DeepSeek
DeepSeek V4.1 Flash
Total Context
1M
Max Output
384K
Released
N/A
deepseek-v4-proDeepSeek V4 Pro is a DeepSeek model for complex coding, reasoning-intensive workflows, and high-volume text generation. Use the DeepSeek V4 Pro API through TokenHub to review current API pricing, context length, maximum output, available endpoints, and benchmark results before selecting it for production workloads.
Context Window
1M tokens
Maximum Output
384K tokens
Release Date
Apr 24, 2026
Modalities
| Input Price | Output Price | Cache Read |
|---|---|---|
| $1.2857/M | $3.8571/M | $0.0429/M |
Reasoning
Tool calling
Temperature parameter
Attachments
Knowledge Base
Endpoint Protocols
The defining capabilities of DeepSeek V4 Pro for long-context reasoning, agentic workflows and demanding software engineering tasks.
The production release strengthens autonomous planning, tool use and multi-step task completion for complex agent workflows.
Its evaluated strengths in repository understanding and software engineering support coordinated changes across multiple files.
A one-million-token context window allows the model to work with extensive code, documentation and task histories in a single context.
Low, high and max reasoning levels let developers vary deliberation depth according to task complexity.
Official model weights are available under the MIT License, giving developers the option to run and adapt the model in controlled infrastructure.
Practical workloads that use DeepSeek V4 Pro for repository maintenance, terminal-based engineering, tool-driven automation and long-context analysis.
Analyzes dependencies across a repository, identifies affected files and implements coordinated fixes for reported software issues.
Uses command-line tools to inspect projects, edit code, execute builds and tests, and diagnose failures through iterative checks.
Plans a sequence of tool calls, interprets intermediate results and continues toward a completed workflow or structured deliverable.
Applies extended reasoning to complex mathematics, science, cybersecurity and engineering questions, producing a worked solution or investigation plan.
Reviews large collections of text or source code, traces relationships across distant sections and produces a consolidated analysis.
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 40.8 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 43.2 |
| Knowledge & Reasoning | ||
| GPQA | Advanced science problem solving | 90.5% |
| HLE | Broad expert-level exam set | 33.5% |
| Coding & Engineering | ||
| SciCode | Scientific coding challenges | 46.4% |
| Terminal-Bench Hard | Hard terminal task execution | 41.7% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 71.3% |
| AA-LCR | Long-context reasoning | 65% |
| τ²-Bench | Agent workflow tasks | 94.2% |
Metrics sourced from Artificial Analysis
Answers about the DeepSeek V4 Pro API, pricing, coding and reasoning performance, context length, benchmarks, and model comparisons.
DeepSeek V4 Pro is a DeepSeek model for complex coding, reasoning-intensive workflows, and high-volume text generation. Use this page to review its current API price, context length, maximum output, endpoints, and benchmark results before production use.
DeepSeek V4 Pro is a candidate for complex coding, reasoning, agent workflows, and long-context text analysis. Use the DeepSeek V4 Pro benchmarks on this page to shortlist models, then validate it with your own repository, prompts, tools, latency target, and evaluation set.
Review DeepSeek V4 Pro input, output, and cache-read pricing separately. Long coding or research responses are usually more sensitive to output cost, while repeated long-context prompts can be more sensitive to cache-read pricing.
Choose DeepSeek V4 Pro when complex reasoning, difficult coding, or higher-quality long-form text matter most. Choose DeepSeek V4 Flash when the same workflow is more sensitive to token cost, latency, or batch throughput. Compare both models against your representative tasks before making either the default.
Create a TokenHub API key, use the exact DeepSeek V4 Pro model ID shown on this page, and select an available endpoint. Existing OpenAI-compatible applications can usually keep their request flow and update the API key, Base URL, and model ID.
Choose by workload, not a generic ranking. Compare DeepSeek V4 Pro and Kimi K3 on the modalities you need, API price, output volume, latency, tool use, and results from your own production evaluation.
See the current model data above for DeepSeek V4 Pro context length and maximum output. Context length affects how much source material you can include in one request, while maximum output affects how much content the model can generate in one response.
Use one API key to access DeepSeek V4 Pro and more AI models through TokenHub.
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