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Gemini 2.0 Flash Thinking vs GPT-4 Turbo

Gemini 2.0 Flash Thinking leads the LLM Stats Score 17.0 to 9.6.

Google · OpenAI · Updated for 2026

Which is better?

Gemini 2.0 Flash Thinking leads the overall LLM Stats Score 17.0 to 9.6, ranking #198 overall.

In the 1 individual benchmarks reported for both models, Gemini 2.0 Flash Thinking wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 2.0 Flash Thinking

  • overall performance matters — it scores 17.0 and ranks #198 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Jan 2025

Choose GPT-4 Turbo

  • you want predictable pricing at $10.00/M input and $30.00/M output

At a glance

The differences that matter most.

Gemini 2.0 Flash Thinking
Google
GPT-4 Turbo
OpenAI
Core performance indexes
LLM Stats Score
17.0
#198
9.6
#250
Reasoning
17.3
#192
9.7
#242
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$10.00 / M
Output price
— / M
$30.00 / M
Context window
—
128,000

Individual benchmarks

3 reported for Gemini 2.0 Flash Thinking · 6 for GPT-4 Turbo

1 shared

Gemini 2.0 Flash Thinking outperforms in 1 benchmarks (GPQA), while GPT-4 Turbo is better at 0 benchmarks.

Gemini 2.0 Flash Thinking significantly outperforms across most benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-4 Turbo specifies input context (128,000 tokens). Only GPT-4 Turbo specifies output context (4,096 tokens).

Google
Gemini 2.0 Flash Thinking
Input- tokens
Output- tokens
OpenAI
GPT-4 Turbo
Input128,000 tokens
Output4,096 tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 2.0 Flash Thinking supports multimodal inputs, whereas GPT-4 Turbo does not.

Gemini 2.0 Flash Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 2.0 Flash Thinking

Text
Images
Audio
Video

GPT-4 Turbo

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 Thinking

Proprietary

Closed source

GPT-4 Turbo

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 2.0 Flash Thinking was released on 2025-01-21, while GPT-4 Turbo was released on 2024-04-09.

Gemini 2.0 Flash Thinking is 10 months newer than GPT-4 Turbo.

Gemini 2.0 Flash Thinking

Jan 21, 2025

1.6 years ago

9mo newer
GPT-4 Turbo

Apr 9, 2024

2.4 years ago

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash Thinking has a knowledge cutoff of 2024-08-01, while GPT-4 Turbo has a cutoff of 2023-12-31.

Gemini 2.0 Flash Thinking has more recent training data (up to 2024-08-01), making it potentially better informed about events through that date compared to GPT-4 Turbo (2023-12-31).

Gemini 2.0 Flash Thinking

Aug 2024

8 mo newer
GPT-4 Turbo

Dec 2023

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 2.0 Flash Thinking and GPT-4 Turbo side-by-side, then vote on the output you prefer.

Gemini 2.0 Flash Thinking
✓ Preferred
GPT-4 Turbo
Open in Playground

FAQ

Common questions about Gemini 2.0 Flash Thinking vs GPT-4 Turbo.

Which is better, Gemini 2.0 Flash Thinking or GPT-4 Turbo?

Gemini 2.0 Flash Thinking leads the LLM Stats Score 17.0 to 9.6. Gemini 2.0 Flash Thinking is made by Google and GPT-4 Turbo is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 2.0 Flash Thinking compare to GPT-4 Turbo in benchmarks?

Gemini 2.0 Flash Thinking scores MMMU: 75.4%, GPQA: 74.2%, AIME 2024: 73.3%. GPT-4 Turbo scores MGSM: 88.5%, HumanEval: 87.1%, MMLU: 86.5%, DROP: 86.0%, MATH: 72.6%.

What are the context window sizes for Gemini 2.0 Flash Thinking and GPT-4 Turbo?

Gemini 2.0 Flash Thinking supports an unknown number of tokens and GPT-4 Turbo supports 128K 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 Thinking and GPT-4 Turbo?

Key differences include LLM Stats Score (17.0 vs 9.6), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.0 Flash Thinking and GPT-4 Turbo?

Gemini 2.0 Flash Thinking is developed by Google and GPT-4 Turbo is developed by OpenAI.

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