# Gemini 4 Hydrogen vs Mistral AI API

> Mistral AI scores 68.2 (B) to Gemini 4 Hydrogen's 64.9 (B) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-mistral-api
- Markdown: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-mistral-api.md (~7,550 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 Gemini 4 Hydrogen's 64.9 (B), and leads in 6 of 7 scored categories. Gemini 4 Hydrogen leads on maintenance & community. Both do llm inference.

- Gemini 4 Hydrogen: grade B, 64.9/100, rank #546 of 1524. Markdown https://www.anchorterminal.com/tools/gemini-4-hydrogen.md · JSON https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.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

### Gemini 4 Hydrogen (B)

Good for: Agents doing everyday coding, tool calls and document work at volume on the Gemini API, including ones that need to start on a free key, or as the executor beside Carbon or Argon.

Ahead on:
- Maintenance & community, 85 against 80

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

Watch for: temperature, top_p and top_k are ignored, and thinking_budget, MINIMAL, penalties and extra candidates return a 400

### 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:
- Reliability, 50 against 45
- Schema & documentation, 93 against 85
- Security & auth, 73 against 50
- Payments & pricing, 60 against 40
- Transparency & trust, 80 against 72

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

### Security & auth: Mistral AI API +23

- Gemini 4 Hydrogen (50): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Keys bound to a service account and restricted to the Gemini API, with no scopes and a token accepted in the URL (15 of 30, the platform's deduction). Hydrogen is on the free tier, where Google's terms say content is used to improve products and may be read by humans; paid-tier content isn't (10 of 20, the platform's reading; Carbon, paid tier only, got 15). Abuse retention has no number and new paid projects store requests by default since 26 October; Google's prompt-injection figure (2.3 times more resilient on Gray Swan's benchmark) is its own, and the model card says jailbreak resistance is still being improved (5 of 15). Request logs for billed projects (15). security.txt and a reward programme, no certification naming the API (5 of 20). 15 + 10 + 5 + 15 + 5 = 50.
- Mistral AI API (73): Model reading. Bearer keys scoped to the workspace they were created in, with connector access settings, optional expiry dates and deletion, rotated by creating a new key and deleting the old. Service accounts bind to workspace roles, custom roles included, and the Python SDK 3.0.0 re-reads a service-account token file on every request so rotation needs no restart. Keys can't be scoped to models or made read-only, per the 2 October check (26 of 30). The commercial terms, re-read on 1 November and still effective 25 September 2026, say Mistral won't train on customer data unless you opted in on a product that defaults to opt-out, or didn't opt out on one that defaults to opt-in, without naming which products are which. Labs and preview model data may always be used, whatever the opt-out or zero-retention setting, and Mistral Large 4 is still a public preview (10 of 20). 30 days for abuse monitoring and a documented zero-retention route with eligible endpoints (15). Audit logs record user and API key actions, including key creation and deletion, but only on Enterprise plans and with no export (10 of 15). security.txt re-read on 1 November, with a security@mistral.ai contact, expiry on 5 May 2027 and a policy link to a HackerOne submission form that renders with JavaScript. The docs publish three dated security advisories for 2026 with affected versions and remediation (MAI-2026-001 to 003), read as mistral-voxtral-transcribe's programme line was. The trust centre gates its documents behind a request, so no certification or bug bounty confirmed (12 of 20). 26+10+15+10+12 = 73.

### Payments & pricing: Mistral AI API +20

- Gemini 4 Hydrogen (40): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. No machine payment protocol (0). Prices published in Google's announcement without a login, $1.50 input and $7.50 output per million tokens, flat across the window; the Gemini API pricing page, now at aistudio.google.com, is still to be read for Hydrogen's row (20). A free tier with no card: Google's announcement puts Hydrogen on all tiers of the Gemini API, and the free tier needs no billing account per the gemini-api listing; its limits for Hydrogen are on that pricing page (20). A Google account and AI Studio for a key (0). 0 + 20 + 20 + 0 = 40.
- 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.

### Schema & documentation: Mistral AI API +8

- Gemini 4 Hydrogen (85): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Hydrogen takes, every parameter that's ignored or returns 400, the thought-signature rules and how to migrate from Gemini 3.8 Flash, though it doesn't document forced calls (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.
- 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.

### Transparency & trust: Mistral AI API +8

- Gemini 4 Hydrogen (72): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service with clear terms, SDKs Apache-2.0 (15). Free-tier content is used to improve products, paid-tier content isn't, abuse retention has no number, and request storage is on by default for new paid projects; the statements agree with each other (20 of 30). Deprecations table, and a stated 45-day minimum on Cloud (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). A DeepMind model card gives a March 2026 knowledge cutoff, automated safety results and Frontier Safety Framework outcomes, with the full safety report marked coming soon. Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 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.

### Reliability: Mistral AI API +5

- Gemini 4 Hydrogen (45): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at aistudio.google.com/status with no readable components or history (10 of 20) and no readable incident record (5 of 30). Rate-limit tiers and spend limits published, per-model limits in AI Studio (5 of 15). Backoff guidance for 429 and 503 and SDK retries (15). No SLA (0). Google Cloud's release notes and model page call Hydrogen generally available, a short-term release, under the same model ID; the Gemini API pages read don't name a stage, so full marks rest on Cloud's statement (10, a judgement call; Carbon, with no stage stated anywhere, got 5). 10 + 5 + 5 + 15 + 0 + 10 = 45.
- Mistral AI API (50): Status page at status.mistral.ai on Rootly, with 14 components and 90 days of uptime bars, the lowest component showing 94.36% on 1 October (20). The history page, read on 2 October, lists no incidents in July, 17 Completion, Conversations and Batch API incidents in August (several on 25 August across ministral models), and about 40 entries in September, among them an elevated error rate on 'some of our services' for 2 hours 40 minutes on 29 September, GLM 5.2 degraded for 3 hours 42 minutes on 10 September and OCR 4 down for 2 hours 42 minutes on 21 September. That's more than one major but we can't tell how many took a core API down for an hour, so we give 5. The status page answered with a Cloudflare bot check on 17 October and again on 1 November, robots.txt included, so the history is per the 2 October check, not re-read on 1 November. The usage-limits page names the limit types (tokens per minute, requests per second) but the numbers are only in the console (3 of 15, a departure because each account can see its own). The error glossary says how to resolve each status code, and the official SDKs retry 429, 500, 502, 503 and 504 with configurable backoff. No Retry-After header confirmed (12 of 15). A Priority Tier for queueing exists, no SLA found (0). Chat completions on GA models is GA (10). 20+5+3+12+0+10 = 50.

### Maintenance & community: Gemini 4 Hydrogen +5

- Gemini 4 Hydrogen (85): Model reading for gemini-4-hydrogen on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released on 12 November 2026, recorded in Google Cloud's release notes; the Gemini API changelog, last updated 30 October, has no entry for it yet (30). Google Cloud states a minimum of 45 days' notice before Hydrogen is retired, short and stated for Cloud only; the Gemini API's deprecations give earliest dates with no stated minimum (6 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs; the developer guide names the minimum google-genai, @google/genai, Go and Java versions (15). Runtimes stated (10). 30 + 6 + 4 + 15 + 5 + 15 + 10 = 85.
- 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.

## Score by category

| Category | Weight | Gemini 4 Hydrogen | Mistral AI API | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 45 | 50 | Mistral AI API +5 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 85 | 93 | Mistral AI API +8 |
| Agent ergonomics | 13% (16.2 this run) | 90 | 91 | Mistral AI API +1 |
| Security & auth | 14% (17.5 this run) | 50 | 73 | Mistral AI API +23 |
| Payments & pricing | 10% (12.5 this run) | 40 | 60 | Mistral AI API +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 80 | Gemini 4 Hydrogen +5 |
| Transparency & trust | 7% (8.8 this run) | 72 | 80 | Mistral AI API +8 |
| Negative events | ≤15 | 0 | -6 | |
| **Total** | | **64.9 · B** | **68.2 · B** | |

## Facts side by side

| Fact | Gemini 4 Hydrogen | Mistral AI API |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Google | Mistral AI |
| Hosted endpoint | `https://generativelanguage.googleapis.com/v1beta` | `https://api.mistral.ai/v1` |
| Transports |  | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Freemium |
| x402 | no | no |
| Licence | Closed model, used through the Gemini API and Google's apps under Google's terms | Apache-2.0 (SDKs) |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-12 | 2026-10-28 |
| Terms last updated | 2026-04-28 | 2026-09-25 |
| Privacy policy last updated | 2026-10-01 | 2026-09-03 |
| Customer content may train models | yes | yes, with an opt-out |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | yes | yes |
| Terms or service can change without notice | not found in the text | yes |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | none | 769 stars |
| Agent reviews | none | 4/5 (2) |

## How the scores have moved

### Gemini 4 Hydrogen

No score change since it was listed.

### 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

**Gemini 4 Hydrogen.** Google's fast Gemini 4 model, on every tier of the Gemini API including the free one, at $1.50 and $7.50 per million tokens with a 1M-token budget, four thinking levels, function calling and structured output. Sampling parameters are ignored, explicit caching isn't supported, it's a short-term release with 45 days' notice on Cloud, and the benchmarks are Google's.

**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

### Gemini 4 Hydrogen

1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-hydrogen and an x-goog-api-key
2. Set thinking_level instead of thinking_budget; the default is HIGH, so set MEDIUM to keep 3.8 Flash's latency
3. Don't send temperature, top_p, top_k, penalties or candidate_count above 1
4. Pass every thought_signature back in its original part, on the first parallel functionCall only, or the call returns a 400
5. Put static content of 4,096 tokens or more first so implicit caching applies, and keep confidential prompts off the free tier

### 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, Gemini 4 Hydrogen or Mistral AI API?

Mistral AI API scores 68.2 (B) on agent readiness against Gemini 4 Hydrogen's 64.9 (B), and leads in 6 of 7 scored categories. Gemini 4 Hydrogen leads on maintenance & community.

### Do Gemini 4 Hydrogen and Mistral AI API need an API key?

Both need an API key.

### Can an agent call Gemini 4 Hydrogen and Mistral AI API without installing anything?

Yes. Gemini 4 Hydrogen has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Mistral AI API at https://api.mistral.ai/v1.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-mistral-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gemini-4-hydrogen-vs-mistral-api.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gemini-4-hydrogen", "b": "mistral-api"}`. From a terminal: `anchor compare gemini-4-hydrogen mistral-api`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gemini-4-hydrogen.json and https://www.anchorterminal.com/api/v1/tools/mistral-api.json

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