Gemini 3 Flash vs GPT-6.1 Terra
GPT-6.1 Terra and Gemini 3 Flash score 85.8% vs 65.7% averaged across five Vision Evals tasks (#2 and #29 of 65 models), so GPT-6.1 Terra leads overall.
- GPT-6.1 Terra wins all 5 tasks, with its widest lead on object detection (84.7% vs 38.6%).
- Gemini 3 Flash is cheaper: $0.0024 vs $0.0033 overall average cost per sample.
- Gemini 3 Flash is faster: 5.8s vs 10.1s per sample.
Roboflow Vision Evals. Full breakdown below.
Compare Gemini 3 Flash 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.
Gemini 3 Flash vs GPT-6.1 Terra on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Gemini 3 Flash vs GPT-6.1 Terra Comparison Table
Evals updated October 26, 2026Pricing updated October 27, 2026
| Property | Gemini 3 Flash | GPT-6.1 Terra |
|---|---|---|
| Organization | OpenAI | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Dec 2025 | Oct 2026 |
| Context Window | 1.0M | 1.1M |
| Parameters | Unknown | undisclosed |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.500 | $1.00 |
| Output $/1M | $3.00 | $5.00 |
| Vision Tasks | ||
| Captioning | Demo | Supported |
| Classification | Demo | Supported |
| Object Detection | Demo | Supported |
| OCR | Demo | Supported |
| Visual Question Answering | Demo | Supported |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 65.7% | 85.8% |
| Avg cost / sample | $0.0024 | $0.0033 |
| Avg speed / sample | 5.83s | 10.05s |
| By task | ||
| Object Detection (low) | 38.6% | 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) | 67.6% | 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) | 93.8% | 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) | 63.9% | 81.9% |
| by category |
|
|
| OCR (high) | 73.1% | 84.4% |
| by category |
|
|
| Reasoning (low) | 64.9% | 85.4% ±1.7, Mean of 3 runs, range 83.4 to 86.8 |
| Reasoning (high) | 74.2% | 87.0% ±1.3, Mean of 3 runs, range 85.4 to 88.1 |
Gemini 3 Flash vs GPT-6.1 Terra: Overview
Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.
The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.
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.
Frequently Asked Questions
On Roboflow's Vision Evals, GPT-6.1 Terra performed better. It scores higher on all five vision tasks and averages 85.8% (#2 of 65) against 65.7% (#29 of 65) for Gemini 3 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark at low effort, GPT-6.1 Terra leads with 84.7% against 38.6%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0024 per sample against $0.0033. Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 per 1M output; GPT-6.1 Terra is priced at $1.00 per 1M input tokens and $5.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3 Flash is faster. Across Roboflow's Vision Evals it averaged 5.8s per inference against 10.1s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.