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DeepSeek-V4-Pro-0813

DeepSeek-V4-Pro-0813

Run DeepSeek's current Pro API model with 1M context, 384K maximum output, tool calls, JSON output, Responses API, and Anthropic-compatible access Cut Pro API costs versus the April preview pricing to $0.435 per 1M cache-miss input tokens and $0.87 per 1M output tokens Treat this as a formal Pro model snapshot rather than a separate launch blog: DeepSeek lists the live model version as DeepSeek-V4-Pro-0813

Reviewed by ToolWorthy Editors·updated today·DeepSeek-V4-Pro-0813 released today

Pricing:Free + from $0.44/per 1M cache-miss input tokens
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Pros & Cons

Pros

  • Current official Pro model version gives teams a clearer API target than the April Preview label
  • 1M-token context and 384K maximum output support unusually large research, coding, and document workflows
  • Much lower Pro API pricing than the April preview rates shown in older ToolWorthy content
  • Supports OpenAI-format and Anthropic-format API access, reducing migration work
  • Includes JSON output, tool calls, Responses API support, and dual thinking modes

Cons

  • DeepSeek has not published a separate August launch blog for DeepSeek-V4-Pro-0813
  • The pricing page warns that API prices may increase soon
  • Flash remains far cheaper and has a higher listed concurrency limit
  • Public benchmark deltas for the 0813 snapshot versus the April V4 Preview are not separately published
  • Users need to verify legacy alias behavior instead of relying on deepseek-chat or deepseek-reasoner

Overview

DeepSeek-V4-Pro-0813 is the current Pro model version shown on DeepSeek's official API pricing page. It should be understood as a formal Pro API snapshot in the DeepSeek V4 family, not as a separate product line or a new major-version launch blog. The April 24, 2026 DeepSeek V4 Preview introduced DeepSeek-V4-Pro and DeepSeek-V4-Flash with 1M context, open weights, and dual thinking modes; the current model table now identifies the Pro API model version as DeepSeek-V4-Pro-0813.

For users of DeepSeek, the practical change is clearer than the naming: Pro is now the active high-capability API target alongside Flash, with updated token pricing, a 384K maximum output limit, OpenAI-format and Anthropic-format endpoints, tool calls, JSON output, and Responses API support. Teams choosing between Flash and Pro should treat Pro as the stronger model for difficult reasoning, agentic coding, and long-context knowledge work, while using Flash when cost or concurrency matters more.

What's New

A Current Pro API Snapshot

The official DeepSeek pricing table lists deepseek-v4-pro with model version DeepSeek-V4-Pro-0813. That gives API users a concrete production target instead of relying only on the April V4 Preview label. The model still belongs to the V4 family and keeps the same official endpoint pattern: https://api.deepseek.com for OpenAI-format calls and https://api.deepseek.com/anthropic for Anthropic-compatible access.

1M Context and 384K Maximum Output

DeepSeek lists both V4 Flash and V4 Pro with a 1M-token context length and a maximum output of 384K tokens. That keeps Pro relevant for long-form codebase analysis, research synthesis, contract review, large-document workflows, and agent loops that need room for accumulated state. The output ceiling is unusually high for workflows that generate reports, plans, or multi-file edits in a single call.

Lower Pro API Pricing Than the Preview Page

The April preview content described V4-Pro at much higher API rates. The current official pricing table lists Pro at $0.003625 per 1M cache-hit input tokens, $0.435 per 1M cache-miss input tokens, and $0.87 per 1M output tokens. DeepSeek also notes that it plans to raise API pricing in the near future, so teams should verify the pricing page before committing a long-running workload.

Production API Features

DeepSeek-V4-Pro-0813 supports JSON output, tool calls, the Responses API, Anthropic API compatibility, chat prefix completion, and FIM completion in non-thinking mode. Thinking mode supports both non-thinking and thinking modes, with thinking as the default. For agent builders, the key value is not only model quality; it is being able to keep existing OpenAI or Anthropic client patterns while swapping the base URL and model name.

Compatibility Notes

DeepSeek's April V4 release note said deepseek-chat and deepseek-reasoner would be retired after July 24, 2026, and were then routing to V4 Flash non-thinking and thinking modes. New integrations should call deepseek-v4-pro or deepseek-v4-flash directly instead of relying on legacy aliases.

Existing OpenAI-compatible clients can usually migrate by updating the base URL and model ID. Anthropic-compatible clients should use DeepSeek's Anthropic-format base URL and verify streaming, tool-call, and response-shape assumptions before production rollout.

Pricing & Plans

API Model Cache-Hit Input Cache-Miss Input Output Context Max Output Concurrency
deepseek-v4-pro $0.003625 / 1M tokens $0.435 / 1M tokens $0.87 / 1M tokens 1M 384K 500
deepseek-v4-flash $0.0028 / 1M tokens $0.14 / 1M tokens $0.28 / 1M tokens 1M 384K 2500

Pricing is pay-as-you-go through the DeepSeek API. Cache-hit pricing is only relevant when your prompts reuse cached context. For cold prompts, Pro costs about 3.1x Flash on cache-miss input and output, while Flash provides five times the listed concurrency limit. DeepSeek warns that API prices may rise soon, so current cost estimates should be treated as time-sensitive.

Best For

  • Teams that need DeepSeek's strongest current V4 API model for reasoning, coding, and long-context analysis
  • Agent builders who want OpenAI-compatible or Anthropic-compatible API access with tool calls and JSON output
  • Research and legal workflows that benefit from 1M context and very large generated outputs
  • Cost-sensitive teams comparing Pro only for hard tasks while routing simpler calls to Flash
  • Developers replacing legacy DeepSeek aliases with explicit V4 model IDs

FAQ

Is DeepSeek-V4-Pro-0813 a brand-new major version?

No. It is best treated as the current Pro model snapshot within the DeepSeek V4 family. DeepSeek's official April 24, 2026 post launched DeepSeek V4 Preview, while the current pricing table lists the live Pro API model version as DeepSeek-V4-Pro-0813.

What is the model ID for the API?

Use deepseek-v4-pro for the Pro API model. DeepSeek's pricing page lists its model version as DeepSeek-V4-Pro-0813, but the API model column shows the callable model as deepseek-v4-pro.

How much does DeepSeek-V4-Pro-0813 cost?

The official pricing page lists $0.003625 per 1M cache-hit input tokens, $0.435 per 1M cache-miss input tokens, and $0.87 per 1M output tokens for Pro. DeepSeek says it may raise API prices soon, so verify the current page before production use.

Should I use V4 Pro or V4 Flash?

Use Pro for difficult reasoning, agentic coding, and long-context work where accuracy matters more than raw cost. Use Flash when throughput, lower spend, and a higher listed concurrency limit matter more.

Does it support Anthropic-compatible calls?

Yes. DeepSeek lists both OpenAI-format and Anthropic-format base URLs for V4 Pro and V4 Flash. Teams should still test tool-calling and streaming behavior before switching production workloads.

Version History

DeepSeek-V4-Pro-0813

Current Version

Released on August 13, 2026

+What's new
3 updates
  • Run DeepSeek's current Pro API model with 1M context, 384K maximum output, tool calls, JSON output, Responses API, and Anthropic-compatible access
  • Cut Pro API costs versus the April preview pricing to $0.435 per 1M cache-miss input tokens and $0.87 per 1M output tokens
  • Treat this as a formal Pro model snapshot rather than a separate launch blog: DeepSeek lists the live model version as DeepSeek-V4-Pro-0813

DeepSeek-V4-Flash-0731 Public Beta

Released on July 31, 2026

View Update
+What's new
3 updates
  • Use the formal public-beta DeepSeek-V4-Flash API through the same deepseek-v4-flash model name with no request-format change
  • Evaluate DeepSeek-reported Code Agent scores across Terminal Bench 2.1, NL2Repo, Cybergym, DeepSWE, Toolathlon, and DSBench; no Flash Preview baseline is disclosed
  • Build Codex-style agents with native Responses API support while V4-Pro, DeepSeek APP, and DeepSeek WEB models remain unchanged for now

DeepSeek-V4 Preview

Released on April 24, 2026

View Update
+What's new
3 updates
  • Run million-token coding, reasoning, and agent workflows on DeepSeek-V4-Pro (1.6T/49B active MoE) or faster V4-Flash (284B/13B active MoE)
  • Use V4-Flash at $0.14/M cache-miss input and $0.28/M output, or V4-Pro at $1.74/M cache-miss input and $3.48/M output; open weights are MIT licensed
  • Compare against frontier models with V4-Pro-Max scoring 80.6% on SWE Verified, 67.9 on Terminal Bench 2.0, and leading current open models on knowledge and reasoning

DeepSeek-V3.2

Released on December 1, 2025

+What's new
3 updates
  • Integrate thinking directly into tool use with DeepSeek-V3.2, the first model to support tool-use in both thinking and non-thinking modes
  • Deploy DeepSeek-V3.2 as the official successor to V3.2-Exp, now live across App, Web, and API with general availability
  • Launch DeepSeek-V3.2-Speciale (API-only) alongside, pushing reasoning capabilities further for the most demanding research workloads

DeepSeek-V3.2-Exp

Released on September 29, 2025

+What's new
3 updates
  • Explore DeepSeek Sparse Attention (DSA) for the first time, delivering fine-grained sparse attention that dramatically improves long-context training and inference efficiency
  • Cut API costs by up to 50% compared to V3.1-Terminus while maintaining virtually identical model output quality on most benchmarks
  • Validate architectural optimizations for long-context scenarios on open weights before rolling DSA into the December V3.2 general release

DeepSeek-V3.1-Terminus

Released on September 22, 2025

+What's new
3 updates
  • Get cleaner language consistency across extended conversations, reducing mid-response switching between English and Chinese that appeared in earlier V3.1 output
  • Use stronger Code Agent and Search Agent behaviors with more reliable tool invocation for coding and multi-step web research workflows
  • Tighten the August V3.1 release one month later, preparing the base for V3.2-Exp's sparse-attention experiments

DeepSeek-R1

Released on January 20, 2025

+What's new
3 updates
  • Solve advanced reasoning tasks on math, science, and coding with DeepSeek-R1's reinforcement-learning approach, rivaling OpenAI o1 at a fraction of the cost
  • Score 79.8% pass@1 on AIME 2024 and 97.3% on MATH-500 while running as open weights under MIT license—rare for frontier reasoning models at the time
  • Trigger a global reaction in AI markets, influencing the open-weight and pricing strategies of OpenAI, Meta, and Anthropic in the months that followed

DeepSeek-V3

Released on December 26, 2024

+What's new
3 updates
  • Launch DeepSeek-V3 as a 671B-parameter MoE model with 37B activated per forward pass and 128K context, outperforming most open models on coding and math
  • Cut training cost to roughly $5.6M by combining MoE routing with FP8 mixed-precision training, dramatically undercutting Western frontier model economics
  • Ship open weights for both base and chat variants with full tokenizer and inference code, setting a new bar for open-source frontier model transparency

DeepSeek-V2

Released on May 6, 2024

+What's new
3 updates
  • Release DeepSeek-V2 with a 236B-parameter MoE architecture and 21B activated per token, delivering stronger performance at lower inference cost than dense peers
  • Cut API pricing aggressively—input at roughly 1/100 of GPT-4 at the time—and launch DeepSeek-Coder V2 one month later for dedicated coding workloads
  • Establish the Mixture-of-Experts plus low-price playbook that defines DeepSeek's strategy through the V3, R1, and V4 generations

DeepSeek LLM

Released on November 29, 2023

+What's new
2 updates
  • Launch DeepSeek LLM (7B and 67B dense base and chat variants) as DeepSeek's first public release, matching Llama 2 on general capabilities
  • Publish full training details, tokenizer, and fine-tuned chat variants on Hugging Face under a permissive open-weight license—an early commitment to open-source AI

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