---
title: Gemma 4 31B-it FP8 — Multimodal Reasoning LLM | ModelsLab
description: Deploy Gemma 4 31B-it FP8 for reasoning, coding, and multimodal tasks. 256K context, 140+ languages, Apache 2.0 license. Try now.
url: https://modelslab.com/gemma-4-31b-it-fp8
canonical: https://modelslab.com/gemma-4-31b-it-fp8
type: website
component: Seo/ModelPage
generated_at: 2026-07-01T04:03:19.400087Z
---

Available now on ModelsLab · Language Model

Gemma 4 31B-it FP8
Reasoning. Multimodal. Efficient.
---

[Try Gemma 4 31B-it FP8](/models/together_ai/google-gemma-4-31B-it) [API Documentation](https://docs.modelslab.com)

Dense Model. Frontier Performance.
---

256K Context

### Long-Context Reasoning

Process 256K tokens with hybrid attention for deep reasoning across large inputs.

Multimodal Native

### Text and Image Input

Handle variable aspect ratios and resolutions with integrated vision encoder support.

Function Calling

### Agentic Workflows

Native function calling and structured JSON output for autonomous task execution.

Examples

See what Gemma 4 31B-it FP8 can create
---

Copy any prompt below and try it yourself in the [playground](/models/together_ai/google-gemma-4-31B-it).

Code Generation

“Write a Python function that implements binary search with detailed comments explaining the algorithm and edge cases.”

Document Analysis

“Analyze this technical whitepaper image and extract the key findings, methodology, and conclusions in structured format.”

Multi-step Reasoning

“Solve this complex math problem step-by-step, showing all work and explaining the reasoning behind each calculation.”

Multilingual Support

“Translate this technical documentation from English to Spanish, French, and Mandarin while preserving formatting.”

For Developers

A few lines of code.
Reasoning. Three lines.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Gemma 4 31B-it FP8
---

[Read the docs ](https://docs.modelslab.com)

### What is Gemma 4 31B-it FP8?

Gemma 4 31B-it FP8 is Google DeepMind's 31-billion parameter multimodal model with FP8 quantization for efficient deployment. It supports text and image inputs, handles 256K token context, and delivers frontier-level performance on reasoning, coding, and multimodal tasks across 140+ languages.

### How does the Gemma 4 31B-it FP8 API pricing work?

Pricing is $0.20 per million input tokens and $0.50 per million output tokens. FP8 quantization reduces memory requirements while maintaining performance, making it cost-effective for production workloads.

### What are the key performance metrics?

Gemma 4 31B-it achieves 89.2% on AIME (reasoning), 80.0% on LiveCodeBench v6 (coding), 84.3% on GPQA Diamond (science), and 76.9% on MMMU Pro (multimodal). These benchmarks demonstrate frontier-level capability across diverse tasks.

### Can I use Gemma 4 31B-it FP8 for production?

Yes. Released April 2, 2026 under Apache 2.0 license, it's production-ready with native function calling, system prompt support, and configurable thinking mode for step-by-step reasoning in agentic workflows.

### What deployment options are available?

Deploy via serverless API endpoints, self-hosted on GPU infrastructure using vLLM, or through multiple cloud providers. FP8 quantization enables efficient deployment on consumer GPUs and workstations.

### Does Gemma 4 31B-it FP8 support video input?

Yes. The model processes video as sequences of frames up to 60 seconds at one frame per second, with configurable visual token budgets for flexible multimodal workflows.

Ready to create?
---

Start generating with Gemma 4 31B-it FP8 on ModelsLab.

[Try Gemma 4 31B-it FP8](/models/together_ai/google-gemma-4-31B-it) [API Documentation](https://docs.modelslab.com)

---

*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

---
*Generated by ModelsLab - 2026-07-01*