+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
DeepSeek-V3 vs Gemini 1.0 Pro
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 33.6% higher average benchmark score. DeepSeek-V3 offers 221.2K more tokens in context window than Gemini 1.0 Pro. DeepSeek-V3 is $0.63 cheaper per million tokens. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
+
+
+
+
DeepSeek
DeepSeek-V3 is a language model developed by DeepSeek. It achieves strong performance with an average score of 67.2% across 20 benchmarks. It excels particularly in DROP (91.6%), CLUEWSC (90.9%), MATH-500 (90.2%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
+
+
+
+
Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
10 months newer
Gemini 1.0 Pro
2024-02-15
DeepSeek-V3
DeepSeek
2024-12-25
Pricing Comparison
Cost per million tokens (USD)
+
+
+
+
DeepSeek-V3
Input:$0.27
Output:$1.10($0.63 cheaper)
+
+
+
+
Gemini 1.0 Pro
Input:$0.50
Output:$1.50
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
+
+
+
+
DeepSeek-V3
Average Score:49.8%(+33.6%)
+
+
+
+
Gemini 1.0 Pro
Average Score:16.1%
+
+
+
+
Knowledge Cutoff
Training data recency comparison
Gemini 1.0 Pro
2024-02-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
+
+
+
+
Gemini 1.0 Pro
+
+
+
+
DeepSeek-V3
Avg Score:49.8%(+33.6%)
Providers:1
+
+
+
+
Gemini 1.0 Pro
Avg Score:16.1%
Providers:1