Atlas / Models / DeepSeek / DeepSeek: DeepSeek V3 0324

DeepSeek: DeepSeek V3 0324✓ Catalog verified

deepseek/deepseek-chat-v3-0324

DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the DeepSeek V3 model and performs really well on a variety of tasks.

Input price
$0.20 /1M
Output price
$0.77 /1M
Context
164K
Modalities
text
Released
Mar 24, 2025
Tool calling
✓ Yes
Atlas signal
85/100
01

Overview

DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the DeepSeek V3 model and performs really well on a variety of tasks.

Access: available through the official DeepSeek API. Context window: 164K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Aug 5, 2026
02

Specifications

API identifierdeepseek/deepseek-chat-v3-0324
ProviderDeepSeek
Model typeText LLM
Context window164K catalog
Input modalitiestext
Output modalitiestext
ReleasedMar 24, 2025
TokenizerDeepSeek
ModeratedNo
Architecture modalitytext->text
Supported parameters
frequency_penaltylogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Source: provider documentation + catalog feedMethodology →
03

Pricing

Live pricing components for deepseek/deepseek-chat-v3-0324 as published in the catalog.

$0.20
Input /1M
$0.77
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$2e-7$0.20 / 1MPer input token
Completion tokens$7.7e-7$0.77 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.25Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool Calling✓ SupportedSupports tools / function calling
Self-Hosting✓ SupportedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

DeepSeek: DeepSeek V3 0324
MMLU Signal (Reasoning)
91signal
Coding Signal (HumanEval proxy)
88signal
Math Signal (GSM8K proxy)
83signal
Science Signal (GPQA proxy)
79signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call DeepSeek: DeepSeek V3 0324 through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-chat-v3-0324",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does DeepSeek: DeepSeek V3 0324 cost?

$0.20 per 1M input tokens and $0.77 per 1M output tokens on the official DeepSeek API.

What is the context window of DeepSeek: DeepSeek V3 0324?

DeepSeek: DeepSeek V3 0324 supports up to 164K tokens of context.

Does DeepSeek: DeepSeek V3 0324 support tool / function calling?

Yes, DeepSeek: DeepSeek V3 0324 supports tool / function calling — you can register tools and the model will emit structured tool calls.

How do I access DeepSeek: DeepSeek V3 0324?

Use the official DeepSeek API with the model id `deepseek/deepseek-chat-v3-0324`. See the Quick start section above for code examples.