DeepSeek-V3
DeepSeek-V3 is an AI model published by DeepSeek-AI, released on 2024-12-26, for Chat model, with 681B parameters, and 128K context length, requiring about 687.9 GB storage, with a 92.30 score on BBH.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Model basics
Open source & experience
Official resources
API details
| Type | Condition | Input | Output |
|---|---|---|---|
| Text | - | $0.270/ 1M tokens | $1.10/ 1M tokens |
| Type | TTL | Write | Read |
|---|---|---|---|
| Text | - | $0.270/ 1M tokens | $0.070/ 1M tokens |
| Text | - | $0.270/ 1M tokens Cache = write | — |
| Text | - | — | $0.070/ 1M tokens Cache = hit |
“—” means the modality is not billed in that direction, or the vendor has not published a price for it.
Benchmark Results
DeepSeek-V3 currently shows benchmark results led by HumanEval (18 / 140, score 89), BBH (3 / 21, score 92.30), MMLU (18 / 124, score 88.50). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.
General Knowledge
4 evaluationsCoding and Software Engineer
2 evaluationsMath and Reasoning
5 evaluationsPublisher
Model Overview
DeepSeek-V3 is an AI model published by DeepSeek-AI, released on 2024-12-26, for Chat model, with 681B parameters, and 128K context length, requiring about 687.9 GB storage, with a 92.30 score on BBH.
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