Gemini 1.0 Pro vs Qwen2.5-Vl-72B-Instruct: Benchmarks, Pricing, and Context Window Comparison
Gemini 1.0 Pro vs Qwen2.5-Vl-72B-Instruct compares provider, context window, token pricing, benchmark performance, and release timeline in one side-by-side view. Use this page to quickly identify which model is a better fit for your production constraints, quality targets, and estimated cost per request.
Verdict
Qwen2.5-Vl-72B-Instruct has lower listed token pricing, while Gemini 1.0 Pro can still be preferable if benchmark results better match your workload.
Author: Mirai Minds Research Team
Last updated:
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Overview
Gemini 1.0 Pro was released 9 months before Qwen2.5-Vl-72B-Instruct.
Provider The entity that provides this model. | ||
Input Context Window The number of tokens supported by the input context window. | 32.8K tokens | 129,024 tokens |
Maximum Output Tokens The number of tokens that can be generated by the model in a single request. | 8,192 tokens | 8,192 tokens |
Release Date When the model was first released. | Dec 13, 2023 over 1 yearago 2023-12-13 | Sep 19, 2024 over 1 year 2024-09-19 |
Leaderboard
Rank | 25 | Unknown |
Arena Elo | 1115 | Not specified. |
95% CI | +6/-6 | Not specified. |
Votes | 6818 | Not specified. |
License | Proprietary | Not specified. |
Knowledge Cutoff | 4/2023 4/2023 | Unknown |
Pricing
Input Cost of input data provided to the model. | $12.50 per million tokens | $1.95 per million tokens |
Output Cost of output tokens generated by the model. | $37.50 per million tokens | $8.00 per million tokens |
Benchmarks
Compare relevant benchmarks between Gemini 1.0 Pro and Qwen2.5-Vl-72B-Instruct Instruct.
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings. | 71.8 (5-shot) | Benchmark not available. |
MMMU A wide ranging multi-discipline and multimodal benchmark. | 47.9 | Benchmark not available. |
HellaSwag A challenging sentence completion benchmark. | Benchmark not available. | Benchmark not available. |
