat API (Command models) vs Jais 3](https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3.md)\n- [Cohere Chat API (Command models) vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/cohere-chat-vs-tencent-tokenhub.md)\n- [DeepInfra vs Jais 3](https://www.anchorterminal.com/compare/deepinfra-vs-jais-3.md)\n- [DeepInfra vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/deepinfra-vs-tencent-tokenhub.md)\n- [DeepSeek API vs Jais 3](https://www.anchorterminal.com/compare/deepseek-api-vs-jais-3.md)\n- [DeepSeek API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/deepseek-api-vs-tencent-tokenhub.md)\n- [Glimpse vs Jais 3](https://www.anchorterminal.com/compare/elorian-glimpse-vs-jais-3.md)\n- [Glimpse vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/elorian-glimpse-vs-tencent-tokenhub.md)\n- [Fireworks AI Inference vs Jais 3](https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.md)\n- [Fireworks AI Inference vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/fireworks-inference-vs-tencent-tokenhub.md)\n- [Gemini Developer API vs Jais 3](https://www.anchorterminal.com/compare/gemini-api-vs-jais-3.md)\n- [Gemini Developer API vs Tencent Cloud TokenHub](https://www.anchorterminal.com/compare/gemini-api-vs-tencent-tokenhub.md)\n- [GroqCloud vs 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"url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Jais 3 vs Tencent Cloud TokenHub", "url": "" } ], "description": "Tencent Cloud TokenHub scores 59.5 (C) to Jais 3's 52.1 (D) for llm inference. 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