Key Specifications

SpecificationGPT-4oLlama 3.1 405B
Vendoropenaimeta
Version4o3.1-405b
Release Date2024-05-132024-07-23
Context Window128000 tokens128000 tokens
Input Modalitiestext, image, audiotext
Output Modalitiestext, audiotext
LicenseProprietaryLlama 3 Community License
SOC2
HIPAA
GDPR
ISO 27001

Benchmark Results

BenchmarkGPT-4oLlama 3.1 405BWinner
BBH83.182.9GPT-4o
GSM8K95.889.2GPT-4o
HUMANEVAL90.289GPT-4o
MATH76.673.8GPT-4o
MMLU88.788.6GPT-4o

Pricing Comparison

Tier (per Mtok)GPT-4oLlama 3.1 405B
Input$2.5$5
Output$10$15
Cache Read$1.25$0
Cache Write$2.5$0

GPT-4o 대 Llama 3.1 405B

모델 개요

GPT-4o and Llama 3.1 405B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.

핵심 사양

공급업체출시일컨텍스트 창라이선스
Openai / Meta2024-05-13 / 2024-07-23128K / 128KProprietary / Llama 3 Community License

벤치마크 성능

벤치마크GPT-4oLlama 3.1 405B승자
BBH (BIG-Bench Hard)83.182.9Tie
GSM8K (Grade School Math 8K)95.889.2A
HumanEval90.289.0A
MATH76.673.8A
MMLU (Massive Multitask Language Understanding)88.788.6Tie

가격 비교

입력출력캐시 읽기캐시 쓰기
— / —— / —— / —— / —

백만 토큰당 — A / B

강점 & 약점

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。

Llama 3.1 405B

  • ✅ MMLU score 88.6, strong knowledge reasoning.
  • ✅ HumanEval 89.0, excellent code generation.
  • ✅ GSM8K 89.2, robust math reasoning.
  • ⚠️ 闭源专有模型,不支持自托管。

편집자 의견

GPT-4o and Llama 3.1 405B 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.

참고문헌

Editor's Take

See Editor's Take section.