DeepSeek V3
Open-weight LLM built for long-context text tasks.
DeepSeekLanguage ModelsOpenII 10.4
Model page Updated 2026-06-18
About DeepSeek V3
DeepSeek V3 uses a transformer design that accommodates very long input sequences without truncation. Its open-weight release allows users to inspect, modify, and run the model on their own hardware. This approach emphasizes transparency and community-driven adaptation.
A primary strength is the extensive context window, which supports coherent processing of lengthy documents or multi-turn dialogues. Open weights remove licensing barriers, enabling fine-tuning for specialized domains while preserving core functionality.
Common applications include code assistance, technical writing support, and research experiments that require sustained context. Users typically deploy it in local or cloud environments where full control over weights and inference settings is desired.
Capabilities
Long-context reasoning
Code generation and debugging
Mathematical problem solving
Multilingual text generation
Instruction following
Chain-of-thought reasoning
Benchmarks & performance
Independent evaluation scores and measured speed.
10.4
Intelligence Index
16.4
Coding Index
8.8
Agentic Index
Source: Artificial Analysis
How DeepSeek V3 compares
DeepSeek V3 (striped bar) vs other language models on intelligence, speed and price.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · DeepSeek V3 ranks #49 of 69
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Solar Pro 314
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Price
USD per 1M output tokens · Lower is better · DeepSeek V3 ranks #75 of 147
$0.78
$0.78
$0.78
$0.78
$0.79
$0.80
$0.80
$0.80
$0.80
Skyfall 36B V2$0.80
Coder Large$0.85
Trinity Large Thinking$0.85
$0.85
Llama 3.1 Euryale 70B v2.2Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Analyzing lengthy technical documents
DeepSeek V3 handles inputs up to 131072 tokens, enabling detailed reasoning across full research papers or code repositories in a single pass.
Debugging complex software projects
The model generates and debugs code while applying chain-of-thought reasoning to identify issues in large multi-file codebases.
Solving advanced mathematics problems
It delivers step-by-step solutions for mathematical tasks, combining mathematical problem solving with instruction following for clear explanations.
Strengths & limitations
Strengths
- +Strong coding and math performance
- +Efficient large-scale inference
- +Open weights availability
- +Handles 128k token contexts well
Limitations
- –Text-only modality
- –No native vision or multimodal support
- –Standard LLM hallucination risks
Cost calculator
Estimate what DeepSeek V3 would cost for your usage.
$0.00060
per request
$6
estimated / month
Based on DeepSeek V3's $0.20/1M input · $0.80/1M output. Estimate only — actual cost varies by provider and caching.
Download & self-host DeepSeek V3
This is an open-weight model. Download the weights from Hugging Face or load it directly with Transformers.
685B
Parameters (safetensors)
2,527,350
Monthly downloads
1,448
Hugging Face likes
Download · transformers
# Install the Hugging Face CLI
pip install -U "huggingface_hub[cli]"
# Download the model weights
hf download deepseek-ai/DeepSeek-V3.2
# Or load it directly in Python
from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("deepseek-ai/DeepSeek-V3.2")
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-V3.2", device_map="auto")Inference providers
Hosted APIs that serve DeepSeek V3 (via Hugging Face Inference Providers).
novitafeatherless-ai
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
JavaScript · openai
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "deepseek/deepseek-chat",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: deepseek/deepseek-chat
Editor's verdict
Our take on DeepSeek V3
DeepSeek V3 is DeepSeek's open-weight language models with a 131K-token context window.
On independent testing it scores 10.4 on the Artificial Analysis Intelligence Index.
At $0.80 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it (685B parameters) or call it through a hosted API.
Best suited to strong coding and math performance and efficient large-scale inference.
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Frequently asked questions
DeepSeek V3 provides a context window of 131072 tokens.
User reviews
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