# DeepSeek-V4-Pro-0813 DeepSeek-V4-Pro-0813 is an AI model released by DeepSeek on Aug 13 2026. It has 1.6T parameters, a 1M context window and open weight. Tracked results include 35% on BullshitBench v2, 80.6% on SWE-Bench Verified and 60% on Humanity's Last Exam (with tools). ## Facts | Field | Value | | --- | --- | | Model | DeepSeek-V4-Pro-0813 | | Developer | DeepSeek | | Release date | Thursday, Aug 13 2026 | | Licensing | Open Weight | | Parameters | 1.6T | | Context window | 1M | ## API pricing All rates in USD per 1,000,000 tokens, pay-as-you-go. | Tier | Input | Cached input | Output | | --- | --- | --- | --- | | Off-peak (including weekends and Chinese public holidays) | $0.66 | $0.022 | $1.98 | | Peak (01:00–04:00 and 06:00–10:00 UTC, Monday–Friday except Chinese public holidays) | $1.32 | $0.044 | $3.96 | Verified October 19, 2026 against the first-party source: https://api-docs.deepseek.com/quick_start/pricing ## Tracked benchmark scores | Benchmark | Score | Source | What it measures | | --- | --- | --- | --- | | BullshitBench v2 | 35% | [BullshitBench](https://github.com/petergpt/bullshit-benchmark) | Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | | SWE-Bench Verified | 80.6% | [BenchLM](https://benchlm.ai), retrieved 2026-08-31 | Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | | Terminal-Bench 2.1 | 87.9% | Lab | Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | | Toolathlon-Verified | 74.1% | Lab | Tests how well the AI uses everyday personal tools and apps to get things done — a human-checked version of Toolathlon. Higher is better. | | BrowseComp | 83.4% | [BenchLM](https://benchlm.ai), retrieved 2026-08-31 | Can the AI browse the web and track down hard-to-find answers? Higher is better. | | CyberGym | 83.3% | Lab | Tests the AI on cybersecurity challenges — finding and exploiting software weaknesses inside a safe sandbox. Higher is better. | | Humanity's Last Exam (no tools) | 42.7% | Lab | Humanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | | Humanity's Last Exam (with tools) | 60% | Lab | Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | | ARC-AGI-2 | 61.3% | [BenchLM](https://benchlm.ai), retrieved 2026-09-28 | Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | | AutomationBench | 31.8% | Lab | Tests whether the AI can run real multi-step business workflows — the kind of end-to-end office processes companies want to automate — from start to finish. Higher is better. | ## About DeepSeek-V4-Pro-0813 DeepSeek V4 Pro 0813 was introduced in August 2026 as the general-availability update to the Pro tier of the V4 family. DeepSeek emphasized stronger agent performance and made the model available through the app, website and API. In the hosted assistant, the updated Pro model was served through the existing Expert Mode. The announcement added selectable low, high and maximum reasoning effort for both V4 Pro and V4 Flash. It also extended to the Pro tier the native Responses API and Codex support that V4 Flash 0731 had introduced, while retaining existing API model names. DeepSeek published the 0813 checkpoint’s weights under the MIT License, providing a self-hosted option alongside the hosted service. ## Questions and answers ### When was DeepSeek-V4-Pro-0813 released? DeepSeek-V4-Pro-0813 was released by DeepSeek on Thursday, Aug 13 2026. ### Who made DeepSeek-V4-Pro-0813? DeepSeek-V4-Pro-0813 was built by DeepSeek. Chinese AI lab known for efficient, open-weight models. Gained attention for strong performance at lower cost. ### How much does DeepSeek-V4-Pro-0813 cost? DeepSeek-V4-Pro-0813 costs $0.66 per million input tokens and $1.98 per million output tokens through the DeepSeek API. Cached input is $0.022 per million tokens. Those are the rates for the “Off-peak (including weekends and Chinese public holidays)” tier; 1 other pricing tier is published for this model. Rates are pay-as-you-go API prices verified against DeepSeek's published pricing on October 19, 2026. ### What benchmark scores did DeepSeek-V4-Pro-0813 get? DeepSeek-V4-Pro-0813 reports 10 tracked benchmark scores — BullshitBench v2: 35%; SWE-Bench Verified: 80.6%; Terminal-Bench 2.1: 87.9%; Toolathlon-Verified: 74.1%; BrowseComp: 83.4%; CyberGym: 83.3%; Humanity's Last Exam (no tools): 42.7%; Humanity's Last Exam (with tools): 60%; ARC-AGI-2: 61.3%; AutomationBench: 31.8%. Tracked scores may come from lab reports or independent benchmarks; source details accompany the benchmark data. ### What is the context window of DeepSeek-V4-Pro-0813? DeepSeek-V4-Pro-0813 has a context window of 1M. Providers may specify separate input and output token limits. ### How many parameters does DeepSeek-V4-Pro-0813 have? DeepSeek-V4-Pro-0813 is reported at 1.6T parameters. ### Is DeepSeek-V4-Pro-0813 open source? Partly. DeepSeek-V4-Pro-0813 is an open-weight model: the trained weights are free to download and run locally or on your own infrastructure, but the training data and code are not fully released and the license may restrict some commercial uses. It is not open source in the strict sense. ### What came before and after DeepSeek-V4-Pro-0813? DeepSeek's previous tracked release was DeepSeek-V4-Flash-0731 on Jul 31 2026, 13 days earlier. It was followed by DeepSeek-V4.1-Flash on Sep 10 2026. --- Canonical page: https://aireleasetracker.com/model/deepseek/deepseek-v4-pro-0813 Site index: https://aireleasetracker.com/llms.txt Source: AI Release Tracker (https://aireleasetracker.com). Most benchmark scores come from lab launch material; gathered results identify the leaderboard that published them.