Best forAnthropic's Sonnet 5.5 for coding and agent work that has to stay fast without stepping up to the flagship rate.
Per 1M tokens · catalog rate
Input$2.00$1.80/M−10%
Output$10.00$9.00/M−10%
// Cross-vendor model comparisonView model page
Claude Sonnet 5.5vsGPT-6.1 Sol
Claude Sonnet 5.5 and GPT-6.1 Sol are the pair public writeups kept comparing through October 2026: two high-end models, released a day apart, with vendor list cards that are often quoted at the same input and output rate. On GPTProto the live text rates are not the same. This page reads those catalog rates. It does not copy a token price from OpenRouter, and it does not pick a quality winner the benchmarks do not agree on.
The short answer: start the cost check with GPT-6.1 Sol. On the live GPTProto rates its input is 11% lower and its output is 11% lower. The struck-through figures in the table are the provider list rates from the same catalog. Public comparisons of this pair split once the effort setting changes, so read the benchmark row only when both scores are present, then test the prompts you will send.
View model page
Best forOpenAI's GPT-6.1 Sol for the same class of coding and knowledge work when the GPTProto token rate is part of the choice.
Per 1M tokens · catalog rate
Input$2.00$1.60/M−20%
Output$10.00$8.00/M−20%
// Side by side
Claude Sonnet 5.5 vs GPT-6.1 SolAt 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 Sol
Provider
Claude
OpenAI
Model ID
claude-sonnet-5-5
gpt-6.1-sol
OpenRouter model
anthropic/claude-sonnet-5.5
openai/gpt-6.1-sol
Availability
97.89%
Last 7 days98.73%
Last 7 daysRelease date
September 28, 2026
September 29, 2026
Input
$1.80$2.00 official list
$1.60$2.00 official list
Output
$9.00$10.00 official list
$8.00$10.00 official list
You save
−10%vs the catalog list rate
−20%vs the catalog list rate
Cache read
$0.09$0.10 official list
$0.08$0.10 official list
Cache write
$2.25$2.50 official list
$2.00$2.50 official list
Latency (p50)
1.96 s
3.99 s
Throughput (p50)
90 tok/s
43 tok/s
Context window
1M tokens
1.05M tokens
Max output tokens
128K tokens
128K tokens
Accepts
TextImageFile
FileImageText
Returns
Text
Text
Where it earns its keep
Agent and tool steps where you want Sonnet's pace and can grade the result
Repeated coding and knowledge steps where the lower catalog rate still clears the bar
Best first test
A coding agent loop that should finish in fewer turns
A high-volume step with a checkable result
In the catalog since
Sep 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": "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-sol",
"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
The catalog rate,not the quoted list card.
On the live GPTProto text rates, GPT-6.1 Sol is $1.60 per million input tokens and $8.00 per million output tokens. Claude Sonnet 5.5 is $1.80 and $9.00. The provider list rates stored beside them are $2.00/$10.00 for GPT-6.1 Sol and $2.00/$10.00 for Claude Sonnet 5.5. GPT-6.1 Sol is 11% lower on input and 11% 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 $0.024 for GPT-6.1 Sol 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 the gap.
Vendor price cards can step up once a prompt passes a length threshold. This comparison does not apply a second tier. It shows the one text-to-text rate in the GPTProto catalog. Open the model page before you budget a prompt long enough to leave that rate.
Check the live Claude Sonnet 5.5 and GPT-6.1 Sol 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
$2,160
Monthly run rateOfficialGPTProtoSave
Input$400$320$80
Output$500$400$100
Per year$10,800$8,640$2,160
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
Claude Sonnet 5.5
GPT-6.1 Sol
Latency (p50)
1.96 s
3.99 s
Throughput (p50)
90 tok/s
43 tok/s
Providers measured
5
3
Supported parameters
include_reasoningmax_completion_tokensmax_tokensreasoningreasoning_effortresponse_formatstopstructured_outputs
include_reasoningmax_completion_tokensmax_tokensreasoningreasoning_effortresponse_formatseedstructured_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 Claude Sonnet 5.5 and GPT-6.1 Sol 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 GPT-6.1 Sol? At GPTProto pricing, that’s roughly $480 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
Claude Sonnet 5.5
GPT-6.1 Sol
Intelligence Index
54.2Claude Sonnet 5.5 (Max, Default Fallback)
54.5GPT-6.1 Sol (Max)
Artificial Analysis scores as carried by the OpenRouter harvest, fetched November 3, 2026.
// 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 agent loop is the work
- Use Sonnet for coding and tool steps you already know how to grade, especially when a shorter trace matters more than the last fraction of the token rate.
- 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 Solgpt-6.1-sol
Choose GPT-6.1 Sol when the rate is the constraint
- Use Sol for coding and knowledge steps with a clear finish line, especially when the call repeats. The listed input rate is 11% below Claude Sonnet 5.5, 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 Sonnet.
- The context windows are in the same million-token class. Do not pick either model on window size alone.
Route by the step, not by the brand
A practical split is to send the repeated, checkable steps to the model with the lower GPTProto rate, and to keep Sonnet on the agent steps where your grader already prefers it. 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
The windows are one class.The stream is a measurement.
GPT-6.1 Sol lists the larger context window: Claude Sonnet 5.5 at 1M tokens, GPT-6.1 Sol at 1.05M tokens. Both sit in the million-token class. The extra tokens are room for a long prompt, not a lower input rate, and a larger window does not mean the model still uses the material at the end of it.
Maximum output is 128K tokens for Claude Sonnet 5.5 and 128K tokens for GPT-6.1 Sol. Matching limits are not matching recall. Test the lengths you will actually send.
Claude Sonnet 5.5 median latency is 1.96 s. GPT-6.1 Sol is 3.99 s. A short chat should weight latency. These figures are medians of OpenRouter provider p50s, not a GPTProto service level.
Claude Sonnet 5.5 leads on throughput: Claude Sonnet 5.5 at 90 tok/s, GPT-6.1 Sol at 43 tok/s. A long agent trace should weight throughput more than the first token.
// How to decide
Grade the task,not the headline index.
October 2026 comparisons of this pair do not land on one winner. Some favor Sonnet on agent and tool steps, some favor Sol on knowledge and on cost per finished task, and the gap moves when the effort setting changes. Build the set from work you already run: a bounded code change, a long-context read, and a case that must reject a bad input. 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 Sol.Straight answers.
01Is GPT-6.1 Sol cheaper than Claude Sonnet 5.5 on GPTProto?
On the live GPTProto rates, yes. Sol is $1.60 input and $8.00 output per million tokens, against $1.80 and $9.00 for Sonnet. That is 11% less on input and 11% less on output. The provider list rates in the catalog are $2.00/$10.00 and $2.00/$10.00. Cache and a long-prompt tier, if the model page shows one, can change a full bill.
02Which model is more intelligent?
This page does not award that. October 2026 writeups split by benchmark and by effort setting. The intelligence row appears only when the OpenRouter harvest has a score for both models, and the cell note names the configuration. 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?
Not exactly. The table lists each model's published context and maximum output from the OpenRouter snapshot. Both are in the million-token class. Treat a larger window as room for a long request, and test quality at the lengths you will send.
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 Sol 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#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
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Compare models, learn API setup, and explore image and video workflows for real projects.
// Get started
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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
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