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 ضد GPT-4o
نظرة عامة على النموذج
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.
المواصفات الرئيسية
| المزود | تاريخ الإصدار | نافذة السياق | الترخيص |
|---|---|---|---|
| Meta / Openai | 2024-09-25 / 2024-05-13 | 128K / 128K | Llama 3.2 Community License / Proprietary |
أداء المعايير
| المعيار | Llama 3.2 90B Vision | GPT-4o | الفائز |
|---|---|---|---|
| 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 |
مقارنة الأسعار
| الإدخال | الإخراج | قراءة الذاكرة المؤقتة | كتابة الذاكرة المؤقتة |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
لكل مليون رمز — A / B
نقاط القوة & نقاط الضعف
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。
رأي المحرر
Llama 3.2 90B Vision and GPT-4o each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
الأسئلة الشائعة
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.
المراجع
Editor's Take
See Editor's Take section.