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Gemma 3 27B vs GPT-5.6 Terra

Compare Gemma 3 27B and GPT-5.6 Terra side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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GoogleGemma 3 27B
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Gemma 3 27B vs GPT-5.6 Terra: Overview

Gemma 3 27B

Gemma 3 27B, announced on March 12, 2025, is the largest open-weight model in Google DeepMind’s Gemma 3 family. With around 27 billion parameters, it is multimodal—accepting both text and images as input and producing text outputs. It supports a 128,000-token context window and typically generates up to ~8,192 tokens, enabling it to process multi-page documents, extended conversations, or large batches of images in a single prompt.

The model is instruction-tuned in its “-it” variants for chat, reasoning, and summarization use cases, and it supports structured outputs and function calling. It is multilingual, covering over 140 languages. Deployment is flexible: the full BF16 model requires ~46 GB of VRAM, but quantization-aware training (QAT) versions in 8-bit or 4-bit reduce the footprint significantly, allowing more accessible use outside large-scale clusters. While it delivers stronger reasoning and multimodal performance than smaller Gemma models, it remains lighter and more open than proprietary systems, making it well-suited for research, development, and fine-tuned applications.

GPT-5.6 Terra

GPT-5.6 Terra is the mid-tier reasoning model in OpenAI's GPT-5.6 family, which also includes the flagship Sol and the lightweight Luna. Introduced in a limited preview on June 26, 2026, and made broadly available on July 9, 2026, Terra accepts text and image input and produces text output, supporting vision, function calling, tool use, and agentic workflows. It is designed as a balanced option for everyday professional and production workloads — including coding assistance, document analysis, customer support, and multi-step agent tasks — where both output quality and cost efficiency matter. OpenAI positions Terra as delivering performance competitive with GPT-5.5 at approximately half the price, with a context window of around 1,050,000 tokens. On Terminal-Bench 2.1, Terra scores 84.3%, matching Claude Fable 5 on that benchmark. Under OpenAI's Preparedness Framework, Terra is rated High for cybersecurity and biological capabilities, meaning it demonstrates meaningful capability in those domains without reaching the Critical threshold.

GPT-5.6 introduces a new naming convention in which the generation number (5.6) is paired with a durable capability tier name (Sol, Terra, or Luna), allowing each tier to advance on its own schedule. Terra carries the API identifier gpt-5.6-terra and supports the same reasoning effort controls available across the family, including adjustable reasoning depth. The model includes prompt caching with explicit cache breakpoints and a 30-minute minimum cache life, with cache writes billed at 1.25x the uncached input rate and cache reads receiving a 90% discount. GPT-5.6 Terra is a proprietary, closed-weights model served through the OpenAI API, Codex, and ChatGPT.

Gemma 3 27B vs GPT-5.6 Terra Comparison Table

PropertyGemma 3 27BGPT-5.6 Terra
OrganizationGoogleOpenAI
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateMar 2025Jul 2026
Context Window128K1.1M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.080$2.50
Output $/1M$0.160$15.00
Vision Tasks
CaptioningDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
classificationDemo
Document Question Answering
object-detectionDemo
Model Features
Multimodal Vision
LLMs with Vision Capabilities
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
58.21%
Avg Response Time33.60s
Defect Detection
60%(9/15)
Document Understanding
77.8%(7/9)
Object Counting
10%(1/10)
Object Understanding
71.4%(10/14)
Spatial Understanding
63.2%(12/19)