Gemini 1.5 Pro vs Qwen2.5 72B Instruct
Gemini 1.5 Pro and Qwen2.5 72B Instruct are closely matched at 12.0 and 12.1 on the LLM Stats Score. Qwen2.5 72B Instruct is 12.1x cheaper per token.
Google · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Gemini 1.5 Pro and Qwen2.5 72B Instruct are closely matched on the overall LLM Stats Score at 12.0 and 12.1.
In the 5 individual benchmarks reported for both models, Gemini 1.5 Pro wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen2.5 72B Instruct is roughly 12.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 1.5 Pro
- you value its reported benchmark strengths — it wins 3 of 5 exact shared results
- you process long inputs — it offers a 2,097,152 token context window
Choose Qwen2.5 72B Instruct
- cost matters — it's about 12.1x cheaper per token
- you want the most recent training data — it shipped Sep 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
23 reported for Gemini 1.5 Pro · 14 for Qwen2.5 72B Instruct
Gemini 1.5 Pro outperforms in 3 benchmarks (GPQA, MATH, MMLU-Pro), while Qwen2.5 72B Instruct is better at 2 benchmarks (GSM8k, HumanEval).
Gemini 1.5 Pro has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 7.1x more expensive than Qwen2.5 72B Instruct ($0.35/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 25.0x more expensive than Qwen2.5 72B Instruct ($0.40/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than Qwen2.5 72B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Qwen2.5 72B Instruct's 131,072 tokens. Both models can generate responses up to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 1.5 Pro supports multimodal inputs, whereas Qwen2.5 72B Instruct does not.
Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 1.5 Pro
Qwen2.5 72B Instruct
License
Usage and distribution terms
Gemini 1.5 Pro is licensed under a proprietary license, while Qwen2.5 72B Instruct uses Qwen.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Qwen
Open weights
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while Qwen2.5 72B Instruct was released on 2024-09-19.
Qwen2.5 72B Instruct is 5 months newer than Gemini 1.5 Pro.
May 1, 2024
2.4 years ago
Sep 19, 2024
2.0 years ago
4mo newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Qwen2.5 72B Instruct's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Qwen2.5 72B Instruct's cutoff date.
Nov 2023
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Provider Availability
Gemini 1.5 Pro is available from Google. Qwen2.5 72B Instruct is available from DeepInfra, Hyperbolic, Fireworks, Together.
Gemini 1.5 Pro
Qwen2.5 72B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and Qwen2.5 72B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs Qwen2.5 72B Instruct.