# Jais 3 vs Tencent Cloud TokenHub (slim)

> Tencent Cloud TokenHub scores 59.5 (C) to Jais 3's 52.1 (D) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.md (~6,400 tokens) · this version ~3,380 tokens · JSON https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub.json · canonical https://www.anchorterminal.com/compare/jais-3-vs-tencent-tokenhub
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-01
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

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 & pricing. Both do llm inference.

- Jais 3: D 52.1, rank #906 of 1260 · https://www.anchorterminal.com/tools/jais-3.min.md
- Tencent Cloud TokenHub: C 59.5, rank #646 of 1260 · https://www.anchorterminal.com/tools/tencent-tokenhub.min.md
- Jais 3, good 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. Ahead on Payments & 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.
- Tencent Cloud TokenHub, good 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. Ahead on Schema & documentation, 73 against 54; Agent ergonomics, 83 against 65; Security & auth, 71 against 31; Maintenance & community, 73 against 62. Also A hosted endpoint, with nothing to install.

| Category | Jais 3 | Tencent Cloud TokenHub |
| --- | --- | --- |
| Reliability (16%) | 48 | 46 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 54 | 73 |
| Agent ergonomics (13%) | 65 | 83 |
| Security & auth (14%) | 31 | 71 |
| Payments & pricing (10%) | 60 | 35 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 62 | 73 |
| Transparency & trust (7%) | 55 | 54 |

| Fact (where they differ) | Jais 3 | Tencent Cloud TokenHub |
| --- | --- | --- |
| Kind | Model API | Model router |
| Vendor | Institute of Foundation Models (MBZUAI) and Inception42 | Tencent Cloud |
| Hosted endpoint | no (local only) | `https://tokenhub.tencentmaas.com/v1` |
| Auth | None | API key |
| Pricing | Free | Pay per use |
| 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 |
| llms.txt | no | yes |
| Last release | 2026-10-15 | 2026-10-24 |
| Terms last updated | no document linked | couldn't be read |
| Privacy policy last updated | no document linked | couldn't be read |
| Customer content may train models | not read yet | couldn't be read |
| Terms restrict automated access | not read yet | couldn't be read |
| Terms restrict benchmarking | not read yet | couldn't be read |
| Terms or service can change without notice | not read yet | couldn't be read |
| Arbitration or class-action waiver | not read yet | couldn't be read |
| Popularity | none | 204 npm/wk |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Security & auth, Tencent Cloud TokenHub +40: 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.); 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).)
- Payments & pricing, Jais 3 +25: 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.); 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).)
- Schema & documentation, Tencent Cloud TokenHub +19: 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.); 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).)
- Agent ergonomics, Tencent Cloud TokenHub +18: 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.); 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).)
- Maintenance & community, Tencent Cloud TokenHub +11: 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.); 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&A 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).)