Gemini 3.8 Flash API: Pricing, Thinking Costs, and Usage Guide

Released by Google on September 2, 2026, Gemini 3.8 Flash is the third Flash release in six weeks: 3.6 → 3.7 → 3.8. According to Google, the model is built on 3.7 Flash. It accepts text, image, audio, video, and PDF input, and ships with a 1M-token context window and 64K output. Google says 3.8 beats 3.7 Flash on every benchmark row it published. The less-discussed part of the announcement matters just as much: the model deliberately thinks more, which means it can spend more output tokens on the same task.

This guide answers three questions. All three Flash versions are active in the Onysoft catalog at the same price, so which one should you pick? How does extra thinking show up on your bill, and how do you cap it with max_tokens? And next to Gemini 3.1 Pro and DeepSeek V4.1 Flash, which workload belongs where? At the end you will find step-by-step access from Turkey, paid in lira, plus Python, curl, and streaming examples.

What Gemini 3.8 Flash Brings

The spec sheet from the Onysoft catalog: API ID google/gemini-3.8-flash, a 1,048,576-token input context, and a 65,536-token (64K) maximum output. The headline points from Google's announcement:

• Multimodal input: text, image, audio, video, and PDF in a single model. An invoice image, a contract PDF, or a meeting recording can go into the same request without splitting the work across separate tools.
• Built on 3.7 Flash: Google says 3.8 beats 3.7 Flash on every benchmark row it published, and outperforms Claude Opus 5 on three benchmarks. These are the provider's own published results; we recommend validating them on your own workload.
• Deliberately more thinking: part of the quality gain comes from the model spending more thinking tokens before it answers. We cover the cost side of that in its own section below.

Google also announced a restricted-access "Cyber" sibling model. That variant is not in the Onysoft catalog. Everything in this article, including every example, applies to the standard google/gemini-3.8-flash.

The release cadence deserves a note too: three versions in six weeks. At that pace, model selection stops being a one-time decision and becomes a regular testing routine. The sections below help you set that routine up.

3.6, 3.7, or 3.8? Three Flash Models at the Same Price

All three Flash versions are active in the Onysoft catalog and carry the same per-token sale price. For comparison, we added Gemini 3.1 Pro, the upper tier of the Gemini family, and DeepSeek V4.1 Flash, the economical alternative:

Model	API ID	Context	Max output	1M input	1M output	1M input (TRY)	1M output (TRY)
Gemini 3.8 Flash	google/gemini-3.8-flash	1,048,576	65,536	$1.125	$5.625	54.56 TL	272.78 TL
Gemini 3.7 Flash	google/gemini-3.7-flash	1,048,576	65,536	$1.125	$5.625	54.56 TL	272.78 TL
Gemini 3.6 Flash	google/gemini-3.6-flash	1,048,576	65,536	$1.125	$5.625	54.56 TL	272.78 TL
Gemini 3.1 Pro Preview	google/gemini-3.1-pro-preview	1,048,576	65,536	$3	$18	145.48 TL	872.89 TL
DeepSeek V4.1 Flash	deepseek/deepseek-v4.1-flash	1,048,576	384,000	$0.225	$0.90	10.91 TL	43.64 TL

Prices are Onysoft sale prices as of September 13, 2026; see /models for current pricing. TRY equivalents use the CBRT (TCMB) rate of September 11, 2026 (1 USD = 48.4941 TL); measured on September 13, 2026.

When the per-token price is identical, the choice comes down to quality and total token consumption:

• Starting a new project: begin with google/gemini-3.8-flash. Based on Google's published results, it is the newest Flash and beats its predecessor on every benchmark row.
• Running a validated production pipeline on 3.6 or 3.7 Flash: do not switch right away. Run the same test set against 3.8 and measure the quality difference together with output tokens per request. The price list is the same, but cost per task can differ.
• Short, formulaic, high-volume tasks (tagging, simple classification) often gain nothing from extra thinking. Staying on your current version or moving to a cheaper model can make sense.

Pin the model ID explicitly in your code. That way, when Google ships another Flash, your production behavior does not change until you have tested it. For the broader Gemini picture, see our Gemini API in Turkey guide and the Gemini catalog.

More Thinking, More Output Tokens: How to Keep Costs in Check

Onysoft bills every request on two lines: input tokens × input price and output tokens × output price. Thinking tokens the model generates before answering count as output tokens. On 3.8 Flash the output price is 5× the input price ($5.625 vs. $1.125), so extra thinking hits your bill mostly on the output side.

A rough calculation shows the effect (a hypothetical example, not a measurement). Take 1,000 requests with 2,000 input and 500 output tokens each: at 3.8 Flash pricing that comes to $5.0625, made up of $2.25 input + $2.8125 output, or about 245.50 TL. If the same job produces 1,000 output tokens per request instead, the total becomes $7.875: $2.25 input + $5.625 output, or about 381.89 TL. In this scenario, doubling output tokens raises the bill by roughly 56%. The real difference depends on your workload, so measure it with your own data rather than assuming.

Four practical controls:

1. Cap it with max_tokens. This limits the output tokens a single request can generate and keeps unexpectedly long responses off your bill. Note that thinking tokens draw from the same budget, so a cap that is too low can cut off the visible answer. If the response's finish_reason is length, raise the cap.
2. Measure before you switch. Send 50–100 representative requests to both 3.7 and 3.8 Flash and compare the usage.completion_tokens values in the responses.
3. Ask for short answers. Limiting the visible answer length in the prompt ("at most three bullet points") trims the part of output tokens you can control.
4. Route work to the right model. Send simple tasks where thinking adds nothing to more economical models (see the decision matrix below).

For per-key limits and request-level spend visibility, read our AI API cost control guide.

Decision Matrix: 3.8 Flash, 3.1 Pro, or DeepSeek V4.1 Flash?

Flash sits between two reasonable alternatives. At Onysoft sale prices, Gemini 3.1 Pro Preview costs about 2.67× more on input and 3.2× more on output than 3.8 Flash; it is for the cases Flash cannot handle. DeepSeek V4.1 Flash is 5× cheaper on input and 6.25× cheaper on output. According to DeepSeek, V4.1 Flash became generally available on September 10, 2026 as a 552B-parameter multimodal MoE model with native visual understanding and MIT-licensed weights. The catalog lists it with a 384,000-token output ceiling.

Workload	Recommended model	Rationale and caveats
Analysis involving invoices, contract PDFs, meeting recordings, or short videos	google/gemini-3.8-flash	According to Google, it accepts text, image, audio, video, and PDF input in one model.
High-volume, text-only work: classification, tagging, short summaries	deepseek/deepseek-v4.1-flash	5× cheaper on input, 6.25× cheaper on output. Validate quality on your own sample.
Image-only, budget-first tasks (product photo tagging, etc.)	deepseek/deepseek-v4.1-flash	DeepSeek announces native visual understanding; test image input through Onysoft with your own samples before going to production. If you also need audio, video, or PDF, go with 3.8 Flash.
An existing pipeline validated on 3.6 or 3.7 Flash	Current version (test 3.8 in parallel)	Same per-token price, but output tokens may rise. Do not switch without measuring cost per task.
Long, complex reasoning and critical decisions where Flash falls short	google/gemini-3.1-pro-preview	More expensive; reserve it for cases escalated from Flash. The ID carries a "preview" label.
Single responses longer than 64K tokens (long reports, large code generation)	deepseek/deepseek-v4.1-flash	Catalog output ceiling is 384,000 tokens; Gemini Flash and 3.1 Pro cap at 65,536.
You would rather not pick a model per request	onysoft/auto	OnyRouter picks the model for you; routing is free and the selected model's price applies.

When not to use 3.8 Flash

• The task is short and formulaic, and extra thinking does not improve quality: you pay for additional output tokens with no gain.
• Budget is the only criterion and the work is text-only: DeepSeek V4.1 Flash is far more economical.
• You need more than 64K tokens in a single response: Flash's output ceiling does not allow it.
• You are looking for restricted, security-specific capabilities: the Cyber variant is not in the Onysoft catalog.

For the upper tier, see our Gemini 3.1 Pro API guide; for the economical side, see the DeepSeek API in Turkey guide and the DeepSeek catalog.

Accessing the Gemini 3.8 Flash API from Turkey in Lira, Step by Step

You do not need a separate contract with Google, a foreign card, or a VPN to use Gemini 3.8 Flash. Through Onysoft AI Gateway you can get started in a few minutes:

1. Create a free account. Corporate e-invoicing and KVKK (Turkish data protection law) compliance are standard.
2. Generate your sk-ony- prefixed API key in the dashboard.
3. Top up a lira balance. Usage is deducted pay-as-you-go at the CBRT exchange rate; there is no subscription.
4. Before writing code, try google/gemini-3.8-flash and google/gemini-3.7-flash side by side with the same prompt in the Playground. It is the fastest way to see the quality difference and response length firsthand.
5. In your application, set base_url to https://api.onysoft.com/v1 and pass the model name.

If you already have an OpenAI integration, switching is a two-line change: base_url and model. The same key reaches all 754+ models in the catalog: one balance, one invoice, one API. For the bigger picture, see our AI API guide. If you get stuck, 24/7 support in Turkish is available.

Your First Request with Python, curl, and Streaming

The Onysoft endpoint follows the OpenAI schema, so you work with the official openai Python package. Streaming responses arrive as raw OpenAI chunks and are directly compatible with the SDK. This is the most practical way to start:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.onysoft.com/v1",
    api_key="sk-ony-YOUR_KEY",
)

stream = client.chat.completions.create(
    model="google/gemini-3.8-flash",
    messages=[{"role": "user", "content": "Categorize this support ticket and summarize it in one sentence: My order has not shipped in three days."}],
    max_tokens=2048,
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Image input: send content as parts, following the OpenAI schema. You can combine text and an image in the same message:

import base64

with open("invoice.png", "rb") as f:
    b64 = base64.b64encode(f.read()).decode()

stream = client.chat.completions.create(
    model="google/gemini-3.8-flash",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Extract the vendor name, date, and total amount from this invoice."},
            {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64}"}},
        ],
    }],
    max_tokens=1024,
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Google has also announced audio, video, and PDF input. Before putting those types into a production pipeline, send a small test request with your own files; see the API documentation for request format details.

Non-streaming requests: Onysoft returns non-stream responses in a success/data envelope, with the content at data.choices[0].message.content. With the Python SDK you can read the raw body and also see token usage for cost measurement:

raw = client.chat.completions.with_raw_response.create(
    model="google/gemini-3.8-flash",
    messages=[{"role": "user", "content": "Explain this contract clause in plain English: ..."}],
    max_tokens=2048,
)
data = raw.http_response.json()["data"]
print(data["choices"][0]["message"]["content"])
print("finish_reason:", data["choices"][0].get("finish_reason"))
print("output tokens:", data["usage"]["completion_tokens"])

The same request with curl. The content sits under the data field in the response; for streaming, just add "stream": true to the body:

curl https://api.onysoft.com/v1/chat/completions \
  -H "Authorization: Bearer sk-ony-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-3.8-flash",
    "max_tokens": 2048,
    "messages": [{"role": "user", "content": "Explain this contract clause in plain English."}]
  }'

OnyRouter tip: if you would rather not choose a model for every request, set model to onysoft/auto. OnyRouter picks a suitable model for the request; routing is free, you are billed at the selected model's price, and the model field in the response shows which model was used. For multimodal input such as images or PDFs, or for a pipeline whose costs you have measured, pinning google/gemini-3.8-flash is more predictable. See our OnyRouter guide for details.