Gemma 3 4B vs GPT-6.1 Terra
GPT-6.1 Terra: 85.8% average across five Vision Evals tasks (#2 of 65 models). We have not run Gemma 3 4B through Roboflow's Vision Evals, so there is no head-to-head score.
Compare Gemma 3 4B vs GPT-6.1 Terra live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Gemma 3 4B vs GPT-6.1 Terra Comparison Table
Evals updated October 26, 2026Pricing updated October 27, 2026
| Property | Gemma 3 4B | GPT-6.1 Terra |
|---|---|---|
| Organization | OpenAI | |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Mar 2025 | Oct 2026 |
| Context Window | 128K | 1.1M |
| Parameters | 4B | undisclosed |
| License | Custom | Proprietary |
| Commercial use | See license terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.050 | $1.00 |
| Output $/1M | $0.100 | $5.00 |
| Vision Tasks | ||
| Captioning | Demo | Supported |
| OCR | Demo | Supported |
| Visual Question Answering | Demo | Supported |
| Object Detection | Not listed | Supported |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 85.8% |
| Avg cost / sample | – | $0.0033 |
| Avg speed / sample | – | 10.05s |
| By task | ||
| Object Detection (low) | – | 84.7% ±0.1, Mean of 3 runs, range 84.7 to 84.8 |
| Object Detection (high) | – | 84.7% ±0.4, Mean of 3 runs, range 84.2 to 84.9 |
| Counting (low) | – | 80.2% ±2.0, Mean of 3 runs, range 78.4 to 82.4 |
| Counting (high) | – | 84.2% ±3.4, Mean of 3 runs, range 81.1 to 87.8 |
| Identification (low) | – | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| Identification (high) | – | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | – | 81.9% |
| by category |
| |
| OCR (high) | – | 84.4% |
| by category |
| |
| Reasoning (low) | – | 85.4% ±1.7, Mean of 3 runs, range 83.4 to 86.8 |
| Reasoning (high) | – | 87.0% ±1.3, Mean of 3 runs, range 85.4 to 88.1 |
Gemma 3 4B vs GPT-6.1 Terra: Overview
Gemma 3 4B, released on March 12, 2025, is the mid-sized member of Google DeepMind’s open-weight Gemma 3 family. With about 4 billion parameters, it is multimodal—supporting text and image inputs and generating text outputs. Like the larger Gemma 3 models, it features a 128,000-token input context window with an output capacity of ~8,192 tokens, enabling it to handle long documents and mixed text–image reasoning tasks.
The 4B variant is designed as a balance between efficiency and capability: it offers multilingual support across 140+ languages, strong summarization and reasoning performance, and compatibility with moderate hardware. Inference can run with ~6.4 GB VRAM in BF16, or significantly less in quantized 8-bit (~4.4 GB) or 4-bit (~3.4 GB) modes, making it accessible to developers outside large-scale infrastructure. While it lags behind the 12B and 27B versions on the most complex reasoning and multimodal benchmarks, its lower compute footprint makes it ideal for research, prototyping, and practical deployment where efficiency matters.
GPT-6.1 Terra is an OpenAI model released on October 26, 2026 for visual reasoning, computer use and writing. It accepts text and image inputs and produces text, with a 1,050,000-token context window and up to 128,000 output tokens. OpenAI lists applications including matching product photographs to catalog entries, interpreting technical drawings and operating application screens.
The API exposes six reasoning effort settings: none, low, medium, high, xhigh and max. Medium is the default. The model supports structured outputs and tool calling through the Responses API. Vision Evals reports its Low and High results for text understanding, counting, identification, reasoning and object detection, using native OpenAI API inference. Terra is a proprietary model; its weights are not released.