OpenGVLab: InternVL3 78B

Text input Image input Text output
Author's Description

The InternVL3 series is an advanced multimodal large language model (MLLM). Compared to InternVL 2.5, InternVL3 demonstrates stronger multimodal perception and reasoning capabilities. In addition, InternVL3 is benchmarked against the Qwen2.5 Chat models, whose pre-trained base models serve as the initialization for its language component. Benefiting from Native Multimodal Pre-Training, the InternVL3 series surpasses the Qwen2.5 series in overall text performance.

Key Specifications
Cost
$$
Context
32K
Parameters
78B
Released
Sep 15, 2025
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Response Format Max Tokens Presence Penalty Min P Top P Top Logprobs Temperature Structured Outputs Stop Logit Bias Frequency Penalty Seed Logprobs
Features

This model supports the following features:

Response Format Structured Outputs
Performance Summary

OpenGVLab's InternVL3 78B, created on September 15, 2025, is an advanced multimodal large language model (MLLM) with a context length of 32768. It consistently ranks among the fastest models and offers highly competitive pricing across all benchmarks. Demonstrating exceptional reliability, the model achieved a 100% success rate across seven benchmarks, indicating minimal technical failures. In terms of performance, InternVL3 78B exhibits perfect accuracy in both General Knowledge and Ethics benchmarks, often being the most accurate model at its price point and speed. It also shows strong performance in Email Classification (97.0% accuracy) and Coding (84.0% accuracy). While its Instruction Following (57.6% accuracy) and Reasoning (52.0% accuracy) capabilities are moderate, they still place it within a competitive range. A notable strength is its 0.0% hallucination rate, indicating a robust ability to acknowledge uncertainty. Overall, InternVL3 78B stands out for its high accuracy in knowledge-based and ethical tasks, combined with superior speed, cost-efficiency, and reliability.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.0326
Completion $0.13

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
Chutes
Chutes | opengvlab/internvl3-78b 32K $0.0326 / 1M tokens $0.13 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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