# Gemini 4 Argon

Model id on AIHubMix: `gemini-4-argon`
Create an API key: https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms

> Gemini 4 Argon is Google DeepMind’s multimodal reasoning model for complex software engineering, financial research, legal drafting, and cybersecurity defense. It supports sustained reasoning across long, multi-step workflows, combining coding capabilities with chart and long-video understanding. It can also autonomously discover, validate, and patch software vulnerabilities.

- Developer: Google
- Context window: 1,048,576 tokens
- Input modalities: text, image, video, audio, PDF
- Capabilities: Thinking, Streaming, Tool calling, Web search, URL context, Code interpreter, Computer use, File search, Structured outputs, Prompt caching
- Pricing: $2/M input tokens, $10/M output tokens, $0.1/M cached input

## Endpoints (base URL: https://aihubmix.com)

- `POST /v1/chat/completions` — OpenAI Chat Completions (`Authorization: Bearer $AIHUBMIX_API_KEY`)

## Example

```bash
curl -s https://aihubmix.com/v1/chat/completions \
  -H "Authorization: Bearer $AIHUBMIX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"gemini-4-argon","messages":[{"role":"user","content":"Hello"}]}'
```

## Response

Without `stream`, `/v1/chat/completions` returns a standard Chat Completions object:

```json
{"id":"...","object":"chat.completion","model":"gemini-4-argon","choices":[{"message":{"role":"assistant","content":"..."}}],"usage":{"prompt_tokens":12,"completion_tokens":24,"total_tokens":36}}
```

With `"stream": true` the response is `text/event-stream`: read each `data:` JSON chunk until `data: [DONE]`. The Messages and Gemini endpoints return their protocols' native response shapes (Anthropic / Google).

## Errors

Error responses carry a `tid` (trace id) — include it when contacting support. Reference: https://docs.aihubmix.com/en/FAQs/HTTP-Codes.md

- 400 — parameter error; most are passed through from the upstream provider (media: `prompt_missing`, `size_not_supported`, `n_not_within_range`, …)
- 401 — missing `Authorization` header, or the key is invalid/expired
- 403 — `insufficient_user_quota` (top up at https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms), account suspended, or this key is not allowed to use this model
- 429 — rate limited; back off and retry
- 503 — no channel can serve the request (check the model id and your access), or the upstream provider is throttling; retry later

## More

- Model page: https://aihubmix.com/model/gemini-4-argon
- Try in browser: https://aihubmix.com/playground?model=gemini-4-argon
- Compare with another model (human-facing, side-by-side specs and pricing): https://aihubmix.com/compare — pick this model and a peer there; published pairs are listed in https://aihubmix.com/sitemap-compare.xml, unpublished pairs 404 so do not compose the path by hand
- Full parameter schema (machine-readable, authoritative): https://aihubmix.com/model-data/models/gemini-4-argon.c768758f.json — per-protocol parameters with types, ranges, enums and defaults. Refreshed together with this page; if it ever 404s, re-resolve via `https://aihubmix.com/model-data/index.json` (find this id, fetch its `path`)
- Generate runnable code programmatically: npm `@aihubmix/codegen` — the generator behind the Playground's "Get Code" (4 protocols × 7 languages, media endpoints included); the body it builds is the exact wire body the Playground sends, so generated snippets and real requests cannot diverge. `@aihubmix/model-schema` (npm) translates the parameter schema above into codegen input
- Site index for agents: https://aihubmix.com/llms.txt · Onboarding: https://aihubmix.com/agents.md

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Canonical version of this document: https://aihubmix.com/model/gemini-4-argon/llms.txt