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Gemini 4 Argon Review: 1M Context, but a 65,536-Token Reply Cap
Pick Gemini 4 Argon for million-token analysis with images and audio, but plan around its 65,536-token reply cap; so far we have run only launch checks.
Freedom Score
未テスト
- 料金
- $8.00 混合 100 万トークンあたり（入力 3：出力 1）
- 出力速度
- 33 トークン/秒
- 成功率
- データ収集中
Gemini 4 Argon is Google's new frontier model, announced on 30 September 2026 and aimed at software engineering, enterprise knowledge work and cyber defence. On our API it is one OpenAI-compatible chat endpoint that takes text, images and audio, reads up to 1,048,576 tokens and returns up to 65,536 tokens per reply, with function calling, streaming and three reasoning levels.
- SpicyAPI Engineering
- 2026年10月28日 にテスト
- 評価方法 v3.3 →
- 販売中のモデルですが、スコアに料金は無関係です →
The verdict
The most common point of confusion is the output limit. Google's announcement mentions a 1M-token output ceiling, but its developer documentation ties that to a separate long-running mode, while ordinary synchronous calls stop at 65,536 tokens. Our endpoint is the synchronous kind, so plan for 65,536 per reply and split longer work across turns.
This is a launch-day review. On 28 October 2026 our platform ran a real request through the endpoint as part of launch: one neutral message, answered without streaming at low reasoning effort. It returned a complete answer. We also tried video input three ways during integration and it was rejected each time, so this endpoint does not offer video. We have not run a quality blind test or a content-level test, and this page does not score the model.
Key facts
- Tested: one real launch request on 28 Oct 2026 (neutral prompt, low reasoning effort, no streaming), plus integration checks of image and audio input and of video rejection. No scored runs yet.
- Price: the live price, including cached input, is on the model page.
- Limits: 1,048,576-token context shared by input and output, replies up to 65,536 tokens (default 4,096, thinking included), text, image and audio input (wav or mp3, 14 MB combined inline), no video or PDF parts.
- Reasoning: reasoning_effort takes low, medium or high (default medium); thinking cannot be switched off.
- Sources: scoring rules are on our review methodology page, full parameters on the Gemini 4 Argon model page.
良かった点と足りなかった点
良かった点
- Audio is accepted directly. wav or mp3 can be sent as audiourl or base64 inputaudio next to text and images, so a voice note or call recording sits in the same conversation as your instructions.
- A million-token window. Contracts, transcripts, a specification and the code it describes can travel together as written.
- Sampling stays adjustable. temperature (0 to 2) and topp are available, along with stop sequences and responseformat.
- Tool calling is on the endpoint. Up to 128 function definitions per request with toolchoice and paralleltool_calls; we have not graded tool-use quality yet.
- Google publishes numbers. Google reports 77.9% on DeepSWE v1.1 (long-horizon software engineering) and 51.3% on AutomationBench. Those are Google's figures; we have not reproduced them.
足りなかった点
- Replies stop at 65,536 tokens here. The 1M-output figure in Google's announcement does not apply to this endpoint, and thinking counts toward the 65,536.
- No video input. Google lists video among the model's input types, but our three integration attempts were all rejected, so frames or a separate audio track are the workaround.
- No PDF parts. Send pages as images or extracted text.
- Thinking cannot be turned off, and low is the lightest setting, so short lookups still pay for a reasoning pass.
- No quality numbers of our own yet. We have not run a blind test, a speed test or a long-document test.
What we tested
On 28 October 2026 our platform sent Gemini 4 Argon one real request as part of launch: a single neutral user message, answered without streaming at low reasoning effort with a 1,024-token cap. It returned a complete answer, and the request was priced at the published rate. The endpoint also passed our pre-launch checks of its price table and request limits.
During integration, image and audio input were accepted and answered. Video was different: a one-second clip with sound, a five-second silent clip and the same clip sent inline each came back as a rejected request, so the endpoint declares only images and audio.
That is a working-endpoint check, not a benchmark. We have not compared Argon's answers with another model, measured speed, or tried a prompt near the 1,048,576-token limit.
Prompts to start from
These starting prompts come from the model page's published examples. We have not graded the outputs, so they are a place to begin rather than prompts proven on this model.
1. Compare a transcript with a brief. Paste both documents, label them, and say which is authoritative.
Compare a meeting transcript with the product brief and list unresolved decisions. Work from the material I provide, cite the relevant evidence, distinguish facts from assumptions, and identify missing information before proposing changes.Run this prompt on Gemini 4 Argon →
2. A tool step. Confirms your function-calling loop end to end with a trivial function.
Call report_status with status ready.Settings that matter: raise maxtokens as you raise reasoningeffort, because thinking is paid for out of the same 65,536; send audio inline and keep it under 14 MB combined; for work longer than one reply, ask for it in parts.
How far it writes
We have not run our content-level test on Gemini 4 Argon, so we have no result to report and the endpoint carries no Unrestricted label. The model page states the position plainly: content decisions come from the model, behaviour can vary, and no guarantee of unrestricted output is made.
Not tested yet: the content-level ladder, multi-turn behaviour over a long session, languages other than English, audio quality on noisy recordings, and prompts close to the context limit.
Every character in a request should be an adult, keep real, identifiable people out of it, and you are responsible for the law where you publish.
What the community says
Reaction on the launch thread was cautious about the benchmarks. One reader wrote "Big number results, and impressive pricing. That said it really feels like benchmarks have been hyper saturated these days." Another was blunter about where they would use it: "Hate to say i will never be touching this model for anything except for youtube video understanding", which is the one input type our endpoint does not offer.
Alternatives
- Hard coding with a larger reply ceiling? GPT 6.1 Sol allows replies up to 128,000 tokens and takes images but not audio.
- A lighter Google model? Gemini 3.7 Flash is the Flash-class option from the same publisher.
- An Anthropic flagship? Claude Opus 5.5 is the Anthropic option on the same API; compare it on your own prompts.
Gemini 4 Argon の Spicy Index の内訳
各項目から採点の詳細に進めます。点数がどの行から来たのか、なぜ減点されたのかがわかります。
- 公開リーダーボード 品質の 40%
- 未テスト
- ロールプレイ 品質の 15%
- 未テスト
- 創作文 品質の 15%
- 61.6
- 指示への従い方 品質の 15%
- 99.0
- 長いコンテキストの記憶 品質の 15%
- 未テスト
- 機能 重み 10.5%
- 56.0
- Freedom Score 重み 30%
- 未テスト
追跡している公開リーダーボードに、完全に一致するエントリーはまだありません。 仕組み
このモデルではまだロールプレイのテストを実施していません。 仕組み
このモデルではまだ長いコンテキストのテストを実施していません。 仕組み
自由度が未測定、または証拠が不十分です。Index は元の品質・機能スコアを維持し、暫定表示で順位に含めます。証拠の欠如を 0 点とは扱いません。 仕組み
自由度が未測定、または証拠が不十分です。Index は元の品質・機能スコアを維持し、暫定表示で順位に含めます。証拠の欠如を 0 点とは扱いません。
テストレポートをすべて見る →機能の項目別採点
公開採点表の点数です。アップスケールで作る解像度や、当社が独自に設けた上限は数えません。
- コンテキスト長（開発元の公表値）未記載
- 0.0 / 30
- SpicyAPI での入力形式テキストと画像, 音声
- 19.0 / 25
- ツール使用ツールと tool_choice
- 15.0 / 15
- 構造化出力対応、スキーマ準拠を確認済み
- 15.0 / 15
- 推論の制御3 段階：low · medium · high
- 7.0 / 15
SpicyAPI で Gemini 4 Argon にできること
SpicyAPI の現在のモデル仕様から直接取得しています。開発元が自社アプリでより多くの機能を提供している場合もありますが、ここに載っているのは現在当社の API から呼び出せる機能です。
| 機能 | チャット |
|---|---|
| コンテキスト長 | 1,048,576 トークン |
| 1 リクエストの最大出力 | 65,536 トークン |
| 推論レベル | low · medium · high |
| ツール呼び出し | あり |
| 構造化出力 | あり |
実際にかかる時間
過去 30 日の実際のジョブで、リクエストから完成までを計測しています。所要時間には当社自身のテスト実行も含みます。
- 出力速度
- 33 トークン/秒最初のトークンまでの時間を含みます
- 成功率
- データ収集中
完了したジョブが 10 件以上そろうと所要時間を表示します。成功率はお客様のジョブだけで数え、30 日分のトラフィックがそろうまで全モデルで非表示にしています。
Gemini 4 Argon についての声
肯定的 0・賛否 1・否定的 1
Big number results, and impressive pricing. That said it really feels like benchmarks have been hyper saturated these days.
hacker-news· 2026年9月30日· 賛否あり出典
Hate to say i will never be touching this model for anything except for youtube video understanding
hacker-news· 2026年9月30日· 否定的出典
引用は公開投稿の原文そのままで、元の投稿にリンクしています。評価ではなく、どのスコアにも反映していません。
Gemini 4 Argon の代わりに検討できるモデル
OpenAI
GPT 6.1 Sol
Hard coding with a larger reply ceiling?
- Spicy Index
- 81.2+4.5
- Freedom Score
- —
- 料金
- $4.00−50%/ 100 万トークン・入力/出力 3:1
Google
Gemini 3.7 Flash
A lighter Google model?
- Spicy Index
- 77.8+1.1
- Freedom Score
- 73.3
- 料金
- $1.35−83%/ 100 万トークン・入力/出力 3:1
Anthropic
Claude Opus 5.5
An Anthropic flagship?
- Spicy Index
- 82.5+5.8
- Freedom Score
- 88.9
- 料金
- $7.20−10%/ 100 万トークン・入力/出力 3:1
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Gemini 4 Argon のよくある質問
Gemini 4 Argon を自分で試す
プレイグラウンドで全パラメーターを設定し、実行前に正確な料金を確認できます。
$8.00 混合 100 万トークンあたり（入力 3：出力 1）
ほかのレビュー
ランキングを見る →GPT 6.1 Terra
Pick GPT 6.1 Terra for high-volume screens, documents and writing where reasoning_effort none helps; so far we have run only launch checks, no scored tests.
- Spicy Index
- 79.9
- Freedom Score
- —
2026年10月28日 にテスト
レビューを読むKimi K3.1 Pro
Pick Kimi K3.1 Pro for long-context work with screenshots and clips when you accept always-on thinking; so far we have run only launch checks, no scored tests.
- Spicy Index
- 80.4
- Freedom Score
- —
2026年10月28日 にテスト
レビューを読む
Grok 4.3
巨大な文脈窓、本物の推論オフ、低価格の規制なし文章が欲しいなら Grok 4.3。ファイル添付が要るなら見送りを。
2026年9月24日 にテスト
レビューを読む