2 of 59 · every text model Kyma prices per token · 59 measured

Gemini 3.7 Flash vs GPT-5.6 Luna

Two sources on this page and no others: what Kyma measured while serving these two models, and the specification Google and OpenAI publish for their own. Both run on one key, so switching is a one-line change.

Cheapest input

GPT-5.6 Luna

$0.14

per 1M input tokens, against $0.5063 for Gemini 3.7 Flash.

Fastest response

GPT-5.6 Luna

1.14 s

median, on one identical prompt sent to every model every six hours.

Availability

Too close to call

99.8 to 100.0%

the gap between them is smaller than these samples can resolve.

Where these models sit in the catalogue Kyma measures

Two numbers side by side tell you which is bigger and nothing about whether either is any good, so every panel puts these models against every text model Kyma prices per token, all 59 of them. That set is a stated rule and not a list, so there is no line-up to accuse anyone of choosing. Price is what Kyma charges today. Availability, throughput and latency are Kyma's own readings over 30 days, on the same method as /models. No benchmark scores, borrowed or invented.

kymaapi.com

Input price

lower is better
Price on Kymadollars per 1M tokens
OpenAIGPT-5.6 Luna
$0.14
GoogleGemini 3.7 Flash
$0.5063
field

Ticks above the rail are the models on this page; below it is every other model Kyma measures on this, 59 in all, on the same scale. The dashed rule is the field median, $1.009; the solid rule is its best, $0.0494, and 6 models sit beyond the axis.

Output price

lower is better
Price on Kymadollars per 1M tokens
OpenAIGPT-5.6 Luna
$0.8393
GoogleGemini 3.7 Flash
$2.531
field

Ticks above the rail are the models on this page; below it is every other model Kyma measures on this, 59 in all, on the same scale. The dashed rule is the field median, $3.528; the solid rule is its best, $0.2164, and 6 models sit beyond the axis.

Failed requests

lower is better
Measured by Kymaper 100 observations, last 30 days

Too close to call · 99.8 to 100.0%

GoogleGemini 3.7 Flash
0.00100.0% up
OpenAIGPT-5.6 Luna
0.2199.8% up
field

Ticks above the rail are the models on this page; below it is every other model Kyma measures on this, 59 in all, on the same scale. The dashed rule is the field median, 1.49; the solid rule is its best, 0.00, and 6 models sit beyond the axis.

The gap between them is under 5.2 points, which is one failed request in the thinnest sample here. So these rows are in page order and nothing is marked: the ordering would be the claim, and it is the claim this sample cannot support.

Throughput

higher is better
Measured by Kymamedian tokens per second
GoogleGemini 3.7 Flash
118 tok/s
OpenAIGPT-5.6 Luna
41 tok/s
field

Ticks above the rail are the models on this page; below it is every other model Kyma measures on this, 59 in all, on the same scale. The dashed rule is the field median, 41; the solid rule is its best, 321, and 4 models sit beyond the axis.

Latency

lower is better
Measured by Kymamedian seconds to a full response
OpenAIGPT-5.6 Luna
1.14 s
GoogleGemini 3.7 Flash
2.45 s
field

Ticks above the rail are the models on this page; below it is every other model Kyma measures on this, 59 in all, on the same scale. The dashed rule is the field median, 2.25s; the solid rule is its best, 0.81s, and 6 models sit beyond the axis.

Rank in the field

Out of every text model Kyma prices per token, 59 of which Kyma has measured. Where these models lose is stated in the same words as where they win.

GoogleGemini 3.7 Flash

21st of 59 on cheapest input · 1st of 59 on most available · 5th of 59 on fastest tokens

OpenAIGPT-5.6 Luna

9th of 59 on cheapest input · 9th of 59 on most available · 30th of 59 on fastest tokens

Panels where these models come off badly are in this grid on the same terms as the ones where they do well. The ordering inside each panel is the result, not a preference.

The facts a chart cannot draw

A conditional rate, a date, a claim with three answers and two different refusals. Still grouped by who said them.

FactGoogleGemini 3.7 Flash

Google

OpenAIGPT-5.6 Luna

OpenAI

Price on Kyma

What a request costs today. The rates themselves are in the panels above, against the whole price sheet. These two are the parts of a price a bar cannot carry.

Cached input

per 1M tokens, on repeated prefixes

$0.05061
90% off input
$0.014
90% off input
Best

On offer

a temporary rate, and the day it ends

50% off

until Aug 21, then $1.013 in / $5.063 out

48% off

until Aug 21, then $0.27 in / $1.62 out

Measured by Kyma

Kyma's own numbers, on Kyma's own traffic. Availability, throughput and latency are drawn against the field above; this is the one measured fact with no scale to sit on. Same method, same figures as /models.

Below release precision

narrower than the creator shipped

Not established
Not established
Published by the creator

The specification each creator publishes for its own model, read straight from the catalogue Kyma serves from. Nothing in this block is a Kyma opinion.

Creator

Google
OpenAI

Context window

tokens in one request

1.05M
1.05M

Max output

hard ceiling on one response

66K
128KBest

Accepts

Text, image, video, file, audio
Text, image, file

Tool calling

Yes
Yes

Reasoning

Yes
Yes

Vision input

Yes
Yes

Weights

Closed
Closed

“Best” marks the winning cell on exact published facts only. Measured rows carry sampling error, so this page does not rank them by their last digit.

Two sources, and nothing borrowed

On this page

Measured by Kyma

Uptime, throughput, latency and the precision the routes behind each model report, from Kyma's own traffic. Ours to publish, and it refreshes itself. Every one of them is drawn against the whole catalogue, because a figure with nothing to compare it to is not evidence.

Published by the creator

Context window, maximum output, accepted inputs, and tool, reasoning and vision support. Each creator's own specification for its own model, as is the precision each creator released its model at, which is the only thing that makes a serving format count as below it.

Taken off it

Third-party benchmark scores

We do not run those scoreboards. One can go stale without telling anyone, and it takes the page's credibility with it.

A Kyma quality score

We do not have one. Inventing a number to fill the gap would be worth less than the scores that were removed.

So this page will not tell you which model is smarter. It tells you which is cheaper, which is faster, which stays up, where each one sits against every other model we sell, and whether it is served below the precision its creator released it at. For the quality question, run them both on your own prompts. One key, one line changed, and the answer is about your work rather than someone else's test set.

Switch with one line

# One key, one endpoint. Only the model string changes.
client = OpenAI(base_url="https://kymaapi.com/v1", api_key="YOUR_API_KEY")

client.chat.completions.create(model="gemini-3.7-flash", messages=[...])
client.chat.completions.create(model="gpt-5.6-luna", messages=[...])

Questions

Which of Gemini 3.7 Flash and GPT-5.6 Luna is cheapest?

On input tokens today, GPT-5.6 Luna at $0.14 per 1M. Gemini 3.7 Flash is $0.5063. The panels above put both of those against every model Kyma prices, so you can see whether either is actually cheap.

Can I switch between Gemini 3.7 Flash and GPT-5.6 Luna without changing my code?

Yes. All of them are served through the same OpenAI-compatible Kyma endpoint (https://kymaapi.com/v1) on one API key and one balance. Switching is a one-line change to the model field: `gemini-3.7-flash`, `gpt-5.6-luna`.

Which has the largest context window?

Neither is larger in any way you would notice: all of them take about 1.05M tokens in a single request, so context is not the deciding factor here.

Where do these numbers come from?

Two places and no others. Uptime, throughput, latency and the precision the routes report are measured by Kyma on its own traffic over the last 30 days, across all 59 models it prices per token, 59 of which are measured. Context window, maximum output, accepted inputs, tool, reasoning and vision support are the specification each creator publishes for its own model, cited on the model's own page, and so is the precision each creator released its model at. The "below release precision" row is the two put together: a serving format only counts as below the release once you know what the release was. This page carries no third-party benchmark scores, so it cannot rank these models on quality, and it does not pretend to.

Is there a discount running on any of these?

Gemini 3.7 Flash is 50% off until Aug 21, at $0.5063 per 1M input instead of $1.013. GPT-5.6 Luna is 48% off until Aug 21, at $0.14 per 1M input instead of $0.27. The rate is honoured through that date, then returns to list.

Every model above runs on one key and one balance. $0.50 of free credit on signup, no card.Get API key