Best forOpenAI's GPT-6.1 Terra for visual reasoning, computer use, and writing in a text-and-image workflow.
Per 1M tokens · catalog rate
Input$1.00$0.80/M−20%
Output$5.00$4.00/M−20%
// Cross-vendor model comparisonView model page
GPT-6.1 TerravsGemini 3.8 Flash
GPT-6.1 Terra vs Gemini 3.8 Flash starts with the input your application needs. Choose Terra as a first test for visual reasoning, precise computer use, and natural writing in an OpenAI-style workflow. Choose Gemini 3.8 Flash when the task includes native audio, video, or PDF input, or uses Google's documented grounding and tool capabilities. Both produce text and support large-context work. Compare the current promotional price as well as the base catalog rate.
The short answer: at the live GPTProto catalog rates, start with GPT-6.1 Terra. Its input is 11% lower and its output is 11% lower. That is the base catalog comparison. A displayed promotion on Gemini can reverse it, and the price section states that rate only while the promotion is open. Use the same source material and acceptance checks for the tasks both models can perform.
View model page
Best forGoogle's Gemini 3.8 Flash for mixed-media input, including audio, video, and PDF, plus its documented tools.
Per 1M tokens · catalog rate
Input$1.50$0.90/M−40%
Output$7.50$4.50/M−40%
// Side by side
GPT-6.1 Terra vs Gemini 3.8 FlashAt a Glance.
GPTProto prices are the live text-to-text catalog rates. Latency, context, and benchmarks appear only when the OpenRouter harvest returned them for both models.
Spec
GPT-6.1 Terra
Gemini 3.8 Flash
Provider
OpenAI
Google
Model ID
gpt-6.1-terra
gemini-3.8-flash
OpenRouter model
openai/gpt-6.1-terra
google/gemini-3.8-flash
Availability
99.99%
Last 7 days100%
Last 7 daysRelease date
October 26, 2026
September 2, 2026
Input
$0.80$1.00 official list
$0.90$1.50 official list
Output
$4.00$5.00 official list
$4.50$7.50 official list
You save
−20%vs the catalog list rate
−40%vs the catalog list rate
Cache read
$0.04$0.05 official list
$0.09$0.15 official list
Cache write
$1.00$1.25 official list
$0.60$1.00 official list
Context window
1.05M tokens
1,048,576 tokens
Max output tokens
128K tokens
65,536 tokens
Accepts
FileImageText
TextImageVideoFileAudio
Returns
Text
Text
Where it earns its keep
Screenshots, technical drawings, and computer-use steps with a checkable result
Tasks whose source is audio, video, or a PDF, or that need Google's documented tools
Best first test
A text or image task on an existing OpenAI-style route
A mixed-media request you can grade against Terra
In the catalog since
Oct 2026
Sep 2026
API usage
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"}]
}'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"}]
}'Prices per 1M tokens from the GPTProto catalog. OpenRouter figures fetched November 3, 2026. Not a GPTProto SLA.
// Price comparison
Catalog rates first.Then the promotion.
On the live GPTProto text rates, GPT-6.1 Terra is $0.80 per million input tokens and $4.00 per million output tokens. Gemini 3.8 Flash is $0.90 and $4.50. The provider list rates stored beside them are $1.00/$5.00 for GPT-6.1 Terra and $1.50/$7.50 for Gemini 3.8 Flash. GPT-6.1 Terra is 11% lower on input and 11% lower on output, so at these catalog rates the cheaper model does not flip when the reply is long.
During the displayed 0.5× promotion through December 31, 2026, Gemini 3.8 Flash is $0.45 per million input tokens and $2.25 per million output tokens. That promotional input is 44% below GPT-6.1 Terra at $0.80, and the promotional output is 44% below $4.00. Use the price shown for the route and billing period you will actually run. When the promotion closes, this sentence leaves the page and the catalog comparison above remains.
For a batch of 1 million uncached input tokens and 200,000 billed output tokens, the catalog rates come to $1.60 for GPT-6.1 Terra and $1.80 for Gemini 3.8 Flash. The input portion is $0.80 versus $0.90. The output portion is $0.80 versus $0.90. Cache reads, cache writes, tool calls, and media charges are extra.
At the promotional rate, the same batch is $0.90 for Gemini 3.8 Flash: $0.45 of input and $0.45 of output. The catalog batch for GPT-6.1 Terra stays $1.60. A second attempt, or a tool charge, can erase a gap this small.
Check the live GPT-6.1 Terra and Gemini 3.8 Flash pages before you budget a production route. This comparison reads the same catalog those pages use. It does not copy a price from OpenRouter.
// Savings calculator
Run your own numbers.Not ours.
Multiply the input and output tokens you expect by the live GPTProto rates. Then run a real set. A useful budget includes cache, tools, retries, and the share of requests each model finishes correctly.
Pricing model
M tokens
M tokens
You keep, per year
$1,080
Monthly run rateOfficialGPTProtoSave
Input$200$160$40
Output$250$200$50
Per year$5,400$4,320$1,080
Input and output tokens only, at the catalog rate loaded for this page. Cache, tools, and retries are extra.
// Speed and access
How fast. How it is called.What the snapshot shows.
Latency and throughput are OpenRouter provider medians. A missing row was not in the fetch, and it is left out rather than guessed.
Spec
GPT-6.1 Terra
Gemini 3.8 Flash
Supported parameters
include_reasoningmax_completion_tokensmax_tokensreasoningreasoning_effortresponse_formatseedstructured_outputs
include_reasoningmax_tokensreasoningreasoning_effortresponse_formatseedstopstructured_outputs
Tool use
Listed
Listed
Median of OpenRouter provider p50s, fetched November 3, 2026. Not a GPTProto SLA.
// Top-upOne balance.
One balance.
Both models.
Test GPT-6.1 Terra and Gemini 3.8 Flash from the same GPTProto balance, at the rates on their model pages.
$15
Straight credit · no bonus
Get started. Great for testing the endpoint and trying new models.
Most Popular
$100
+4% bonus credits
The sweet spot for individual developers and small projects shipping to production.
Max Savings · +6%
$1,000
+6% bonus credits
Built for teams running production workloads. Bonus credits stack on already-discounted model pricing.
Running 100M tokens/month on Gemini 3.8 Flash? At GPTProto pricing, that’s roughly $720 saved per year vs official pricing — before bonus credits.
// Quality and benchmarks
What the index shows.What it cannot decide.
Only scores present for both models are shown. A higher index is a shortlist signal. It does not decide your tasks.
Spec
GPT-6.1 Terra
Gemini 3.8 Flash
Intelligence Index
51GPT-6.1 Terra (Max)
30.5Gemini 3.8 Flash (High)
Artificial Analysis scores as carried by the OpenRouter harvest, fetched November 3, 2026.
// Verdict
Which model fitsthe input you send?
Use the model whose failure mode you can already describe.
GPT-6.1 Terragpt-6.1-terra
Choose GPT-6.1 Terra for text and images
- Use Terra for screenshots, drawings, writing, and computer-use steps with a clear finish line. At the catalog rates its input is 11% below Gemini 3.8 Flash, and its output is lower by 11%.
- Terra's none effort setting is a concrete difference to include in the route test. Do not copy a Gemini thinking-level name onto the OpenAI request.
- Do not pick Terra for a native audio, video, or PDF input. Add the preprocessing cost if you convert that media first.
Gemini 3.8 Flashgemini-3.8-flash
Choose Gemini 3.8 Flash for mixed media
- Use Flash when audio, video, or PDF input is the task, or when you need its documented grounding and tool calls. Confirm the request format on the model page.
- While the promotion is open, read the promotional rate in the price section and note the end date. The catalog table on this page shows the base rate.
- A lower token rate is not a lower cost per completed task until you count retries, tools, and media charges.
Route by the input, not by the brand
Send native audio, video, and PDF tasks to Gemini. Keep Terra on the text and image steps your grader already checks. Both models are on one GPTProto balance, so the split is a model-name change. Retest the price route when the promotion ends.
// Context and output
Match the input.Then read the limits.
GPT-6.1 Terra lists 1.05M tokens of context. Gemini 3.8 Flash lists 1,048,576 tokens of context and 65,536 tokens of output. Flash's length is the harvested integer, not a rounded million label. OpenAI documents a maximum input and an output ceiling that are separate from the context length shown here. This table shows Terra's output limit when the harvest returns one. A larger window is room for a long prompt, not a lower input rate.
Terra's documented inputs are text and image, and its output is text. Google documents text, image, video, audio, and PDF inputs for Gemini 3.8 Flash, with text output. Image generation and audio generation are separate models. For an audio or video workflow built around Terra, an earlier step has to supply a transcript, extracted frames, or other supported material, and that step belongs in the cost.
Terra supports none, low, medium, high, xhigh, and max effort. Gemini supports low, medium, and high thinking levels. Use each model's own request field. OpenAI requires the Responses API for Terra tool calling. Google's documentation lists function calling, code execution, search grounding, file search, URL context, and computer use in Preview. On GPTProto, start from the selected model's API Usage example and test each tool on that route.
// How to decide
Route by the inputand the tool.
Both models accept images and return text. Terra's official examples include matching product photos, interpreting technical drawings, and acting on application screens. Gemini accepts images inside a broader multimodal interface. Score extracted identifiers, dimensions, labels, or next actions against verified answers, and include small text and ambiguous references when those cases appear in your application.
Google positions Gemini 3.8 Flash for long-horizon software engineering, autonomous agents, and enterprise workflows. OpenAI positions Terra for efficient visual reasoning, precise computer use, and writing. For a coding task, check the final patch and the test results. For an enterprise workflow, check the data written, the required approvals, and the completed state. Record repeated calls so the bill is the full task.
If the application contains both kinds of work, send native mixed-media tasks to a supported Gemini route and evaluate Terra for the image or text steps. Choose Terra first when the work is text and images, computer-based actions, writing, or an existing OpenAI-style integration. Choose Gemini first when audio, video, or PDF input is central, or when the application needs its documented Google tools. Record the promotion end date next to any cost estimate that uses the promotional rate.
// Get started
Try both on one balancebefore you pick a default.
Each model page has the current rate, an API example, and a Playground. Run your own prompts, then keep the routing rule that wins on quality, latency, and budget. Browse the model catalog if you want a third candidate in the same test. Compare current GPTProto pricing.
// FAQ
Terra vs Gemini 3.8 Flash.Straight answers.
01Which is cheaper: GPT-6.1 Terra or Gemini 3.8 Flash?
At the live catalog rates, GPT-6.1 Terra is $0.80 input and $4.00 output per million tokens, against $0.90 and $4.50 for Gemini 3.8 Flash. That is 11% less on input and 11% less on output. The price section states Gemini's displayed promotion only while that window is open. Compare the billing period you will actually run.
02What is the key difference in GPT-6.1 Terra vs Gemini 3.8 Flash inputs?
Terra accepts text and images. Google documents text, images, video, audio, and PDFs for Gemini 3.8 Flash. Both return text. Use the request format supported by the chosen GPTProto route.
03Which model has a larger output limit?
Gemini 3.8 Flash lists 65,536 tokens of output. OpenAI publishes an output ceiling for Terra as well. This page shows Terra's output row when the harvest returns a length. Set the requested output budget and verify the final artifact.
04Can either model generate images or audio directly?
These models return text. Google lists image generation and audio generation as unsupported for Gemini 3.8 Flash. Terra's native output modality is text. Choose a dedicated generation model for image or audio files.
05Can I use the same reasoning parameter for both?
Use each route's supported controls. Terra offers six effort levels, including none. Gemini offers low, medium, and high thinking levels. Start from the API Usage example for the selected model.
06How should I compare computer-use performance?
Run the same actions in the same environment with matching permissions, timeouts, and final-state checks. Record successful completion, invalid actions, recovery steps, elapsed time, and the entire task cost.
07Are these OpenRouter prices?
No. The dollar amounts are GPTProto's catalog rates for the text-to-text scene, including the provider list rate the catalog stores beside them. OpenRouter is the source for latency, throughput, context, output limit, and the Artificial Analysis scores, each marked with its fetch time.
// Social proof
See how others use GPTProto.
Creators and developers share the models and workflows they built with.
BL#Routing
Blogstra
Reddit · r/Bloggers
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.
K
#Cost
K
X (Twitter) · @ChillaiKalan__
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.
SN
#Video
Sanskriti Naruka
X (Twitter) · @snskritinaruka
I turned this single prompt into a cinematic fantasy video using GPTProto. "Continuous 15-second cinematic shot, 4K resolution, hyper-realistic dark fantasy photorealism…"
CF
#Video
Caden Flux
X (Twitter) · @Caden_Flux
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.
Z
#Creative
Zara
X (Twitter) · @ZaraIrahh
Made with Seedance 2.0 + GPT Image 2 on GPTProto. A Pixar-style commercial with the perfect glow.
MO#Integration
Many-Operation2625
Reddit · r/LLMDevs
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.
OB#Resilience
obxsurfer06
Reddit · r/singularity
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.
AL
#Models
Alice The Ai Expert
X (Twitter) · @AliceInfoAi
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.
EB#DevOps
EntireBig7258
Reddit · r/LLMDevs
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.
AL
#Video
Alamin
X (Twitter) · @iam_chonchol
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.
F
#Workflow
Fokki
X (Twitter) · @0x_fokki
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.
FA#Apps
FormalAd4696
Reddit · r/SillyTavernAI
Text, images, and voice are configured separately. You can keep OpenRouter for text and use GPTProto for visuals.
AF#Teams
Any-Farm-1033
Reddit · r/EngineeringManagers
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."
// From the blog
View all posts →AI Model Guides.Practical API Tutorials.
Compare models, learn API setup, and explore image and video workflows for real projects.
// Get started
Your next 100,000,000 tokensshouldn't cost full price.
Create images and videos online, or bring text, image, and video models into your app with one API key. Explore discounted rates on selected models.
- ✓OpenAI-compatible
- ✓200+ models
- ✓10–30% lower than official
- ✓High uptime, auto-failover
✓Copied to clipboard