Beam 1.0 vs Tencent Cloud TokenHub

Beam 1.0 46

Model reading. API keys per project, revocable, shown once and disabled when their creator leaves, with no scopes, expiry or rotation API found (20 of 30). Training is contradictory. The API safety page says content isn't used for training by default, with an opt-in, but the commercial terms of 5 October grant Reflection a licence to train on content sent to Discounted Services, which they define to include services at no charge, and the API is currently free. A reflection-data-retention header reports contributor when training applies (10 of 20). Content kept 30 days for safety review. Zero data retention isn't available yet, though the header reports the retention mode on each response (5 of 15). x-request-id on every response and the retention header, with usage dashboards behind the login and not read (5 of 15). No security.txt on reflection.ai, developers.reflection.ai or api.reflection.ai, no bug bounty of Reflection's own and no SOC 2 or ISO 27001 found. A vulnerability address on the model card, a published safety report with indirect prompt-injection results, and Reflection co-sponsors Gray Swan's public prompt-injection challenge (6 of 20). 46.

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).

Beam 1.0 50

Model reading for a model released the day before this check. Weights and the public API released on 16 October 2026 (30). One model, with a shutdown_date field and a lifecycle section in the docs but no notice period for retirements, and no history of releases or retirements yet (4 of 20). No changelog. Support goes through the platform and Discord, and the model card names reports@reflection.ai. Hugging Face discussions not sampled (6 of 25). No first-party SDK, the docs rely on the OpenAI SDKs (5 of 15). Day-one support in vLLM, SGLang, Transformers, TokenSpeed and Dynamo with Reflection's recipes, and a Beam Verifier repository, but fine-tuning recipes are 'coming soon' (5 of 10). 50.

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).

Beam 1.0 67

Model reading (tool use, structured output, caching, context, batch, SDKs and defaults, errors). tool_choice of auto, none, required or a named function, parallel_tool_calls, strict tools and up to 128 tools. The tool-calling loop needs reasoning_content sent back on every assistant turn, and the docs say the model sometimes returns a tool-call step without it, after which every request in the session fails (12 of 20). json_object and strict json_schema (15). Cached prompt tokens are reported in usage, but caching can't be steered, the prompt_cache_* options are ignored and no cached price exists in the beta (5 of 10). 1,048,576-token context and 131,072 output tokens (15). No batch endpoint (0 of 10). No Reflection SDK, the OpenAI Python and TypeScript SDKs are documented, and defaults cost an agent turns, with reasoning always on at max, stop and seed ignored and a default output budget not reduced to fit the prompt (5 of 10). Machine-readable error.code values with param, x-should-retry, Retry-After and x-request-id (15). 67.

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).

Beam 1.0 20

Graded on the Reflection API. No x402, MPP or L402 (0). The public beta is free with a daily allocation, but no allocation figures or per-token prices are published, and the beta pricing page still shows template placeholders, so plan-level only (10 of 20). Free to start, but the docs say some organisations must verify a credit card before keys work (10 of 20). A person signs up in the browser at platform.reflection.ai to get a key (0). The weights are free under Apache-2.0 for anyone serving them, and hosted copies through other providers are not graded. 20.

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).

Beam 1.0 67

Weights under Apache-2.0, an OSI licence, with no restriction on distillation or training on outputs. The hosted API is closed under clear commercial terms, and training code and data aren't released (25 of 30). Data handling statements disagree. Flagged content is kept up to 12 months in the terms, up to two years on the API safety page and 'one year' later on that page, training is off by default on one page while the terms license training on free use, and the docs reset daily limits at 00:00 UTC while the pricing page says a bracketed midnight Pacific time (10 of 30). A shutdown_date field and 30 days' notice before fee increases, but no model deprecation policy or dated notices (6 of 20). A subprocessor list of twelve with purposes and locations, including Together AI in Canada and Voltage Park for inference (18 of 20). 59.

Tencent Cloud TokenHub 54

Closed service under the TokenHub Terms of Service (effective 14 September 2026), the SLA (23 April 2026), a special note on third-party deployed models and the Tencent Cloud Service Agreement, naming Tencent Cloud Computing (Beijing) Co., Ltd. The CLI is Apache-2.0 (18 of 30). The terms and the FAQ agree that inputs are processed on the customer's instructions and not used for training, and clause 2.14 limits retention to what the service needs without periods. The TokenHub privacy policy on privacy.qq.com renders only with JavaScript and was not read (15 of 30). Dated retirement notices, shutdown dates in the model list, a pre-offline status in /v1/models and a DiscontinuedAt field in the control API. Clause 6.3 refunds paid, unused tokens when a third-party model is removed. No minimum notice period is written (13 of 20). Clause 2.13 places processing generally in mainland China for the China site and in Singapore for the international site, and the third-party model list names DeepSeek's Hangzhou company with a link to its terms. No subprocessor list was found (13 of 20).

Beam 1.0 84

Model reading. OpenAPI 3.0.3 document, version 0.1.0, covering all three documented endpoints with typed schemas and error examples. A second 'Reflection client' base URL, https://api.reflection.ai/v1, is named with no endpoints documented (22 of 25). llms.txt, a Markdown copy of every page and a docs MCP endpoint (10). The guides say which reasoning effort suits which task, which OpenAI parameters are fixed, ignored or unsupported and which endpoints don't exist, so a model knows what not to send (17 of 20). reasoning_effort is an enum, strict JSON Schema for tools and json_schema output with the unsupported keywords and size limits listed, and unknown parameters return unsupported_parameter (15). curl, Python and TypeScript examples on every guide, and an error reference with every status, error.code and retry advice (15). The model ID carries its version and the models endpoint has a shutdown_date field, but no changelog or release notes were found (5 of 15). 84.

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).