Author's Description
Note that this is a base model mostly meant for testing, you need to provide detailed prompts for the model to return useful responses. DeepSeek-V3 Base is a 671B parameter open Mixture-of-Experts (MoE) language model with 37B active parameters per forward pass and a context length of 128K tokens. Trained on 14.8T tokens using FP8 mixed precision, it achieves high training efficiency and stability, with strong performance across language, reasoning, math, and coding tasks. DeepSeek-V3 Base is the pre-trained model behind [DeepSeek V3](/deepseek/deepseek-chat-v3)
Key Specifications
Supported Parameters
This model supports the following parameters:
Performance Summary
DeepSeek V3 Base, a 671B parameter open Mixture-of-Experts (MoE) model, demonstrates exceptional speed and competitive pricing. It consistently ranks among the fastest models and offers highly competitive pricing across all evaluated benchmarks. Created on March 29, 2025, with a substantial context length of 163840, this base model is designed for testing and requires detailed prompts for optimal performance. In terms of benchmark performance, DeepSeek V3 Base exhibits varying capabilities. Its highest accuracy was observed in Coding (24.1%) and General Knowledge (17.6%), placing it in the 18th and 13th percentile respectively. However, performance in Ethics (13.0% accuracy) and Email Classification (10.0% accuracy) was notably lower, ranking in the 11th and 4th percentile. A significant weakness is evident in Instruction Following, where it achieved 0.0% accuracy. While its cost efficiency is generally good, particularly in General Knowledge and Ethics, its duration for tasks like Ethics and Email Classification is quite high, indicating slower processing times despite its overall speed ranking. This suggests that while the model is fast, its accuracy on certain tasks needs improvement.
Model Pricing
Current Pricing
Feature | Price (per 1M tokens) |
---|---|
Prompt | $0.2 |
Completion | $0.8 |
Price History
Available Endpoints
Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
---|---|---|---|---|
Chutes
|
Chutes | deepseek/deepseek-v3-base | 163K | $0.2 / 1M tokens | $0.8 / 1M tokens |
Benchmark Results
Benchmark | Category | Reasoning | Strategy | Free | Executions | Accuracy | Cost | Duration |
---|
Other Models by deepseek
|
Released | Params | Context |
|
Speed | Ability | Cost |
---|---|---|---|---|---|---|---|
DeepSeek: DeepSeek V3.2 Exp | Sep 29, 2025 | — | 131K |
Text input
Text output
|
★★★ | ★★★★★ | $$$ |
DeepSeek: DeepSeek V3.1 Terminus | Sep 22, 2025 | ~671B | 131K |
Text input
Text output
|
★★★★ | ★★★★★ | $$$$ |
DeepSeek: DeepSeek V3.1 | Aug 21, 2025 | ~671B | 131K |
Text input
Text output
|
★★ | ★★★★ | $$$ |
DeepSeek: DeepSeek V3.1 Base Unavailable | Aug 20, 2025 | ~671B | 163K |
Text input
Text output
|
★ | ★ | $$ |
DeepSeek: R1 Distill Qwen 7B Unavailable | May 30, 2025 | 7B | 131K |
Text input
Text output
|
★ | ★ | $$$$ |
DeepSeek: DeepSeek R1 0528 Qwen3 8B | May 29, 2025 | 8B | 131K |
Text input
Text output
|
★★★ | ★★★ | $$ |
DeepSeek: R1 0528 | May 28, 2025 | ~671B | 128K |
Text input
Text output
|
★★★ | ★★★ | $$$ |
DeepSeek: DeepSeek Prover V2 | Apr 30, 2025 | ~671B | 131K |
Text input
Text output
|
★★ | ★★★★ | $$$$ |
DeepSeek: DeepSeek V3 0324 | Mar 24, 2025 | ~685B | 163K |
Text input
Text output
|
★★★★ | ★★★★★ | $$ |
DeepSeek: R1 Distill Llama 8B Unavailable | Feb 07, 2025 | 8B | 32K |
Text input
Text output
|
★ | ★★ | $$ |
DeepSeek: R1 Distill Qwen 1.5B Unavailable | Jan 31, 2025 | 5B | 131K |
Text input
Text output
|
★★★ | ★ | $$$ |
DeepSeek: R1 Distill Qwen 32B | Jan 29, 2025 | 32B | 131K |
Text input
Text output
|
★ | ★★★★ | $$$ |
DeepSeek: R1 Distill Qwen 14B | Jan 29, 2025 | 14B | 32K |
Text input
Text output
|
★ | ★★ | $$$ |
DeepSeek: R1 Distill Llama 70B | Jan 23, 2025 | 70B | 131K |
Text input
Text output
|
★★★ | ★★★★★ | $$ |
DeepSeek: R1 | Jan 20, 2025 | ~671B | 128K |
Text input
Text output
|
★★★ | ★★★★ | $$$ |
DeepSeek: DeepSeek V3 | Dec 26, 2024 | — | 163K |
Text input
Text output
|
★★★ | ★★★★ | $$$ |