Paling cocok untukGoogle's Gemini 3.8 Flash for high-volume prompts where a Flash-class model is the one you already grade.
Per 1 juta token · tarif katalog
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.
Paling cocok untukGoogle's Gemini 3.8 Flash for high-volume prompts where a Flash-class model is the one you already grade.
Per 1 juta token · tarif katalog
Paling cocok untukOpenAI's GPT-6.1 Terra, released October 2026, for computer use and visual tasks at the catalog's newer rate.
Per 1 juta token · tarif katalog
Harga GPTProto adalah tarif katalog teks-ke-teks yang terkini. Latensi, konteks, dan tolok ukur muncul hanya saat pengumpulan OpenRouter mengembalikannya untuk kedua model.
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"}]
}'Harga per 1 juta token dari katalog GPTProto. Angka OpenRouter diambil 3 November 2026. Bukan SLA GPTProto.
Pada tarif teks GPTProto terkini, GPT-6.1 Terra sebesar $0.80 per juta token masukan dan $4.00 per juta token keluaran. Gemini 3.8 Flash sebesar $0.90 dan $4.50. Tarif daftar penyedia yang disimpan di sampingnya adalah $1.00/$5.00 untuk GPT-6.1 Terra dan $1.50/$7.50 untuk Gemini 3.8 Flash. GPT-6.1 Terra lebih rendah 11% pada masukan dan 11% pada keluaran, jadi model yang lebih murah tidak bertukar tempat saat balasan panjang.
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.
Periksa halaman terkini Gemini 3.8 Flash dan GPT-6.1 Terra sebelum Anda menganggarkan rute produksi. Perbandingan ini membaca katalog yang sama dengan halaman tersebut. Harganya tidak disalin dari OpenRouter.
Kalikan token masukan dan keluaran yang Anda perkirakan dengan tarif GPTProto terkini. Lalu jalankan set yang nyata. Anggaran yang berguna mencakup cache, alat, percobaan ulang, dan porsi permintaan yang diselesaikan dengan benar oleh tiap model.
Hanya token masukan dan keluaran, pada tarif katalog yang dimuat untuk halaman ini. Cache, alat, dan percobaan ulang dihitung terpisah.
Latensi dan throughput adalah median penyedia OpenRouter. Baris yang hilang tidak ada dalam pengambilan, dan dibiarkan kosong alih-alih ditebak.
Median p50 penyedia OpenRouter, diambil 3 November 2026. Bukan SLA GPTProto.
Uji Gemini 3.8 Flash dan GPT-6.1 Terra dari saldo GPTProto yang sama, pada tarif di halaman model mereka.
Untuk mencoba. Cocok untuk menyambungkan endpoint dan mencoba model baru.
Nominal yang sering dipilih developer yang kerja sendiri, atau proyek kecil yang mau naik produksi.
Untuk tim yang sudah menjalankan trafik produksi. Kredit bonus ditambah di atas harga yang sudah didiskon.
Hanya skor yang ada untuk kedua model yang ditampilkan. Indeks yang lebih tinggi adalah sinyal daftar pendek. Indeks itu tidak memutuskan tugas Anda.
Skor Artificial Analysis yang dibawa pengumpulan OpenRouter, diambil 3 November 2026.
Gunakan model yang pola kegagalannya sudah dapat Anda jelaskan.
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.
Gemini 3.8 Flash lists 1.048.576 tokens of context and 65.536 tokens 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.
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.
Setiap halaman model memuat tarif terkini, contoh API, dan Playground. Jalankan prompt Anda sendiri, lalu pertahankan aturan perutean yang unggul pada kualitas, latensi, dan anggaran. Jelajahi katalog model jika Anda ingin kandidat ketiga dalam pengujian yang sama.
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.
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.
Baca baris latensi dan throughput, yaitu median p50 penyedia OpenRouter, dengan tanggal pengambilan pada catatan tabel. Angka itu bukan target latensi GPTProto. Obrolan singkat peduli pada latensi. Penyelesaian yang panjang peduli pada throughput.
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.
Bukan. Nominal dolar adalah tarif katalog GPTProto untuk adegan teks-ke-teks, termasuk tarif daftar penyedia yang disimpan katalog di sampingnya. OpenRouter adalah sumber latensi, throughput, konteks, batas keluaran, dan skor Artificial Analysis, masing-masing ditandai dengan waktu pengambilannya.
Ya. Gemini 3.8 Flash dan GPT-6.1 Terra masing-masing memiliki halaman model dengan harga, contoh API, dan Playground. Beralih model berarti mengubah nama model pada saldo yang sama.
Para kreator dan developer berbagi model serta alur kerja yang mereka buat.
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.

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.

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

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.

Made with Seedance 2.0 + GPT Image 2 on GPTProto. A Pixar-style commercial with the perfect glow.
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.
I route the calls through GPTProto so a fallback is a config switch instead of a weekend rewrite when a model disappears. It turns "my default model just got export controlled" from an incident into a config change.

I used to switch between different AI tools just to compare results. Now I just use GPTProto. GPT-5, Claude, Gemini, Kimi, and more — all in one workspace.
I route the calls through GPTProto so the model id and latency land in one place regardless of which provider is behind it. The win is having the log schema consistent across providers.

I created this 15-second cinematic product video with GPTProto using Seedance 2.0, and I was really impressed by how smooth the workflow was.

GPTProto routes the character prompt and shot list to a top model on one API key: 20 minutes … voices it and burns in captions from the same key: 20 minutes.
Text, images, and voice are configured separately. You can keep OpenRouter for text and use GPTProto for visuals.
The call layer underneath the router is GPTProto, so swapping a model does not require provisioning a new provider integration. Changing models becomes cheap enough that the question stops being "should we change."
Bandingkan model, pelajari penyiapan API, dan jelajahi alur kerja gambar serta video untuk proyek nyata.
Buat gambar dan video di browser, atau masukkan model teks, gambar, dan video ke aplikasi dengan satu kunci. Harga diskon juga ada di situ.