Key Specifications

SpecificationQwen2.5 72BMixtral 8x22B
Vendoralibabamistral
Version2.5-72b8x22b
Release Date2024-09-192024-04-10
Context Window131072 tokens64000 tokens
Input Modalitiestexttext
Output Modalitiestexttext
LicenseQwen LicenseApache 2.0
SOC2
HIPAA
GDPR
ISO 27001

Benchmark Results

BenchmarkQwen2.5 72BMixtral 8x22BWinner
BBH82.474.5Qwen2.5 72B
GSM8K88.478.6Qwen2.5 72B
HUMANEVAL86.645.2Qwen2.5 72B
MATH83.146Qwen2.5 72B
MMLU86.177.8Qwen2.5 72B

Pricing Comparison

Tier (per Mtok)Qwen2.5 72BMixtral 8x22B
Input$0.5$1.2
Output$0.8$1.2
Cache Read$0$0
Cache Write$0$0

Qwen2.5 72B 대 Mixtral 8x22B

모델 개요

Qwen2.5 72B and Mixtral 8x22B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.

핵심 사양

공급업체출시일컨텍스트 창라이선스
Alibaba / Mistral2024-09-19 / 2024-04-10131K / 64KQwen License / Apache 2.0

벤치마크 성능

벤치마크Qwen2.5 72BMixtral 8x22B승자
BBH (BIG-Bench Hard)82.474.5A
GSM8K (Grade School Math 8K)88.478.6A
HumanEval86.645.2A
MATH83.146.0A
MMLU (Massive Multitask Language Understanding)86.177.8A

가격 비교

입력출력캐시 읽기캐시 쓰기
— / —— / —— / —— / —

백만 토큰당 — A / B

강점 & 약점

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。

Mixtral 8x22B

  • ✅ 采用 MoE 混合专家架构。
  • ⚠️ HumanEval 45.2,代码能力较弱。
  • ⚠️ 闭源专有模型,不支持自托管。

편집자 의견

Qwen2.5 72B and Mixtral 8x22B 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.