Model Comparison

Gemini 1.5 Pro vs Gemini 2.5 FlashWhich is better in 2026?

Gemini 2.5 Flash shows notably better performance in the majority of benchmarks. Gemini 2.5 Flash is 5.1x cheaper per token.

Verdict: Gemini 1.5 Pro vs Gemini 2.5 Flash — which is better?

Gemini 1.5 Pro (by Google) and Gemini 2.5 Flash (by Google) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Gemini 1.5 Pro outperforms in 1 benchmarks (MRCR), while Gemini 2.5 Flash is better at 3 benchmarks (GPQA, MMMU, Vibe-Eval). Gemini 2.5 Flash shows notably better performance in the majority of benchmarks.

On price, Gemini 2.5 Flash is roughly 5.1x 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.

Choose Gemini 1.5 Pro if…

  • you process long inputs — it offers a 2,097,152 token context window

Choose Gemini 2.5 Flash if…

  • you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
  • cost matters — it's about 5.1x cheaper per token
  • you want the most recent training data — it shipped May 2025
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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Gemini 1.5 Pro outperforms in 1 benchmarks (MRCR), while Gemini 2.5 Flash is better at 3 benchmarks (GPQA, MMMU, Vibe-Eval).

Gemini 2.5 Flash shows notably better performance in the majority of benchmarks.

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemini 2.5 Flash costs less

For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 8.3x more expensive than Gemini 2.5 Flash ($0.30/1M tokens).

For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 4.0x more expensive than Gemini 2.5 Flash ($2.50/1M tokens).

In conclusion, Gemini 1.5 Pro is more expensive than Gemini 2.5 Flash.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
Google
Gemini 1.5 Pro
Input tokens$2.50
Output tokens$10.00
Best providerGoogle
Google
Gemini 2.5 Flash
Input tokens$0.30
Output tokens$2.50
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Gemini 2.5 Flash's 1,048,576 tokens. Gemini 2.5 Flash can generate longer responses up to 65,536 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.

Google
Gemini 1.5 Pro
Input2,097,152 tokens
Output8,192 tokens
Google
Gemini 2.5 Flash
Input1,048,576 tokens
Output65,536 tokens
Sat Jun 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 1.5 Pro and Gemini 2.5 Flash support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 1.5 Pro

Text
Images
Audio
Video

Gemini 2.5 Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Gemini 1.5 Pro

Proprietary

Closed source

Gemini 2.5 Flash

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 1.5 Pro was released on 2024-05-01, while Gemini 2.5 Flash was released on 2025-05-20.

Gemini 2.5 Flash is 13 months newer than Gemini 1.5 Pro.

Gemini 1.5 Pro

May 1, 2024

2.1 years ago

Gemini 2.5 Flash

May 20, 2025

1.1 years ago

1.1yr newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Pro has a knowledge cutoff of 2023-11-01, while Gemini 2.5 Flash has a cutoff of 2025-01-31.

Gemini 2.5 Flash has more recent training data (up to 2025-01-31), making it potentially better informed about events through that date compared to Gemini 1.5 Pro (2023-11-01).

Gemini 1.5 Pro

Nov 2023

Gemini 2.5 Flash

Jan 2025

1.2 yr newer

Provider Availability

Gemini 1.5 Pro is available from Google. Gemini 2.5 Flash is available from Google.

Gemini 1.5 Pro

google logo
Google
Input Price:Input: $2.50/1MOutput Price:Output: $10.00/1M

Gemini 2.5 Flash

google logo
Google
Input Price:Input: $0.30/1MOutput Price:Output: $2.50/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Google
Larger context window (2,097,152 tokens)
Higher MRCR score (82.6% vs 32.0%)
Google
Less expensive input tokens
Less expensive output tokens
Higher GPQA score (82.8% vs 59.1%)
Higher MMMU score (79.7% vs 65.9%)
Higher Vibe-Eval score (65.4% vs 53.9%)
GoogleGemini 1.5 Pro
GoogleGemini 2.5 Flash
Compare in Playground

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.5 Pro
Google
Gemini 2.5 Flash

FAQ

Common questions about Gemini 1.5 Pro vs Gemini 2.5 Flash.

Which is better, Gemini 1.5 Pro or Gemini 2.5 Flash?

Gemini 2.5 Flash shows notably better performance in the majority of benchmarks. Gemini 1.5 Pro is made by Google and Gemini 2.5 Flash is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 1.5 Pro compare to Gemini 2.5 Flash in benchmarks?

Gemini 1.5 Pro scores XSTest: 98.8%, FLEURS: 93.3%, HellaSwag: 93.3%, GSM8k: 90.8%, BIG-Bench Hard: 89.2%. Gemini 2.5 Flash scores Global-MMLU-Lite: 88.4%, AIME 2024: 88.0%, FACTS Grounding: 85.3%, GPQA: 82.8%, MMMU: 79.7%.

Is Gemini 1.5 Pro cheaper than Gemini 2.5 Flash?

Gemini 2.5 Flash is 8.3x cheaper for input tokens. Gemini 1.5 Pro costs $2.50/M input and $10.00/M output via google. Gemini 2.5 Flash costs $0.30/M input and $2.50/M output via google.

What are the context window sizes for Gemini 1.5 Pro and Gemini 2.5 Flash?

Gemini 1.5 Pro supports 2.1M tokens and Gemini 2.5 Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 1.5 Pro and Gemini 2.5 Flash?

Key differences include context window (2.1M vs 1.0M), input pricing ($2.50 vs $0.30/M). See the full comparison above for benchmark-by-benchmark results.

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