GPT-4o vs Gemini 2.0 Flash: Benchmark Comparison
Detailed comparison of GPT-4o and Gemini 2.0 Flash covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | GPT-4o | Gemini 2.0 Flash |
|---|---|---|
| Vendor | openai | |
| Version | 4o | 2.0-flash |
| Release Date | 2024-05-13 | 2024-12-11 |
| Context Window | 128000 tokens | 1.048576e+06 tokens |
| Input Modalities | text, image, audio | text, image, audio, video |
| Output Modalities | text, audio | text |
| License | Proprietary | Proprietary |
| SOC2 | ✓ | ✓ |
| HIPAA | ✓ | ✗ |
| GDPR | ✓ | ✓ |
| ISO 27001 | ✓ | ✓ |
Benchmark Results
| Benchmark | GPT-4o | Gemini 2.0 Flash | Winner |
|---|---|---|---|
| ARC | — | 95.7 | Gemini 2.0 Flash |
| BBH | 83.1 | 83.4 | Gemini 2.0 Flash |
| GPQA | — | 55 | Gemini 2.0 Flash |
| GSM8K | 95.8 | 92.7 | GPT-4o |
| HUMANEVAL | 90.2 | 90.7 | Gemini 2.0 Flash |
| IFEVAL | — | 85.9 | Gemini 2.0 Flash |
| MATH | 76.6 | 71.3 | GPT-4o |
| MMLU | 88.7 | 86.3 | GPT-4o |
| MUSR | — | 69.3 | Gemini 2.0 Flash |
| WINOGRANDE | — | 89.5 | Gemini 2.0 Flash |
Pricing Comparison
| Tier (per Mtok) | GPT-4o | Gemini 2.0 Flash |
|---|---|---|
| Input | $2.5 | $0.1 |
| Output | $10 | $0.4 |
| Cache Read | $1.25 | $0 |
| Cache Write | $2.5 | $0 |
GPT-4o kontra Gemini 2.0 Flash
Przegląd modelu
GPT-4o and Gemini 2.0 Flash are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Kluczowe specyfikacje
| Dostawca | Data wydania | Okno kontekstowe | Licencja |
|---|---|---|---|
| Openai / Google | 2024-05-13 / 2024-12-11 | 128K / 1048K | Proprietary / Proprietary |
Wydajność benchmarków
| Benchmark | GPT-4o | Gemini 2.0 Flash | Zwycięzca |
|---|---|---|---|
| ARC | — | 95.7 | B |
| BBH (BIG-Bench Hard) | 83.1 | 83.4 | Tie |
| GPQA | — | 55.0 | B |
| GSM8K (Grade School Math 8K) | 95.8 | 92.7 | A |
| HumanEval | 90.2 | 90.7 | B |
| IFEval | — | 85.9 | B |
| MATH | 76.6 | 71.3 | A |
| MMLU (Massive Multitask Language Understanding) | 88.7 | 86.3 | A |
| MUSR | — | 69.3 | B |
| WinoGrande | — | 89.5 | B |
Porównanie cen
| Wejście | Wyjście | Odczyt pamięci podręcznej | Zapis pamięci podręcznej |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
za milion tokenów — A / B
Mocne strony & Słabe strony
GPT-4o
- ✅ MMLU score 88.7, strong knowledge reasoning.
- ✅ HumanEval 90.2, excellent code generation.
- ✅ GSM8K 95.8, robust math reasoning.
- ✅ 支持文本、图像、音频多模态输入。
- ⚠️ 闭源专有模型，不支持自托管。
Gemini 2.0 Flash
- ✅ MMLU score 86.3, strong knowledge reasoning.
- ✅ HumanEval 90.7, excellent code generation.
- ✅ GSM8K 92.7, robust math reasoning.
- ✅ 支持文本、图像、音频多模态输入。
- ⚠️ 闭源专有模型，不支持自托管。
Opinia redakcji
GPT-4o and Gemini 2.0 Flash each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
FAQ
Which model is better for coding tasks?
Refer to the HumanEval benchmark table; the model with a higher score is better suited for coding tasks.
Which model is cheaper?
Refer to the pricing comparison table above; the model with lower input/output prices is more cost-effective.
Which has a longer context window?
Refer to the key specifications table; the model with a larger context window is better for long documents.
Referencje
Editor's Take
See Editor's Take section.