GPT-3.5 Turbo vs GPT-4: Benchmark Comparison
Detailed comparison of GPT-3.5 Turbo and GPT-4 covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | GPT-3.5 Turbo | GPT-4 |
|---|---|---|
| Vendor | openai | openai |
| Version | 3.5-turbo | 4 |
| Release Date | 2023-03-01 | 2023-03-14 |
| Context Window | 16385 tokens | 8192 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | Proprietary | Proprietary |
| SOC2 | ✓ | ✓ |
| HIPAA | ✓ | ✓ |
| GDPR | ✓ | ✓ |
| ISO 27001 | ✓ | ✓ |
Benchmark Results
| Benchmark | GPT-3.5 Turbo | GPT-4 | Winner |
|---|---|---|---|
| ARC | 86.8 | 94.1 | GPT-4 |
| BBH | 48.2 | 80.9 | GPT-4 |
| GPQA | 22.4 | 39.2 | GPT-4 |
| GSM8K | 34.3 | 91.7 | GPT-4 |
| HUMANEVAL | 51.3 | 77.6 | GPT-4 |
| IFEVAL | 57.4 | 74.6 | GPT-4 |
| MATH | 17.8 | 43.9 | GPT-4 |
| MMLU | 61.1 | 85.8 | GPT-4 |
| MUSR | 29.2 | 54.6 | GPT-4 |
| WINOGRANDE | 76.7 | 80.3 | GPT-4 |
Pricing Comparison
| Tier (per Mtok) | GPT-3.5 Turbo | GPT-4 |
|---|---|---|
| Input | $0.5 | $30 |
| Output | $1.5 | $60 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
GPT-3.5 Turbo gegen GPT-4
Modellübersicht
GPT-3.5 Turbo and GPT-4 are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Hauptspezifikationen
| Anbieter | Veröffentlichungsdatum | Kontextfenster | Lizenz |
|---|---|---|---|
| Openai / Openai | 2023-03-01 / 2023-03-14 | 16K / 8K | Proprietary / Proprietary |
Benchmark-Leistung
| Benchmark | GPT-3.5 Turbo | GPT-4 | Gewinner |
|---|---|---|---|
| ARC | 86.8 | 94.1 | B |
| BBH (BIG-Bench Hard) | 48.2 | 80.9 | B |
| GPQA | 22.4 | 39.2 | B |
| GSM8K (Grade School Math 8K) | 34.3 | 91.7 | B |
| HumanEval | 51.3 | 77.6 | B |
| IFEval | 57.4 | 74.6 | B |
| MATH | 17.8 | 43.9 | B |
| MMLU (Massive Multitask Language Understanding) | 61.1 | 85.8 | B |
| MUSR | 29.2 | 54.6 | B |
| WinoGrande | 76.7 | 80.3 | B |
Preisvergleich
| Eingabe | Ausgabe | Cache-Lesen | Cache-Schreiben |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
pro Million Token — A / B
Stärken & Schwächen
GPT-3.5 Turbo
- ✅ 可靠的通用模型。
- ⚠️ 闭源专有模型，不支持自托管。
- ⚠️ 上下文窗口 16K 偏小。
GPT-4
- ✅ MMLU score 85.8, strong knowledge reasoning.
- ✅ GSM8K 91.7, robust math reasoning.
- ⚠️ 闭源专有模型，不支持自托管。
- ⚠️ 上下文窗口 8K 偏小。
Redaktionsmeinung
GPT-3.5 Turbo and GPT-4 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.
Referenzen
Editor's Take
See Editor's Take section.