Key Specifications

Specificationo1DeepSeek V3
Vendoropenaideepseek
Versiono1v3
Release Date2024-12-172024-12-26
Context Window200000 tokens64000 tokens
Input Modalitiestexttext
Output Modalitiestexttext
LicenseProprietaryDeepSeek License
SOC2
HIPAA
GDPR
ISO 27001

Benchmark Results

Benchmarko1DeepSeek V3Winner
ARC96.8o1
BBH83.184.9DeepSeek V3
GPQA57.5o1
GSM8K88.989.3DeepSeek V3
HUMANEVAL85.382.6o1
IFEVAL82.2o1
MATH55.761.6DeepSeek V3
MMLU86.388.5DeepSeek V3
MUSR71.8o1
WINOGRANDE86.7o1

Pricing Comparison

Tier (per Mtok)o1DeepSeek V3
Input$15$0.27
Output$60$1.1
Cache Read$0$0.07
Cache Write$0$0.27

o1 대 DeepSeek V3

모델 개요

o1 and DeepSeek V3 are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.

핵심 사양

공급업체출시일컨텍스트 창라이선스
Openai / Deepseek2024-12-17 / 2024-12-26200K / 64KProprietary / DeepSeek License

벤치마크 성능

벤치마크o1DeepSeek V3승자
ARC96.8A
BBH (BIG-Bench Hard)83.184.9B
GPQA57.5A
GSM8K (Grade School Math 8K)88.989.3Tie
HumanEval85.382.6A
IFEval82.2A
MATH55.761.6B
MMLU (Massive Multitask Language Understanding)86.388.5B
MUSR71.8A
WinoGrande86.7A

가격 비교

입력출력캐시 읽기캐시 쓰기
— / —— / —— / —— / —

백만 토큰당 — A / B

강점 & 약점

o1

  • ✅ MMLU score 86.3, strong knowledge reasoning.
  • ✅ HumanEval 85.3, excellent code generation.
  • ✅ GSM8K 88.9, robust math reasoning.
  • ⚠️ 闭源专有模型,不支持自托管。

DeepSeek V3

  • ✅ MMLU score 88.5, strong knowledge reasoning.
  • ✅ HumanEval 82.6, excellent code generation.
  • ✅ GSM8K 89.3, robust math reasoning.
  • ✅ 采用 MoE 混合专家架构。
  • ⚠️ 闭源专有模型,不支持自托管。

편집자 의견

o1 and DeepSeek V3 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.