Summarize project material
Turn supplied meeting notes, design documents and requirements into a brief that preserves decisions and unresolved questions.
Gemma 4 26B A4B is part of Google’s open-weight model family. On Blade, use it for long-context text generation, grounded summaries and assistants built around your own content.
€5 in free credits for every new customer.
Try Gemma 4 26B A4BFrom €0.0398 per million input tokens. View the pricing details.
Practical starting points for Gemma 4 26B A4B. Choose one task, define the expected output and measure the result on your own examples.
Turn supplied meeting notes, design documents and requirements into a brief that preserves decisions and unresolved questions.
Retrieve relevant documents in your application, then ask the model to answer from those excerpts with source references.
Produce first drafts of release notes or product explanations. Validate required fields and review technical claims before publication.
Gemma 4 26B A4B pricing
These are catalogue “From” rates in EUR. Dynamic pricing can change the applicable price. Confirm your model, request route and active billing unit before estimating a workload.
See Gemma 4 26B A4B on the rate card ↗A concrete example
10,000 input tokens + 2,000 output tokens = €0.000696 at the displayed starting rates.
Illustration only; excludes retries, other models and paid tools. Catalogue updated 2026-10-22.
Check current rates ↗API integration
Use the Blade model ID gemma-4-26b-a4b and keep your API key in your backend environment. Verify account access and supported parameters before connecting production traffic.
pip install openai and set BLADE_API_KEY.import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.models.blade.sh/v1",
api_key=os.environ["BLADE_API_KEY"],
timeout=120.0,
)
reply = client.chat.completions.create(
model="gemma-4-26b-a4b",
messages=[{
"role": "user",
"content": "Create a release-note template with sections for changes, migration steps and known issues.",
}],
max_tokens=4096,
)
print(reply.choices[0].message.content)Install openai and set BLADE_API_KEY. This sends a billed request. Check supported parameters and handle timeouts, rate limits and incomplete responses.
Connect a skill or API runner that sends a focused task to gemma-4-26b-a4b. Your main assistant keeps the project context, reviews the proposal and runs the checks.
Define the task and select the files.
Propose code through Blade’s API.
Review the diff. Run the tests.
A configured integration is required. Your assistant retains its main model; delegated Blade requests are billed separately. Evaluate the result on your task before expanding the workflow.
Set up coding delegation ↗Gemma 4 26B A4B is part of Google’s open-weight model family. On Blade, use it for long-context text generation, grounded summaries and assistants built around your own content. Its Blade model ID is gemma-4-26b-a4b.
Input / 1M tokens: from €0.0398. Output / 1M tokens: from €0.149. These are dynamic catalogue starting rates as of 2026-10-22, not fixed prices for every request. Check the console for current rates.
Google documents a mixture-of-experts architecture with 26B total and 4B active parameters. Those architecture figures do not define Blade latency, multimodal support or request limits.
Yes, through a configured delegation skill or API runner. Your primary assistant sends a task to Blade and reviews the result. It keeps its own model, and Blade requests are billed separately. Follow the delegation guide.
Model reference: Publisher model reference ↗. Hosted configuration and pricing: Blade catalogue, 2026-10-22.
Choose by task, input type and billing unit. Browse all models ↗
Need to configure your own worker? Read the Gemma 4 26B A4B GPU deployment guide ↗