DeepSeek V2 vs DeepSeek V3: Benchmark Comparison
Detailed comparison of DeepSeek V2 and DeepSeek V3 covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | DeepSeek V2 | DeepSeek V3 |
|---|---|---|
| Vendor | deepseek | deepseek |
| Version | v2 | v3 |
| Release Date | 2024-05-07 | 2024-12-26 |
| Context Window | 32768 tokens | 64000 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | DeepSeek License | DeepSeek License |
| SOC2 | ✗ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✗ |
| ISO 27001 | ✗ | ✗ |
Benchmark Results
| Benchmark | DeepSeek V2 | DeepSeek V3 | Winner |
|---|---|---|---|
| ARC | 92.1 | — | DeepSeek V2 |
| BBH | 70.5 | 84.9 | DeepSeek V3 |
| GPQA | 31.5 | — | DeepSeek V2 |
| GSM8K | 78.8 | 89.3 | DeepSeek V3 |
| HUMANEVAL | 75.7 | 82.6 | DeepSeek V3 |
| IFEVAL | 78.6 | — | DeepSeek V2 |
| MATH | 35.2 | 61.6 | DeepSeek V3 |
| MMLU | 78.2 | 88.5 | DeepSeek V3 |
| MUSR | 53.4 | — | DeepSeek V2 |
| WINOGRANDE | 84.7 | — | DeepSeek V2 |
Pricing Comparison
| Tier (per Mtok) | DeepSeek V2 | DeepSeek V3 |
|---|---|---|
| Input | $0.14 | $0.27 |
| Output | $0.28 | $1.1 |
| Cache Read | $0 | $0.07 |
| Cache Write | $0 | $0.27 |
DeepSeek V2 ضد DeepSeek V3
نظرة عامة على النموذج
DeepSeek V2 and DeepSeek V3 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 |
|---|---|---|---|
| Deepseek / Deepseek | 2024-05-07 / 2024-12-26 | 32K / 64K | DeepSeek License / DeepSeek License |
أداء المعايير
| المعيار | DeepSeek V2 | DeepSeek V3 | الفائز |
|---|---|---|---|
| ARC | 92.1 | — | A |
| BBH (BIG-Bench Hard) | 70.5 | 84.9 | B |
| GPQA | 31.5 | — | A |
| GSM8K (Grade School Math 8K) | 78.8 | 89.3 | B |
| HumanEval | 75.7 | 82.6 | B |
| IFEval | 78.6 | — | A |
| MATH | 35.2 | 61.6 | B |
| MMLU (Massive Multitask Language Understanding) | 78.2 | 88.5 | B |
| MUSR | 53.4 | — | A |
| WinoGrande | 84.7 | — | A |
مقارنة الأسعار
| الإدخال | الإخراج | قراءة الذاكرة المؤقتة | كتابة الذاكرة المؤقتة |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
لكل مليون رمز — A / B
نقاط القوة & نقاط الضعف
DeepSeek V2
- ✅ 采用 MoE 混合专家架构。
- ⚠️ 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。
رأي المحرر
DeepSeek V2 and DeepSeek V3 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.