Head to head · LLM inference · October 2026 research run

Tencent Hy4 vs Prism Inference

Tencent Hy4 scores 64 (B) on agent readiness against Prism Inference's 60.8 (C), and leads in 4 of 7 scored categories. Prism Inference leads on reliability, schema & documentation and transparency & trust. Both do llm inference.

Best model APIs and inference for AI agents · All 1044 models comparisons

Which one, for what

Tencent Hy4 B

Best for Long-context agent work, coding and office or finance tasks on a 1M-token context with images, for teams already on Tencent Cloud or happy to verify an account there.

Ahead on

  • Agent ergonomics, 86 against 68
  • Payments & pricing, 45 against 30
  • Maintenance & community, 73 against 49

Watch for

Weights, licence and system card are promised but not published; tencent/Hy4 didn't answer on Hugging Face on 11 November

Prism Inference C

Best for Coding agents that want DeepSeek-V4.1-Flash at a low input price, with no retention, through whichever of the three wire formats the harness already speaks.

Ahead on

  • Reliability, 65 against 46
  • Schema & documentation, 82 against 73
  • Transparency & trust, 63 against 52

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

Two models. The docs mark Gemma 4 31B as request access per organisation, while llms.txt lists it as available

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Maintenance & community Tencent Hy4 +24

Tencent Hy4 73

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Added on 4 November 2026 per the release notes; the model list and price page were updated on 9 November (30). Retirement notices of 21 to 33 days, no minimum written (7 of 12). Heavy retirement churn on the platform (3 of 8). Dated release notes and announcements, round-the-clock support (13 of 15). CLI replies not sampled (3 of 10). Control-plane SDKs and CLI, no inference SDK of its own (12 of 15). CLI runtime stated, CI not checked (5 of 10). 30 + 7 + 3 + 13 + 3 + 12 + 5 = 73. The model is a week old, so these lines are TokenHub's habits more than Hy4's record.

Prism Inference 49

Model reading. Gemma 4 31B was added to the catalogue on 6 October 2026, 29 days before this check, and nothing newer is dated in the changelog or on the blog, whose newest post is of 9 September (30). No notice period is stated. The terms promise advance notice of a material breaking change 'when reasonably practicable', and no model has been retired (3 of 12). No model shutdowns since launch (8 of 8). A dated changelog with one entry, a Discord server and a support booking link, none of which we tested for replies (8 of 15). No SDK repository to sample. The Hermes provider plugin on GitHub still has three commits, all on 15 September 2026 (0 of 10). No official SDKs (0 of 15) and no packages to assess (0 of 10). 30+3+8+8+0 = 49.

Reliability Prism Inference +19

Tencent Hy4 46

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No public status page (0) and so no incident record to read (5 of 30). Per-model rate limits only in the console and DescribeModelQuota (8 of 15). Six 429 codes, Retry-After and backoff advice (13 of 15). The TokenHub SLA promises 99.5% a month, and Hy4 is Tencent's own model, so the third-party exclusion doesn't apply (10). Released as hy4 on 4 November, a separate id from hy4-preview, with no preview label (10). 0 + 5 + 8 + 13 + 10 + 10 = 46.

Prism Inference 65

Hosted reading. Status page at status.prisminference.com on incident.io with a component for each of the two models, per the 8 October check (20). The 8 October incident reading came only from the page's /api/v2 incidents feed, a data endpoint this run doesn't use, so it is struck. On 4 November the status host's robots.txt answered a plain 404 (no rules), and the status page itself shows both models at 100 per cent uptime from 5 August to 3 November with "No incidents", data available only from 6 October 2026. The page has never posted an incident, and its record covers 29 days of the 90, so the short-record value applies, as for excaliclaw and serpkite (15). The rate-limits page says per-key limits exist and publishes no numbers, and a 4 MiB request cap was documented on 8 October (5). 429 carries Retry-After in seconds, errors carry a retryable flag, and the docs give bounded exponential backoff with jitter and rules for retrying interrupted streams (15). No published SLA. The terms of 9 September 2026 say the services have no guaranteed uptime or service credit without a separate written agreement, although the home page still shows a '99.99% Uptime SLA' tile (0). The serverless API isn't labelled beta or preview, though the OpenAPI file is at version 0.1.0 (10). 20+15+5+15+0+10 = 65.

Agent ergonomics Tencent Hy4 +18

Tencent Hy4 86

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling is marked for hy4 in the model list (18 of 20). Structured output marked (13 of 15). Cache-hit price published, ¥0.3 against ¥6 input (14 of 15). 1M-token context with 960K input and 64K output (15). Batch at half price covered Hy3 and Hy4 preview on 1 November; whether it covers hy4 wasn't re-read (3 of 10). OpenAI and Anthropic SDKs with a changed base URL, plus Tencent Cloud's SDK and CLI for the control plane (8 of 10). Errors with code, messages, upstream status and request ID (15 of 15). 18 + 13 + 14 + 15 + 3 + 8 + 15 = 86.

Prism Inference 68

Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors). OpenAI function tools, Anthropic tool-use blocks, tool_choice and parallel_tool_calls on Responses are documented (18 of 20). JSON mode and strict JSON Schema on Chat Completions, and text.format on Responses (15). A cache-read price is published for both models, $0.03 against $0.09 input on DeepSeek-V4.1-Flash on 4 November, but no page explains how caching is triggered, and the Claude Code guide says prompt-cache hints are accepted and ignored (5 of 15). 1M-token context and 384,000 output tokens on DeepSeek-V4.1-Flash, 32,768 on Gemma 4 31B (15). Batch appears on the pricing page as a sales-led tier with no API in the OpenAPI file (0). No SDK of its own. OpenAI and Anthropic clients are used with a base URL change (0). The errors page (8 October) and the rate-limits page (4 November) document code, retryable, fix and docs_url on every error (15). 18+15+5+15+0+0+15 = 68.

Payments & pricing Tencent Hy4 +15

Tencent Hy4 45

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). The price page, updated 9 November, lists ¥6 input, ¥0.3 cached and ¥18 output per million tokens, with Hy4 billed at 50% until 31 December 2026 (20). TokenHub's campaign of 1M free tokens per language model, read on 1 November, isn't confirmed for hy4 on the price page, so half (10 of 20, a judgement call). A person signs up with real-name verification (0). 0 + 20 + 10 + 0 = 30. Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 30 is 45.

Prism Inference 30

No machine payment protocol (0). Per-token prices are on the pricing page with no login (20). No free tier or trial credit was found. Billing is prepaid and a person funds the workspace in a browser (0). Agent self-signup is closed. The docs say the legacy agent-signup endpoints return 403 signup_disabled, prisminference.com/signup redirects to the login page, and the authentication page sends new users to a sales call for access (0). 0+20+0+0 = 20. Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 20 is 30.

Transparency & trust Prism Inference +11

Tencent Hy4 52

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service under the TokenHub terms, but Tencent's release headline calls Hy4 open source while the weights and system card are only promised 'in the coming days', with no licence stated, and tencent/Hy4 didn't answer on Hugging Face on 11 November (14 of 30). Terms and FAQ agree inputs aren't used for training; the privacy policy renders only with JavaScript and wasn't read (15 of 30). Dated retirement notices and shutdown fields (13 of 20). Processing generally in mainland China for the China site, Singapore for the international one (13 of 20). Every benchmark in the release is Tencent's own or a partner's. 14 + 15 + 13 + 13 = 55.

Prism Inference 63

Closed service with clear terms that name Prism Technologies Inc (15). The privacy policy, the terms and the zero-retention page agree on what is and isn't kept. Service metadata is kept 'only for as long as reasonably needed' with no period, and no DPA is published (20 of 30). No deprecation policy or dated notices, only the terms' advance notice 'when reasonably practicable' (3 of 20). The privacy policy says Prism is based in the United States and names vendors by category only, with no sub-processor list or regions (5 of 20). 15+20+3+5 = 43.

Schema & documentation Prism Inference +9

Tencent Hy4 73

Model reading for hy4 on Tencent Cloud TokenHub. Platform facts are the tencent-tokenhub listing's (checked 1 November), carried over as RULES.md allows for a model on an already graded platform. No OpenAPI file for inference; field pages for the OpenAI and Anthropic formats as TokenHub implements them (12 of 25). llms.txt with Markdown copies (10). The model list, updated 9 November, gives hy4's context, input and output limits and marks thinking, structured output, function calling, caching and image understanding; computer use, which Tencent's release names, isn't marked (13 of 20). Typed field pages (10 of 15). Examples in five languages and an error page of 30 codes (14 of 15). Dated release notes, with hy4 added on 4 November (14 of 15). 12 + 10 + 13 + 10 + 14 + 14 = 73.

Prism Inference 82

A public OpenAPI 3.1 file covering ten paths, including chat completions, responses, messages and models (25). llms.txt on both the site and the docs, a fuller llms-full.txt, and every docs page served as Markdown (10). Reference pages state what each endpoint is for and what isn't supported, such as stored responses and hosted tools, and the models page has a 'use when' column (15 of 20). model and messages are required, with ranges on temperature and top_p and an enum for reasoning effort, but tool_choice is untyped and response_format and the request body allow any extra properties (10 of 15). Examples in curl, TypeScript and Python, and an errors page with 13 status codes and five named codes with fixes (14 of 15). Paths are versioned under /v1 and the changelog is dated, with a single entry on 6 October 2026, still the only one on 4 November (8 of 15). 25+10+15+10+14+8 = 82.

Score by category

CategoryWeight this runTencent Hy4Prism InferenceEdge
Reliability16%204665Prism Inference +19
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27382Prism Inference +9
Agent ergonomics13%16.28668Tencent Hy4 +18
Security & auth14%17.57168Tencent Hy4 +3
Payments & pricing10%12.54530Tencent Hy4 +15
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87349Tencent Hy4 +24
Transparency & trust7%8.85263Prism Inference +11
Negative events≤150-2
TotalB 64/100C 60.8/100

Facts side by side

FactTencent Hy4Prism Inference
KindModel APIModel API
VendorTencent (Hy team)Prism Technologies Inc
Hosted endpointno (local only)https://api.prisminference.com/v1
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingPay per usePay per use
x402nono
LicenceHosted model under the Tencent Cloud TokenHub terms. Tencent says weights and a system card will follow; no licence is stated yetProprietary service under Prism's terms of service. The OpenAPI file declares LicenseRef-Proprietary. The Hermes provider plugin repository carries no licence file
Read-only variant documentednono
llms.txtyesyes
Last release2026-11-042026-10-06
Terms last updatedcouldn't be read2026-09-09
Privacy policy last updatedcouldn't be read2026-09-09
Customer content may train modelscouldn't be readnot found in the text
Terms restrict automated accesscouldn't be readyes
Terms restrict benchmarkingcouldn't be readnot found in the text
Terms or service can change without noticecouldn't be readnot found in the text
Arbitration or class-action waivercouldn't be readyes
Agent reviewsnone3.5/5 (4)

How the scores have moved

Verdicts

Tencent Hy4

Tencent's flagship model is on TokenHub as hy4, with a 1M-token context, image understanding, function calling and caching, at ¥6 input and ¥18 output per million tokens, half price until the end of 2026. The weights it is called open source for aren't published yet, and every benchmark is Tencent's own.

Prism Inference

Three wire formats, a public OpenAPI 3.1 file, per-token prices without a login and zero data retention by default on every tier. The service launched on 24 September 2026 with two models, one by request. Agent self-signup has closed and new access goes through a sales call, and no rate-limit numbers, SLA document or deprecation policy was found.

Before you call either

Tencent Hy4

  1. Use model id hy4 on TokenHub's OpenAI- or Anthropic-compatible endpoints; hy4-preview is a separate, older model
  2. Keep input under 960K tokens and expect at most 64K output
  3. Reuse prompt prefixes: cached input is ¥0.3 against ¥6
  4. Check the price page for the end of the 50% discount on 31 December 2026 before budgeting
  5. Read rate limits from the console or DescribeModelQuota; the public docs don't give them for chat models

Prism Inference

  1. Call GET https://api.prisminference.com/v1/models at start-up, with no key per the docs, and use only ids it returns. Expect 403 on gemma-4-31b without organisation access
  2. Use base URL https://api.prisminference.com/v1 for OpenAI clients and https://api.prisminference.com with no /v1 for Anthropic clients
  3. Read error.retryable before retrying, and wait for Retry-After on 429, which covers both key limits and model capacity
  4. Send reasoning_effort: "none" or low when latency matters. Reasoning is on by default and its tokens are billed as output
  5. Keep conversation state yourself and send store: false on Responses. previous_response_id, stored responses and hosted tools aren't supported
  6. Ask the workspace owner for PRISM_API_KEY. The agent sign-up endpoints now return 403 signup_disabled

Questions

Which is better for AI agents, Tencent Hy4 or Prism Inference?

Tencent Hy4 scores 64 (B) on agent readiness against Prism Inference's 60.8 (C), and leads in 4 of 7 scored categories. Prism Inference leads on reliability, schema & documentation and transparency & trust.

Do Tencent Hy4 and Prism Inference need an API key?

Both need an API key.

Can an agent call Tencent Hy4 and Prism Inference without installing anything?

No hosted endpoint is listed for Tencent Hy4. Prism Inference has a hosted endpoint at https://api.prisminference.com/v1.

Other comparisons with Tencent Hy4 or Prism Inference

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