reasoningunverifiedHand-written lesson

Google

Gemini 3.8 Flash

google/gemini-3.8-flash

Google's most capable Flash model, with gains over 3.7 Flash in software engineering, agentic tasks, and multi-step reasoning. Takes text, images, video, audio, and files.

RoleThe cheap multimodal worker

$0.825

In / M

$4.13

Out / M

1.0M

Context

AA intelligence index
30.8
Inputs
text, image, video, file, audio
Outputs
text
Tools
Listed
Structured output
Listed
Reasoning
Listed
Weights
Not verified
Listed
Sep 2, 2026
Live from the OpenRouter listing ↗

01 · What it's good at

Use it for this.

Three jobs this model is built for, and the ones to give to something else.

01

Cheap multimodal: audio, video, images, and PDFs in one call

02

Agent steps and coding at Flash pricing

03

Long files thanks to a 1M-token context

Skip it for

  • Your hardest agent turns. Gemini 4 Argon is the flagship

02 · Example tasks

What you'd actually send it.

Real inputs, not a benchmark. Paste one into the snippet below to try it.

You send

From this 30-minute meeting recording, list decisions, owners, and due dates as a table.

Why this model

Audio in, structured text out, at a Flash price.

03 · Your stack

Where it sits: Do the volume.

The worker for media-heavy pipelines: per upload, per recording, per screenshot. Escalate the unclear cases to Argon.

04 · Wire it up

One request. Paste and run.

Uses OpenRouter, so one key works for every model on this site. Set OPENROUTER_API_KEY and swap the prompt for one of the tasks above.

// OpenRouter speaks the OpenAI Chat Completions format.
const res = await fetch("https://openrouter.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "google/gemini-3.8-flash",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Read this receipt and return merchant, date, total, and currency."
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://example.com/receipt.jpg"
            }
          }
        ]
      }
    ],
    "reasoning": {
      "effort": "low"
    }
  }),
});
const data = await res.json();
console.log(data.choices[0].message.content);

05 · Watch out for

Gotchas.

  • Reasoning is mandatory on the listing (low, medium, high). Use low for extraction.

  • Batch pricing is listed separately for offline jobs.

Sources

Lessons are written from each model's listing and the linked docs. We don't publish our own benchmark numbers; the index above is Artificial Analysis, as shown on OpenRouter.

Keep learning

Same board, other models.