定價+7% 贈送
// 跨供應商模型比較

Gemini 3.8 FlashvsGPT-6.1 Terra

作者 GPTProto

GPT-6.1 Terra is the model OpenAI released at the end of October 2026, and the pricing roundups that followed put it next to Gemini 3.8 Flash. They are not the same product. Flash is the high-volume Gemini route. Terra is the new computer-use and visual model. Public comparisons of this pair mix effort settings, so this page does not award an index. It prices both from the GPTProto text catalog, and it does not copy a token price from OpenRouter.

The short answer: start the cost check with GPT-6.1 Terra. On the live GPTProto rates its input is 11% lower and its output is 11% lower. The struck-through figures are the provider list rates from the same catalog. The gap is small enough that retries can erase it. Keep both models in the test, and read a benchmark row only when both scores are present.

在 GPTProto 上探索 Gemini 3.8 Flash在 GPTProto 上探索 GPT-6.1 Terra
// 並排比較

Gemini 3.8 Flash vs GPT-6.1 Terra一眼看完。

GPTProto 價格是即時的文字對文字目錄費率。只有 OpenRouter 擷取為兩個模型都帶回時，延遲、上下文和基準才出現。

規格
Gemini 3.8 Flash
GPT-6.1 Terra
供應商
Google
OpenAI
模型 ID
gemini-3.8-flash
gpt-6.1-terra
OpenRouter 模型
google/gemini-3.8-flash
openai/gpt-6.1-terra
可用性
100%
最近 7 天
99.99%
最近 7 天
發布日期
2026年9月2日
2026年10月26日
輸入
$0.90$1.50 官方牌價
$0.80$1.00 官方牌價
輸出
$4.50$7.50 官方牌價
$4.00$5.00 官方牌價
你省下
−40%相較目錄牌價
−20%相較目錄牌價
快取讀取
$0.09$0.15 官方牌價
$0.04$0.05 官方牌價
快取寫入
$0.60$1.00 官方牌價
$1.00$1.25 官方牌價
上下文視窗
1,048,576 token
105 萬 token
最大輸出 token
65,536 token
12.8 萬 token
接受
文字圖片影片檔案音訊
檔案圖片文字
輸出
文字
文字
它擅長的地方
Repeated prompts that already run on a Gemini Flash route
Visual checks and computer-use steps where the catalog rate still has to clear the bar
最適合的第一次測試
A high-volume step you can grade against Terra
一張截圖、一份表單，或一個有可核對結果的桌面步驟
上架時間
2026年9月
2026年10月
API 用法
curl https://gptproto.com/v1/chat/completions \
  -H "Authorization: Bearer $GPTPROTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.8-flash",
    "messages": [{"role": "user", "content": "Hi"}]
  }'
curl https://gptproto.com/v1/chat/completions \
  -H "Authorization: Bearer $GPTPROTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6.1-terra",
    "messages": [{"role": "user", "content": "Hi"}]
  }'

價格來自 GPTProto 目錄，每 100 萬 token。OpenRouter 數字抓取於 2026年11月3日。不是 GPTProto SLA。

輸入與輸出價格 · 每 100 萬 token · 每一對都相對自己的官方牌價縮放
官方GPTProto
Gemini 3.8 FlashGoogle
輸入$1.50
輸入−40%$0.90
輸出$7.50
輸出−40%$4.50
GPT-6.1 TerraOpenAI
輸入$1.00
輸入−20%$0.80
輸出$5.00
輸出−20%$4.00
// 價格比較

A small gap在兩邊。

在即時 GPTProto 文字費率上，GPT-6.1 Terra 是每 100 萬輸入 token $0.80、每 100 萬輸出 token $4.00。Gemini 3.8 Flash 是 $0.90 和 $4.50。存在旁邊的供應商牌價是 $1.00/$5.00 的 GPT-6.1 Terra，以及 $1.50/$7.50 的 Gemini 3.8 Flash。GPT-6.1 Terra 的輸入低 11%、輸出低 11%，所以回覆變長時，較便宜的模型不會反轉。

For a request with 10,000 uncached input tokens and 1,000 output tokens, those GPTProto rates come to about $0.012 for GPT-6.1 Terra and $0.0135 for Gemini 3.8 Flash. That illustration is input plus output only. Cache reads, cache writes, tool calls, and retries are extra, and a second attempt can erase the gap. Vendor price cards can step up once a prompt passes a length threshold. This page shows the one text-to-text catalog rate, not a second tier.

為正式路由編預算前，先查看即時的 Gemini 3.8 Flash 和 GPT-6.1 Terra 頁面。這份比較讀的是那些頁面用的同一份目錄。它不會從 OpenRouter 複製價格。

// 節省計算機

用你自己的數字算。不是我們的。

把你預期的輸入和輸出 token 乘上即時 GPTProto 費率。然後跑一組真實測試。有用的預算要包含快取、工具、重試，以及每個模型正確完成的請求比例。

計價模型
百萬 token
百萬 token
一年你留下
$1,080
每月運行成本官方GPTProto省下
輸入$200$160$40
輸出$250$200$50
每年$5,400$4,320$1,080

只有輸入和輸出 token，用本頁載入的目錄費率。快取、工具和重試另計。

查看儲值檔位
// 速度與存取

有多快。怎麼呼叫。快照顯示什麼。

延遲和吞吐量是 OpenRouter 供應商中位數。缺的那一列不在這次抓取裡，所以略過，而不是猜測。

規格
Gemini 3.8 Flash
GPT-6.1 Terra
支援的參數
include_reasoningmax_tokensreasoningreasoning_effortresponse_formatseedstopstructured_outputs
include_reasoningmax_completion_tokensmax_tokensreasoningreasoning_effortresponse_formatseedstructured_outputs
工具呼叫
已列出
已列出

OpenRouter 供應商 p50 的中位數，抓取於 2026年11月3日。不是 GPTProto SLA。

// 儲值

一個餘額。
兩個模型。

用同一個 GPTProto 餘額測試 Gemini 3.8 Flash 和 GPT-6.1 Terra，費率以它們的模型頁為準。

$15
原額入帳 · 無贈送

先試。拿來打通端點、換幾個模型看看。

最多人選擇
$100
+4% 贈送額度

個人開發、小型專案要上線，多半從這裡開始。

省最多 · +6%
$1,000
+6% 贈送額度

給已經在跑正式流量的團隊。贈送金疊在已經打折的模型價格上。

Gemini 3.8 Flash 每月用 1 億 token？以 GPTProto 的價格，一年大約比官方少 $720 — 尚未計入贈送金。
// 品質與基準

指數顯示什麼。它決定不了什麼。

只顯示兩個模型都有的分數。較高的指數是候選信號。它不決定你的任務。

規格
Gemini 3.8 Flash
GPT-6.1 Terra
智力指數
30.5Gemini 3.8 Flash (High)
51GPT-6.1 Terra (Max)

OpenRouter 擷取所帶的 Artificial Analysis 分數，抓取於 2026年11月3日。

// 結論

哪個模型適合你最常打的呼叫？

用你已經能描述其失敗模式的模型。

Gemini 3.8 Flashgemini-3.8-flash
Choose Gemini 3.8 Flash for the route you already grade
  • Use Flash when the prompt already runs on Gemini and you can grade the result against Terra.
  • Do not treat one intelligence index as the decision. Published comparisons of this pair mix effort settings, and the table shows a score only when the harvest has it for both models.
  • 本頁的延遲數字是 OpenRouter 供應商中位數，不是對你這條路由的承諾。請計時你實際會打的那次呼叫。
在 GPTProto 上測試 Gemini 3.8 Flash
GPT-6.1 Terragpt-6.1-terra
Choose GPT-6.1 Terra when the rate is the constraint
  • Use Terra for visual checks, form filling, and other computer-use steps with a clear finish line. The listed input rate is 11% below Gemini 3.8 Flash, and the output rate is lower by 11%.
  • A lower token rate is not a lower cost per completed task until you count retries. Run the same set you use for Flash.
  • Do not pick Terra on window size alone. If its context cell is a catalog label, the table note says so.
在 GPTProto 上測試 GPT-6.1 Terra

按步驟分流，而不是按品牌

Send the repeated, checkable steps to the model with the lower GPTProto rate, and keep Flash on the prompts your Gemini grader already prefers. Write down when the switch changes the result. Both models are on one GPTProto balance, so the split is a model-name change.

// 上下文與輸出

Read Flash's window.等 Terra 的。

Gemini 3.8 Flash lists 1,048,576 token of context and 65,536 token of output. That length is the harvested integer, not a rounded million label. A larger window is room for a long prompt, not a lower input rate. OpenAI's launch note describes Terra as a million-token-class model. If Terra's context cell is filled from the catalog label, the table note says so, and that label is rounded.

// 怎麼做決定

Grade the new modelon the work Flash already runs.

Do not pick Terra because it is new, or Flash because the route is already Gemini, until the same set has run on both. Use work you already trust: a high-volume prompt, a visual check, and a case that must reject a bad input. Send the same instructions, tools, and grader. Record task success, total tokens, retries, and time to the last token. Cost per successful task is the number to keep. A small token gap loses when it needs the extra try.

// 開始使用

用同一個餘額試用兩者選定預設之前。

每個模型頁都有目前費率、API 示例和 Playground。跑你自己的提示，然後留下在品質、延遲和預算上勝出的分流規則。若想在同一組測試裡放進第三個候選，瀏覽模型目錄。

查看 Gemini 3.8 Flash 的 API 與價格查看 GPT-6.1 Terra 的 API 與價格
// 常見問題

Gemini 3.8 Flash vs GPT-6.1 Terra.直接回答。

01Is GPT-6.1 Terra cheaper than Gemini 3.8 Flash on GPTProto?+

On the live GPTProto rates, yes. Terra is $0.80 input and $4.00 output per million tokens, against $0.90 and $4.50 for Flash. That is 11% less on input and 11% less on output. The provider list rates in the catalog are $1.50/$7.50 for Gemini 3.8 Flash and $1.00/$5.00 for GPT-6.1 Terra. Cache and retries can change a full bill.

02哪個模型分數更高？+

This page does not award that. A published comparison of these names uses a non-reasoning Terra setting against a high-effort Flash setting, so the indexes are not the same test. The intelligence row appears only when the OpenRouter harvest has a score for both models. Use it to shortlist, then test the jobs you will run.

03哪一個回應更快？+

看延遲和吞吐量這兩列。它們是 OpenRouter 供應商 p50 的中位數，抓取日期寫在表格註記裡。它們不是 GPTProto 的延遲目標。短對話在意延遲。長的完成在意吞吐量。

04它們接受相同的上下文視窗嗎？+

Read the context row. Flash's harvested length is the integer the harvest returned, which is not a rounded million label. If Terra's cell is filled from the catalog label, the table note says so. Treat a larger window as room for a long request, and test quality at the lengths you will send.

05這些是 OpenRouter 的價格嗎？+

不是。這些美元金額是 GPTProto 文字對文字場景的目錄費率，包含目錄存在旁邊的供應商牌價。OpenRouter 是延遲、吞吐量、上下文、輸出上限和 Artificial Analysis 分數的來源，每一項都標了抓取時間。

06我可以透過 GPTProto 呼叫兩者嗎？+

可以。Gemini 3.8 Flash 和 GPT-6.1 Terra 各自有模型頁，含價格、API 示例和 Playground。切換模型就是在同一個餘額上改模型名稱。

// 使用者怎麼說

不要只聽我們說。聽聽他們的。

這些是真實公開帳號的貼文。這裡沒有編造的內容。

BL
Blogstra
Reddit · r/Bloggers
#Routing

For a team already juggling DeepSeek, Kimi, Qwen, or other providers, a shared routing layer can be reasonable if it removes duplicated work and the fallback behavior is tested. GPTProto is one implementation of this approach.

KK
K
X (Twitter) · @ChillaiKalan__
#Cost

I've been testing GPTProto recently, and it's honestly made my creative workflow much simpler. Instead of paying for multiple subscriptions, I can access several leading AI models from one place.

SNSanskriti Naruka
Sanskriti Naruka
X (Twitter) · @snskritinaruka
#Video

I turned this single prompt into a cinematic fantasy video using GPTProto. "Continuous 15-second cinematic shot, 4K resolution, hyper-realistic dark fantasy photorealism…"

CFCaden Flux
Caden Flux
X (Twitter) · @Caden_Flux
#Video

I challenged myself to create a cinematic AI cooking short in just 15 seconds. I used GPTProto to bring the entire workflow together, from image generation to video, all in one place.

ZZara
Zara
X (Twitter) · @ZaraIrahh
#Creative

Made with Seedance 2.0 + GPT Image 2 on GPTProto. A Pixar-style commercial with the perfect glow.

MO
Many-Operation2625
Reddit · r/LLMDevs
#Integration

What worked for me was pointing the cloud connections at GPTProto so the frontend only sees one endpoint and I just change the model name to swap. I am not rebuilding a connection from scratch every time.

// 來自部落格

AI 模型指南。實用的 API 教學。

比較模型、了解 API 設定，以及圖像和影片在實際專案裡的做法。

查看全部文章 →

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// 開始

接下來這一億 token不必再付原價。

在瀏覽器裡做圖和影片，或用一把 API 金鑰把文字、圖像、影片模型接到應用裡。指定模型的折扣也在這裡。

  • ✓相容 OpenAI
  • ✓200 多個模型
  • ✓比官方低 10–30%
  • ✓高可用，自動容錯
✓已複製到剪貼簿