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DeepSeek-V3 vs Gemini 2.0 Flash

Rows highlighted in warm gray are where the models differ. Numbers carry their as-of date and primary source.

Specs

Field A: DeepSeek-V3 B: Gemini 2.0 Flash
Released 2024-12-11
Developer DeepSeekGoogle DeepMind
Openness OpenProprietary
License DeepSeek LicenseProprietary
OSI-approved nono
Data released nono
Training code nono
Architecture moeunknown
Total params 671B
Active params 37B
Experts 256 (8 active)
Context window 128K1.0M
Attention mlaunknown
Position enc. rope-yarnunknown
Pretraining tokens 14.8T
Post-training sft, grporlhf
Training hardware H800
$/M input $0.40$0.15
$/M output $0.89$0.60
Output tok/sec 00

Benchmarks

Missing scores render as not reported; never inferred. Bold highlights the leader per benchmark.

General reasoning

MMLU 87.1 2024-12-27
MMLU-Pro 75.2 2026-05-21 77.9 2026-05-21
GPQA-Diamond 59.1 2024-12-27 62.3 2026-05-21

Code

HumanEval 65.2 2024-12-27
LiveCodeBench 35.9 2026-05-21 33.4 2026-05-21

Math

MATH 90.2 2024-12-27 93.0 2026-05-21
AIME 2024 25.3 2026-05-21 33.0 2026-05-21
AIME 2025 26.0 2026-05-21 21.7 2026-05-21

Context · A

The cost-quality reset. Pretrained for a reported $5.6M on H800 GPUs (US-export-constrained silicon) and matched closed-frontier benchmarks. Triggered the "DeepSeek moment" in January 2025 when US markets re-priced AI capex assumptions.

Context · B

Google's workhorse Gemini 2.0 checkpoint, released initially as an experimental developer preview. Google positioned it as outperforming Gemini 1.5 Pro on key benchmarks at roughly twice the speed, with native multimodal output (image generation, text-to-speech) and native tool use including Google Search and code execution. The Multimodal Live API added real-time audio and video streaming.

DeepSeek-V3 detail → · Gemini 2.0 Flash detail →