LLM Reference

DeepSeek V2

Released
2024-05-06
Last refreshed
2026-04-19
Status
Researched 55d ago
Open WeightsCommercial use allowedRAGLong contextClassificationJSON / Tool use

DeepSeek V2 is worth evaluating for rag, long context, and classification when its provider route and context window match the workload.

Use it for

  • Teams evaluating rag, long context, and classification
  • Workloads that can use a 128k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Vision or document-understanding workloads
Specifications
Released
2024-05-06
Context
128k
Parameters
236B
Architecture
Mixture of Experts
Specialization
general
Openness
Open weights
License
DeepSeek LicenseCommercial use allowed
Training
finetuned
Fine-tuning
base
Created by

Advancing artificial general intelligence (AGI).

Hangzhou, Zhejiang, China
Founded 2023
Website
Pricing
Output / 1M
$0.280
Input / 1M
$0.140

Cheapest of 1 route · DeepSeek Platform

About

DeepSeek-V2 with Mixture of Experts. 236B total parameters with 21B active. 128K context window.

DeepSeek V2 is an open-weight model. The structured metadata tracks a 128k-token context window and structured outputs. This page tracks provider routes through DeepSeek Platform, with the cheapest tracked route listed at $0.14 input and $0.28 output per 1M tokens. No headline benchmark score is tracked for DeepSeek V2 yet.

Top use-case fit

RAG

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Classification

Included by capability and metadata signals in the decision map.

Capabilities

Structured Outputs

Benchmark peer barsfor RAG

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.