Gemini 3.1 Pro vs Llama 4 Maverick
Gemini 3.1 Pro: 76.8% average across five Vision Evals tasks (#14 of 65 models). We have not run Llama 4 Maverick through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
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Gemini 3.1 Pro vs Llama 4 Maverick Comparison Table
Evals updated October 26, 2026Pricing updated November 4, 2026
| Property | Gemini 3.1 Pro | Llama 4 Maverick |
|---|---|---|
| Organization | Meta | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Apr 2025 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | 400B |
| License | Proprietary | Custom |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.188 |
| Output $/1M | $12.00 | $0.652 |
| Vision Tasks | ||
| Classification | Demo | Supported |
| Object Detection | Demo | Supported |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 76.8% | Not evaluated |
| Avg cost / sample | $0.010 | – |
| Avg speed / sample | 8.44s | – |
| By task | ||
| Object Detection | 67.4% | – |
| Counting | 71.6% | – |
| Identification | 100.0% | – |
| OCR (low) | 72.6% | – |
| by category |
| |
| OCR (high) | 73.1% | – |
| by category |
| |
| Reasoning (low) | 72.2% | – |
| Reasoning (high) | 74.8% | – |
Gemini 3.1 Pro vs Llama 4 Maverick: Overview
Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.
The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.
Llama 4 Maverick, introduced on April 5, 2025, is one of the first models in Meta’s Llama 4 family, designed as a natively multimodal model supporting text + image inputs with text outputs. It employs a Mixture-of-Experts (MoE) architecture with 128 experts, activating ~17B parameters per token out of a pool of ~400B total parameters. This design improves scalability, efficiency, and reasoning capacity. Maverick has a 1M-token context window, enabling it to handle large documents, extended conversations, and multimodal reasoning. Its knowledge cutoff is August 2024.
The model is released under the Llama 4 Community License and comes in both base and instruction-tuned (“Instruct”) versions. Maverick is widely deployed via Hugging Face, Google Vertex AI, Amazon Bedrock, and Oracle Cloud, making it one of the most accessible large open-weight models. However, it outputs text only (no image/audio generation) and, while input capacity is huge, output limits are typically much smaller. The MoE design also raises hardware demands, as maintaining 128 experts requires significant compute resources, and Meta’s license introduces restrictions around commercial-scale use.