Key Specifications

SpecificationLlama 3.1 405BQwen2.5 72B
Vendormetaalibaba
Version3.1-405b2.5-72b
Release Date2024-07-232024-09-19
Context Window128000 tokens131072 tokens
Input Modalitiestexttext
Output Modalitiestexttext
LicenseLlama 3 Community LicenseQwen License
SOC2
HIPAA
GDPR
ISO 27001

Benchmark Results

BenchmarkLlama 3.1 405BQwen2.5 72BWinner
BBH82.982.4Llama 3.1 405B
GSM8K89.288.4Llama 3.1 405B
HUMANEVAL8986.6Llama 3.1 405B
MATH73.883.1Qwen2.5 72B
MMLU88.686.1Llama 3.1 405B

Pricing Comparison

Tier (per Mtok)Llama 3.1 405BQwen2.5 72B
Input$5$0.5
Output$15$0.8
Cache Read$0$0
Cache Write$0$0

Llama 3.1 405B 대 Qwen2.5 72B

모델 개요

Llama 3.1 405B and Qwen2.5 72B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.

핵심 사양

공급업체출시일컨텍스트 창라이선스
Meta / Alibaba2024-07-23 / 2024-09-19128K / 131KLlama 3 Community License / Qwen License

벤치마크 성능

벤치마크Llama 3.1 405BQwen2.5 72B승자
BBH (BIG-Bench Hard)82.982.4A
GSM8K (Grade School Math 8K)89.288.4A
HumanEval89.086.6A
MATH73.883.1B
MMLU (Massive Multitask Language Understanding)88.686.1A

가격 비교

입력출력캐시 읽기캐시 쓰기
— / —— / —— / —— / —

백만 토큰당 — A / B

강점 & 약점

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。

Qwen2.5 72B

  • ✅ MMLU score 86.1, strong knowledge reasoning.
  • ✅ HumanEval 86.6, excellent code generation.
  • ✅ GSM8K 88.4, robust math reasoning.
  • ⚠️ 闭源专有模型,不支持自托管。

편집자 의견

Llama 3.1 405B and Qwen2.5 72B 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.