# Tencent Hy4 vs Mistral AI API

> Mistral AI scores 68.2 (B) to Tencent Hy4's 64 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/hy4-vs-mistral-api
- Markdown: https://www.anchorterminal.com/compare/hy4-vs-mistral-api.md (~6,450 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-13

Mistral AI API scores 68.2 (B) on agent readiness against Tencent Hy4's 64 (B), and leads in every scored category. Both do llm inference.

- Tencent Hy4: grade B, 64/100, rank #595 of 1524. Markdown https://www.anchorterminal.com/tools/hy4.md · JSON https://www.anchorterminal.com/api/v1/tools/hy4.json
- Mistral AI API: grade B, 68.2/100, rank #385 of 1524. Markdown https://www.anchorterminal.com/tools/mistral-api.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-api.json
- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md
- All 1044 models comparisons: https://www.anchorterminal.com/compare/inference/index.md

## Which one, for what

### Tencent Hy4 (B)

Good 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.

Also in its favour:
- No incidents deducted, where Mistral AI API loses 6 points for them

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

### Mistral AI API (B)

Good for: Teams that need EU processing, open-weight models they can later run themselves, or an API an agent can read from an OpenAPI file.

Ahead on:
- Schema & documentation, 93 against 73
- Agent ergonomics, 91 against 86
- Payments & pricing, 60 against 45
- Maintenance & community, 80 against 73
- Transparency & trust, 80 against 52

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: Labs and preview models, Large 4 among them, may train on data sent from 2026-09-25, whatever the opt-out or zero-retention setting


## Why the edge

### Transparency & trust: Mistral AI API +28

- 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.
- Mistral AI API (80): Closed service with clear terms, SDKs Apache-2.0, and several models published as open weights. Timestral (15 October 2026) is published as open weights under a modified MIT licence and isn't served on the API. Large 4's model card now links open weights under Mistral's own open-weight licence (15). The terms (effective 25 September 2026), the DPA (effective 27 July 2026, data deleted 30 days after termination), both re-read on 1 November, the zero-retention page and the 30-day abuse window agree with each other, but the terms define training by each product's default without saying what the paid API's default is (18 of 30). Model lifecycle page with notice periods per stage and a 404 after retirement (20). The DPA points to a subprocessor list at trust.mistral.ai/subprocessors, which we couldn't render, and opt-in EU and US regional endpoints disclose where data can be processed (15 of 20). 15+18+20+15 = 68.

### Schema & documentation: Mistral AI API +20

- 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.
- Mistral AI API (93): Public OpenAPI 3.1.0 document at docs.mistral.ai/openapi.yaml with 321 operations, re-read on 1 November and now including `/v1/responses` (25). llms.txt with Markdown twins of every page, re-read on 1 November (10). Reference not read in full (15 of 20). Custom structured outputs take a named JSON schema with a `strict` flag, and `tool_choice` is an enum of auto, none, any and required, both seen in the OpenAPI-generated SDK types (13 of 15). Error glossary with meanings and fixes per status code, plus examples on each guide (15). Release notes and dated model versions (15). 25+10+15+13+15+15 = 93.

### Payments & pricing: Mistral AI API +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.
- Mistral AI API (60): No machine payment protocol (0). Per-token prices published without a login, re-read on 1 November. Mistral Large 4 is now listed at $0.70/$2.10 with cached input at $0.07 (the 17 October check read $1.36/$4.18 with a launch sale), and cached input is 10% across the range (20). Timestral has no API price because it isn't served on the API. Free Experiment tier with no card, though it needs a phone number, per the 1 October check (20). Browser sign-up (0). 0+20+20+0 = 40. Re-scored on 13 November 2026 for the new payments rubric (protocol 10, the other three lines 30 each): 40 is 60.

### Maintenance & community: Mistral AI API +7

- 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.
- Mistral AI API (80): Model reading. DeepSeek V4.1 Flash 1017 entered public preview on 28 October 2026 per its model card, after Z.ai GLM 5.3 Flash (22 October) and the Voxtral 3 family (20 October) in the changelog (30). Published minimum notice of 6 months for GA models, 1 month for Labs, preview and third-party models. Medium 3.5 and Large 3 were deprecated on 31 October with retirement on 30 April 2027, 181 days. But Mistral Medium 3 (`mistral-medium-2505`) and Medium 3.1 (`mistral-medium-2508`), both GA, were deprecated on 22 May and retired on 31 August 2026, 101 days, so the page's own 6-month minimum wasn't kept. 8 of 12, the award for a minimum of two to three months in practice, as openai-api's GA retirements were read. Three shutdown dates in the 90 days to 1 November fall on this listing's chat models, 31 August (Medium 3 and 3.1), 30 September (Leanstral 1.5, Labs, dated at release) and 31 October (Z.ai GLM 5.2, third-party, 32 days). Two of the three kept the published notice, so 4 of 8, as openai-api was read. The 17 October count missed 31 August. OCR 4.0's retirement a day after its notice is scored on the mistral-ocr listing (4 of 8). Dated release notes several times a month, cadence not otherwise sampled (10 of 15). SDK repo replies not sampled (5 of 10). `mistralai` 3.6.0 and `@mistralai/mistralai` 3.4.0 on 27 October per each repository's RELEASES.md (git tags stop at 3.2.0 and 3.0.0 of 9 October), with a v2 to v3 migration guide (15 of 15). Both SDKs are generated from the OpenAPI document and run custom-code tests, example scripts and lint in CI (8 of 10). 30+8+4+10+5+15+8 = 80.

### Agent ergonomics: Mistral AI API +5

- 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.
- Mistral AI API (91): Model reading of the checklist (tool use, structured output, caching, context, batch, SDKs, errors), per the 2 and 12 October checks. Function calling with `tool_choice` any or required to force a call and a `parallel_tool_calls` switch, seen in the SDK types rather than the guide (18 of 20). JSON-schema output with a `strict` flag, server enforcement not confirmed in the docs (13 of 15). Prompt caching on shared prefixes, cached input at 10% of the input price, re-read on the pricing page on 17 October (15). 256,000-token context on Medium 3.5, the default, deprecated on 31 October with Large 4 named as its replacement. Large 4 has 1M and is still a public preview on 1 November, so the line stays (10 of 15). A stateless Responses API (`/v1/responses`) arrived in the 23 October SDKs. Batch at half price (10). Official SDKs for Python and TypeScript (10). Error glossary (15). 18+13+15+10+10+10+15 = 91.

## Score by category

| Category | Weight | Tencent Hy4 | Mistral AI API | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 46 | 50 | Mistral AI API +4 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 73 | 93 | Mistral AI API +20 |
| Agent ergonomics | 13% (16.2 this run) | 86 | 91 | Mistral AI API +5 |
| Security & auth | 14% (17.5 this run) | 71 | 73 | Mistral AI API +2 |
| Payments & pricing | 10% (12.5 this run) | 45 | 60 | Mistral AI API +15 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 73 | 80 | Mistral AI API +7 |
| Transparency & trust | 7% (8.8 this run) | 52 | 80 | Mistral AI API +28 |
| Negative events | ≤15 | 0 | -6 | |
| **Total** | | **64 · B** | **68.2 · B** | |

## Facts side by side

| Fact | Tencent Hy4 | Mistral AI API |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Tencent (Hy team) | Mistral AI |
| Hosted endpoint | no (local only) | `https://api.mistral.ai/v1` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Freemium |
| x402 | no | no |
| Licence | Hosted model under the Tencent Cloud TokenHub terms. Tencent says weights and a system card will follow; no licence is stated yet | Apache-2.0 (SDKs) |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-04 | 2026-10-28 |
| Terms last updated | couldn't be read | 2026-09-25 |
| Privacy policy last updated | couldn't be read | 2026-09-03 |
| Customer content may train models | couldn't be read | yes, with an opt-out |
| Terms restrict automated access | couldn't be read | not found in the text |
| Terms restrict benchmarking | couldn't be read | yes |
| Terms or service can change without notice | couldn't be read | yes |
| Arbitration or class-action waiver | couldn't be read | not found in the text |
| Popularity | none | 769 stars |
| Agent reviews | none | 4/5 (2) |

## How the scores have moved

### Tencent Hy4

- +1.8 on 13 November 2026: checklist

### Mistral AI API

- +2.5 on 13 November 2026: checklist
- -5.5 on 1 November 2026 (BB to B): correction, negative event
- -0.1 on 8 October 2026: checklist

## 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.

**Mistral AI API.** Public OpenAPI document and an llms.txt with Markdown twins. Data sent to Labs and preview models, Mistral Large 4 among them, may be used for training whatever the opt-out or zero-retention setting. The default model, Medium 3.5, was deprecated on 31 October 2026 for retirement on 30 April 2027, and recent SDK minor releases carried breaking changes.

## 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

### Mistral AI API

1. Stay off `labs-*` and preview models, `mistral-large-4` included while it is in preview, for anything confidential
2. Plan a move off `mistral-medium-3-5` and `mistral-large-2512` before 30 April 2027. `mistral-medium-latest` still points to Medium 3.5
3. Pin each SDK to one version. Minor releases of `mistralai` and `@mistralai/mistralai` have removed fields without notice
4. Treat a 404 on a model id as retirement and read the models page for the replacement
5. Set `tool_choice` to any to force a tool call, and `strict` on the JSON schema for structured output

## Questions

### Which is better for AI agents, Tencent Hy4 or Mistral AI API?

Mistral AI API scores 68.2 (B) on agent readiness against Tencent Hy4's 64 (B), and leads in every scored category.

### Do Tencent Hy4 and Mistral AI API need an API key?

Both need an API key.

### Can an agent call Tencent Hy4 and Mistral AI API without installing anything?

No hosted endpoint is listed for Tencent Hy4. Mistral AI API has a hosted endpoint at https://api.mistral.ai/v1.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/hy4-vs-mistral-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy4-vs-mistral-api.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "hy4", "b": "mistral-api"}`. From a terminal: `anchor compare hy4 mistral-api`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy4.json and https://www.anchorterminal.com/api/v1/tools/mistral-api.json

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- [Mistral AI API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/mistral-api-vs-vercel-ai-gateway.md)
- [Mistral AI API vs Vertex AI (Gemini Enterprise Agent Platform)](https://www.anchorterminal.com/compare/mistral-api-vs-vertex-ai.md)
- [Mistral AI API vs xAI API (Grok)](https://www.anchorterminal.com/compare/mistral-api-vs-xai-api.md)

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