Llama 3.2 90B Vision vs GPT-4o: Benchmark Comparison
Detailed comparison of Llama 3.2 90B Vision and GPT-4o covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | Llama 3.2 90B Vision | GPT-4o |
|---|---|---|
| Vendor | meta | openai |
| Version | 3.2-90b-vision | 4o |
| Release Date | 2024-09-25 | 2024-05-13 |
| Context Window | 128000 tokens | 128000 tokens |
| Input Modalities | text, image | text, image, audio |
| Output Modalities | text | text, audio |
| License | Llama 3.2 Community License | Proprietary |
| SOC2 | ✗ | ✓ |
| HIPAA | ✗ | ✓ |
| GDPR | ✗ | ✓ |
| ISO 27001 | ✗ | ✓ |
Benchmark Results
| Benchmark | Llama 3.2 90B Vision | GPT-4o | Winner |
|---|---|---|---|
| ARC | 94.6 | — | Llama 3.2 90B Vision |
| BBH | 76.1 | 83.1 | GPT-4o |
| GPQA | 42.2 | — | Llama 3.2 90B Vision |
| GSM8K | 82.6 | 95.8 | GPT-4o |
| HUMANEVAL | 73.1 | 90.2 | GPT-4o |
| IFEVAL | 74.5 | — | Llama 3.2 90B Vision |
| MATH | 52.5 | 76.6 | GPT-4o |
| MMLU | 76.5 | 88.7 | GPT-4o |
| MUSR | 53.5 | — | Llama 3.2 90B Vision |
| WINOGRANDE | 79.3 | — | Llama 3.2 90B Vision |
Pricing Comparison
| Tier (per Mtok) | Llama 3.2 90B Vision | GPT-4o |
|---|---|---|
| Input | $1.2 | $2.5 |
| Output | $1.2 | $10 |
| Cache Read | $0 | $1.25 |
| Cache Write | $0 | $2.5 |
Llama 3.2 90B Vision vs GPT-4o
Ikhtisar Model
Llama 3.2 90B Vision and GPT-4o are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Spesifikasi Utama
| Vendor | Tanggal Rilis | Jendela Konteks | Lisensi |
|---|---|---|---|
| Meta / Openai | 2024-09-25 / 2024-05-13 | 128K / 128K | Llama 3.2 Community License / Proprietary |
Kinerja Benchmark
| Benchmark | Llama 3.2 90B Vision | GPT-4o | Pemenang |
|---|---|---|---|
| ARC | 94.6 | — | A |
| BBH (BIG-Bench Hard) | 76.1 | 83.1 | B |
| GPQA | 42.2 | — | A |
| GSM8K (Grade School Math 8K) | 82.6 | 95.8 | B |
| HumanEval | 73.1 | 90.2 | B |
| IFEval | 74.5 | — | A |
| MATH | 52.5 | 76.6 | B |
| MMLU (Massive Multitask Language Understanding) | 76.5 | 88.7 | B |
| MUSR | 53.5 | — | A |
| WinoGrande | 79.3 | — | A |
Perbandingan Harga
| Input | Output | Baca Cache | Tulis Cache |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
per juta token — A / B
Kelebihan & Kekurangan
Llama 3.2 90B Vision
- ✅ 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。
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。
Pendapat Editor
Llama 3.2 90B Vision and GPT-4o 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.
Referensi
Editor's Take
See Editor's Take section.