Pricing+7% bonus
// Cross-vendor model comparison

Claude Sonnet 5.5vsGPT-6.1 Terra

GPT-6.1 Terra is the model OpenAI released at the end of October 2026 for fast computer use and visual work, and the writeups that followed put it next to Claude Sonnet 5.5. They are not the same product. Sonnet is the model teams already use for graded coding and tool loops. Terra is the new lower rate. This page prices both from the GPTProto text catalog. It does not copy a token price from OpenRouter, and it does not treat one public index as the winner.

The short answer: start the cost check with GPT-6.1 Terra. On the live GPTProto rates its input is 56% lower and its output is 56% lower. The struck-through figures are the provider list rates from the same catalog. Public comparisons still give Sonnet the higher intelligence index at the settings they publish, and they give Terra the lower bill. Read the benchmark row only when both scores are present, then test the prompts you will send.

// Side by side

Claude Sonnet 5.5 vs GPT-6.1 TerraAt 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
Claude Sonnet 5.5
GPT-6.1 Terra
Provider
Claude
OpenAI
Model ID
claude-sonnet-5-5
gpt-6.1-terra
Availability
83.6%
Last 7 days
100%
1 day of traffic since Oct 27
Input
$1.80$2.00 official list
$0.80$1.00 official list
Output
$9.00$10.00 official list
$4.00$5.00 official list
You save
−10%vs the catalog list rate
−20%vs the catalog list rate
Cache read
$0.09$0.10 official list
$0.04$0.05 official list
Cache write
$2.25$2.50 official list
$1.00$1.25 official list
Where it earns its keep
Coding and tool steps you already know how to grade
Repeated visual and computer-use steps where the token rate is the constraint
Best first test
A coding agent loop where a missed edit is expensive
A high-volume step with a screenshot, a form, or a checkable result
In the catalog since
Sep 2026
Oct 2026
API usage
curl https://gptproto.com/v1/chat/completions \
  -H "Authorization: Bearer $GPTPROTO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-5-5",
    "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"}]
  }'

Prices per 1M tokens from the GPTProto catalog. OpenRouter figures fetched October 20, 2026. Not a GPTProto SLA.

Input & output price · per 1M tokens · each pair scaled to its official rate
OfficialGPTProto
Claude Sonnet 5.5Claude
Input$2.00
Input−10%$1.80
Output$10.00
Output−10%$9.00
GPT-6.1 TerraOpenAI
Input$1.00
Input−20%$0.80
Output$5.00
Output−20%$4.00
// Price comparison

The new rateis lower on both sides.

On the live GPTProto text rates, GPT-6.1 Terra is $0.80 per million input tokens and $4.00 per million output tokens. Claude Sonnet 5.5 is $1.80 and $9.00. The provider list rates stored beside them are $1.00/$5.00 for GPT-6.1 Terra and $2.00/$10.00 for Claude Sonnet 5.5. GPT-6.1 Terra is 56% lower on input and 56% lower on output, so the cheaper model does not flip when the reply is long.

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 $0.027 for Claude Sonnet 5.5. That illustration is input plus output only. Cache reads, cache writes, tool calls, and retries are extra, and a second attempt can erase a small gap. This gap is large enough that one retry does not automatically erase it. Count the retries anyway.

Check the live Claude Sonnet 5.5 and GPT-6.1 Terra 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.

// Top-up

One balance.
Both models.

Test Claude Sonnet 5.5 and GPT-6.1 Terra 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.

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 Claude Sonnet 5.5? At GPTProto pricing, that’s roughly $240 saved per year vs official pricing — before bonus credits.
// Verdict

Which model fitsthe call you make most?

Use the model whose failure mode you can already describe.

Claude Sonnet 5.5claude-sonnet-5-5
Choose Sonnet 5.5 when the edit has to land
  • Use Sonnet for coding and tool steps you already know how to grade, especially when a wrong change costs more than the token gap.
  • Do not treat a single intelligence index as the decision. Public comparisons of this pair change with the effort setting, and the table shows only the configuration the harvest returned for both models.
  • Measure your own prompt. The latency figure on this page is an OpenRouter provider median, not a promise about your route.
GPT-6.1 Terragpt-6.1-terra
Choose GPT-6.1 Terra when the call repeats
  • Use Terra for visual checks, form filling, and other computer-use steps with a clear finish line, especially when the call repeats. The listed input rate is 56% below Claude Sonnet 5.5, and the output rate is lower by 56%.
  • A lower token rate is not a lower cost per completed task until you count retries. Run the same set you use for Sonnet.
  • Do not pick Terra, or reject it, on window size alone. Use the context row when both lengths are on the table.

Route by the step, not by the brand

Send the repeated visual and computer-use steps to the model with the lower GPTProto rate, and keep Sonnet on the coding steps your 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.

// Context and output

Show the windowonly when both sides have one.

OpenAI's launch note describes Terra as a million-token-class model. This table uses a harvested length only. A larger window is room for a long prompt, not a lower input rate.

// How to decide

Split visual workfrom the graded code change.

October 2026 writeups describe Terra as the cheaper model for screenshots, forms, and computer use, and Sonnet as the model that still leads the published intelligence index at the settings they show. Those indexes move with the effort setting. Build two sets from work you already run: a visual or computer-use set with a checkable result, and a bounded code change. Send the same instructions, tools, and grader to both. Record task success, total tokens, retries, and time to the last token. Keep cost per successful task next to the per-token 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.

// FAQ

Sonnet 5.5 vs GPT-6.1 Terra.Straight answers.

01Is GPT-6.1 Terra cheaper than Claude Sonnet 5.5 on GPTProto?+

On the live GPTProto rates, yes. Terra is $0.80 input and $4.00 output per million tokens, against $1.80 and $9.00 for Sonnet. That is 56% less on input and 56% less on output. The provider list rates in the catalog are $2.00/$10.00 for Claude Sonnet 5.5 and $1.00/$5.00 for GPT-6.1 Terra. Cache and retries can change a full bill.

02Which model is more intelligent?+

This page does not award that. October 2026 writeups, including Artificial Analysis, publish a higher intelligence index for Sonnet than for Terra at the settings they show, and those settings are not the same effort level. The intelligence row appears only when the OpenRouter harvest has a score for both models. Use it to shortlist, then test your own tasks.

03Which one responds faster?+

Read the latency and throughput rows, which are medians of OpenRouter provider p50s and carry the fetch date in the table note. They are not a GPTProto latency target. A short chat cares about latency. A long completion cares about throughput.

04Do they accept the same context window?+

Read the context row. It appears only when a length is available for both models. Treat a larger window as room for a long request, and test quality at the lengths you will send. Do not pick either model on window size alone.

05Are 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.

06Can I call both through GPTProto?+

Yes. Claude Sonnet 5.5 and GPT-6.1 Terra each have a model page with pricing, an API example, and a Playground. Switching models is a model-name change on the same balance.

// Social proof

See how others use GPTProto.

Creators and developers share the models and workflows they built with.

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.

// 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
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