Gemma 3 27B IT is Google DeepMind's most capable open model — 27 billion parameters with vision understanding, multilingual support, and Google's training quality, all under Apache 2.0.
Gemma 3 27B is an AI model released March 2025 by Google, a leading organization in large language model research. Google's Gemma-3 27B — excellent coding assistant with strong reasoning, multilingual support, and 128k context. With 27B and a 128K tokens context window, Gemma 3 27B is designed to excel across a range of demanding tasks — from software engineering and mathematical problem-solving to multilingual content generation and long-document analysis.
Gemma 3 27B uses a dense transformer architecture with 27B of parameters, all of which are active for every input token. Dense architectures provide predictable, consistent behavior across diverse task types — there are no "cold" experts to warm up, and quality is uniform across prompts. Google's training pipeline combined large-scale pretraining on Google pretraining with multimodal training with supervised fine-tuning and alignment techniques (RLHF or DPO), producing Gemma 3 27B's characteristic balance of capability, helpfulness, and safety.
As of 2026-10-16, Gemma 3 27B by Google demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 78.4%. For software engineering tasks, Gemma 3 27B scores 74.3% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, Gemma 3 27B records 73.2% on MGSM. Across all 4 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Gemma 3 27B — at 27B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
The primary strengths of Gemma 3 27B are: Google's open multimodal model at accessible 27B scale; Strong visual document understanding with 128K context; Broad language support; Gemma Terms allow broad commercial deployment. These make it particularly well-suited for Multimodal enterprise apps at deployable scale, Visual document analysis: receipts, invoices, charts, Multilingual applications. Users working on complex, multi-step problems benefit most from Gemma 3 27B's ability to maintain coherence across long inputs and produce structured, verifiable outputs.
Like all current AI systems, Gemma 3 27B has limitations: Superseded by Gemma 4 (June 2025); 27B requires 24GB+ VRAM. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. Google continues to improve Gemma 3 27B through ongoing research.
Gemma 3 27B is available on LITHOVEX AI with a free account. Unlike direct API access — which requires billing setup, API key management, and per-token charges — LITHOVEX AI provides a seamless browser interface with no setup required, making Gemma 3 27B accessible to students, researchers, developers, and early-stage teams globally.
As of 2026-10-16, Gemma 3 27B by Google demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 78.4%. For software engineering tasks, Gemma 3 27B scores 74.3% on HumanEval, which tests ability to write correct functions from docstrings. In mathematical reasoning, Gemma 3 27B records 73.2% on MGSM. Across all 4 benchmarks tracked, the model shows consistent capability in its primary task domains. These scores place Gemma 3 27B — at 27B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.
Dense transformer, 27B parameters, multimodal (text + images)
The training pipeline for Gemma 3 27B involves multiple stages: large-scale pretraining on Google pretraining with multimodal training to develop broad world knowledge, followed by supervised fine-tuning on instruction-response pairs, and alignment techniques such as RLHF or DPO. Each stage refines the model's helpfulness, accuracy, and safety. Google's research team — based in United States — has optimized Gemma 3 27B for the specific capability profile described above.
Inference efficiency: Gemma 3 27B at 27B is designed to deliver quality outputs at practical serving speeds. Its 128K tokens context window enables processing entire documents, multi-file codebases, and extended conversation histories — particularly valuable for contract review, technical documentation analysis, and codebase-level AI assistance.
Getting started with Gemma 3 27B on LITHOVEX AI takes under two minutes. Follow these steps:
For best results with Gemma 3 27B: provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions.
Enterprise multimodal AI with vision understanding
Document intelligence with image and text processing
Advanced content generation leveraging Google training quality
European organizations requiring GDPR-friendly open-weight AI
Developer tools requiring reliable, well-documented open models
Google DeepMind is Alphabet's AI research organization, formed through the merger of Google Brain and DeepMind in 2023. Google published the original "Attention Is All You Need" paper in 2017, which introduced the transformer architecture underlying virtually every modern language model. The Gemma model family represents Google's open-weight contributions — models that bring Google research quality to open-access deployment. Gemma 3 and Gemma 4 models support multimodal inputs including images and long-document processing. Google's computational infrastructure and proprietary TPUs give it advantages in training efficiency that few organizations can match.
Funding: Part of Alphabet Inc. ($1.9T+ market cap)
Founded: 1998, headquartered in United States.
Gemma 3 27B by Google competes in a field with several strong alternatives. Below is a detailed side-by-side comparison against commonly listed alternatives, using benchmark data and capability profiles in the catalog.
Both Gemma 3 27B and the models above are available free on LITHOVEX AI — test them side by side on your real tasks before committing to a subscription with any provider.
Gemma 3 27B is released under Gemma Terms of Use, which means you can download and run it on your own hardware. Below are the quickest ways to get started.
LITHOVEX AI runs Gemma 3 27B on cloud infrastructure, so you can use it instantly in your browser without downloading anything, configuring drivers, or managing VRAM. Create a free account and start in under 60 seconds.
Gemma 3 27B IT represents Google's commitment to the open-source AI ecosystem globally. Its vision capabilities, Apache 2.0 license, and Google research backing make it a trusted choice for enterprise AI deployments in Europe, North America, and Asia, particularly for organizations that value data sovereignty.
Gemma 3 27B by Google has the following version history and notable updates:
For the complete changelog and latest release notes, visit the official Google model page.