Model Comparison

Gemini 2.0 Flash vs Gemini 2.5 ProWhich is better in 2026?

Gemini 2.5 Pro significantly outperforms across most benchmarks. Gemini 2.0 Flash is 19.6x cheaper per token.

Verdict: Gemini 2.0 Flash vs Gemini 2.5 Pro — which is better?

Gemini 2.0 Flash (by Google) and Gemini 2.5 Pro (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 2.0 Flash outperforms in 0 benchmarks, while Gemini 2.5 Pro is better at 4 benchmarks (GPQA, MMMU, MRCR, Vibe-Eval). Gemini 2.5 Pro significantly outperforms across most benchmarks.

On price, Gemini 2.0 Flash is roughly 19.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Choose Gemini 2.0 Flash if…

  • cost matters — it's about 19.6x cheaper per token

Choose Gemini 2.5 Pro if…

  • you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
  • you want the most recent training data — it shipped May 2025

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Gemini 2.0 Flash outperforms in 0 benchmarks, while Gemini 2.5 Pro is better at 4 benchmarks (GPQA, MMMU, MRCR, Vibe-Eval).

Gemini 2.5 Pro significantly outperforms across most benchmarks.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemini 2.0 Flash costs less

For input processing, Gemini 2.0 Flash ($0.10/1M tokens) is 12.5x cheaper than Gemini 2.5 Pro ($1.25/1M tokens).

For output processing, Gemini 2.0 Flash ($0.40/1M tokens) is 25.0x cheaper than Gemini 2.5 Pro ($10.00/1M tokens).

In conclusion, Gemini 2.5 Pro is more expensive than Gemini 2.0 Flash.*

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

Lowest available price from all providers
Tue Jul 21 2026 • llm-stats.com
Google
Gemini 2.0 Flash
Input tokens$0.10
Output tokens$0.40
Best providerGoogle
Google
Gemini 2.5 Pro
Input tokens$1.25
Output tokens$10.00
Best providerGoogle
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. Gemini 2.5 Pro can generate longer responses up to 65,536 tokens, while Gemini 2.0 Flash is limited to 8,192 tokens.

Google
Gemini 2.0 Flash
Input1,048,576 tokens
Output8,192 tokens
Google
Gemini 2.5 Pro
Input1,048,576 tokens
Output65,536 tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 2.0 Flash and Gemini 2.5 Pro support multimodal inputs.

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

Gemini 2.0 Flash

Text
Images
Audio
Video

Gemini 2.5 Pro

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 2.0 Flash

Proprietary

Closed source

Gemini 2.5 Pro

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 2.0 Flash was released on 2024-12-01, while Gemini 2.5 Pro was released on 2025-05-20.

Gemini 2.5 Pro is 6 months newer than Gemini 2.0 Flash.

Gemini 2.0 Flash

Dec 1, 2024

1.6 years ago

Gemini 2.5 Pro

May 20, 2025

1.2 years ago

5mo newer

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash has a knowledge cutoff of 2024-08-01, while Gemini 2.5 Pro has a cutoff of 2025-01-31.

Gemini 2.5 Pro has more recent training data (up to 2025-01-31), making it potentially better informed about events through that date compared to Gemini 2.0 Flash (2024-08-01).

Gemini 2.0 Flash

Aug 2024

Gemini 2.5 Pro

Jan 2025

5 mo newer

Provider Availability

Gemini 2.0 Flash is available from Google. Gemini 2.5 Pro is available from Google.

Gemini 2.0 Flash

google logo
Google
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

Gemini 2.5 Pro

google logo
Google
Input Price:Input: $1.25/1MOutput Price:Output: $10.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Less expensive input tokens
Less expensive output tokens
Google
Higher GPQA score (83.0% vs 62.1%)
Higher MMMU score (79.6% vs 70.7%)
Higher MRCR score (93.0% vs 69.2%)
Higher Vibe-Eval score (65.6% vs 56.3%)
GoogleGemini 2.0 Flash
GoogleGemini 2.5 Pro
Compare in Playground

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemini 2.0 Flash and Gemini 2.5 Pro side-by-side, then vote on the output you prefer.

Gemini 2.0 Flash
✓ Preferred
Gemini 2.5 Pro
Open in Playground
AI Model Comparison Table
Feature
Google
Gemini 2.0 Flash
Google
Gemini 2.5 Pro

FAQ

Common questions about Gemini 2.0 Flash vs Gemini 2.5 Pro.

Which is better, Gemini 2.0 Flash or Gemini 2.5 Pro?

Gemini 2.5 Pro significantly outperforms across most benchmarks. Gemini 2.0 Flash is made by Google and Gemini 2.5 Pro is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 2.0 Flash compare to Gemini 2.5 Pro in benchmarks?

Gemini 2.0 Flash scores Natural2Code: 92.9%, MATH: 89.7%, FACTS Grounding: 83.6%, MMLU-Pro: 76.4%, EgoSchema: 71.5%. Gemini 2.5 Pro scores MRCR: 93.0%, AIME 2024: 92.0%, Global-MMLU-Lite: 88.6%, Video-MME: 84.8%, AIME 2025: 83.0%.

Is Gemini 2.0 Flash cheaper than Gemini 2.5 Pro?

Gemini 2.0 Flash is 12.5x cheaper for input tokens. Gemini 2.0 Flash costs $0.10/M input and $0.40/M output via google. Gemini 2.5 Pro costs $1.25/M input and $10.00/M output via google.

What are the context window sizes for Gemini 2.0 Flash and Gemini 2.5 Pro?

Gemini 2.0 Flash supports 1.0M tokens and Gemini 2.5 Pro 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 2.0 Flash and Gemini 2.5 Pro?

Key differences include input pricing ($0.10 vs $1.25/M). See the full comparison above for benchmark-by-benchmark results.

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