DeepSeek V4 Pro 0813: Intelligence, Performance and Price Analysis

DeepSeek V4 Pro 0813 (Reasoning, Max Effort) scores 53 on the Artificial Analysis Intelligence Index, well above the median of 27, and is priced at $0.43 per 1M input tokens and $0.87 per 1M output tokens, with a total evaluation cost of $135.03. The model, which has a 1M token context window and 1600B total parameters (49B active), outputs text at 83 tokens per second, faster than the average of 66, according to Artificial Analysis.

DeepSeek V4 Pro 0813 Reasoning, Max Effort Intelligence, Performance & Price Analysis Model summary DeepSeek V4 Pro 0813 Reasoning, Max Effort is amongst the leading models in intelligence and reasonably priced when comparing to other open weight models of similar size. It's also faster than average, however somewhat verbose. The model supports text input, outputs text, and has a 1M tokens context window. DeepSeek V4 Pro 0813 Reasoning, Max Effort scores 53 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models median: 27 . When evaluating the Intelligence Index, it generated 130M tokens, which is somewhat verbose in comparison to the median of 100M. Pricing for DeepSeek V4 Pro 0813 Reasoning, Max Effort is $0.43 per 1M input tokens somewhat expensive, median: $0.33 and $0.87 per 1M output tokens moderately priced, median: $1.20 . In total, it cost $135.03 to evaluate DeepSeek V4 Pro 0813 Reasoning, Max Effort on the Intelligence Index. At 83 tokens per second, DeepSeek V4 Pro 0813 Reasoning, Max Effort is faster than average 66 . | Reasoning | Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist. | |---|---| | Input modality | Supports: text | | Output modality | Supports: text | | Context window | 1M ~1500 A4 pages of size 12 Arial font | | Total parameters | 1600B | | Active parameters | 49B Number of parameters active per token during inference | Metrics are compared against models of the same class: - Non-reasoning models → compared only with other non-reasoning models - Reasoning models → compared across both reasoning and non-reasoning - Open weights models → compared only with other open weights models of the same size class: - Tiny: ≤4B parameters - Small: 4B–40B parameters - Medium: 40B–150B parameters - Large: 150B parameters - Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio: - <$0.15 per 1M tokens - $0.15–$1 per 1M tokens - $1 per 1M tokens Highlights Intelligence Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index by Open Weights / Proprietary Intelligence Evaluations Agentic real-world work tasks, Elo-500 /2000 𝜏³-Banking /evaluations/tau3-banking Updated Agentic tool use Agentic coding & terminal use Coding Humanity's Last Exam /evaluations/humanitys-last-exam Updated Reasoning & knowledge Scientific reasoning Physics reasoning AA-Omniscience Accuracy /evaluations/omniscience Updated Knowledge 1 - hallucination rate AA-LCR /evaluations/artificial-analysis-long-context-reasoning Updated Long context reasoning Agentic knowledge work, Elo Agentic SaaS workflows Legal agentic work, criterion pass rate Agentic business operations Quantitative analysis on spreadsheets & documents Instruction following Long-horizon agentic tasks Kubernetes incident root-cause analysis Visual reasoning AA-Omniscience AA-Omniscience Index Openness Index Artificial Analysis Openness Index: Score Intelligence Index Comparisons Intelligence Index vs. Cost per Intelligence Index Task Token Use Output Tokens per Intelligence Index Task Cost Cost per Intelligence Index Task Cost to Run Artificial Analysis Intelligence Index Pricing: Cache Hit, Input, and Output Context Window Context Window Speed Measured by Output Speed tokens per second Output Speed Time per Intelligence Index Task Latency Measured by Time seconds to First Token Latency: Time To First Answer Token End-to-End Response Time Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed End-to-End Response Time Model Size Open Weights Models Only Model Size: Total and Active Parameters Frequently Asked Questions Common questions about DeepSeek V4 Pro 0813 Reasoning, Max Effort DeepSeek V4 Pro 0813 Reasoning, Max Effort was released on August 13, 2026. DeepSeek V4 Pro 0813 Reasoning, Max Effort was created by DeepSeek. DeepSeek V4 Pro 0813 Reasoning, Max Effort scores 53 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size median: 27 . DeepSeek V4 Pro 0813 Reasoning, Max Effort generates output at 83.2 tokens per second based on DeepSeek's API , which is above average compared to other open weight models of similar size median: 66.2 t/s . DeepSeek V4 Pro 0813 Reasoning, Max Effort has a time to first token TTFT of 1.63s based on DeepSeek's API , which is better than average compared to other open weight models of similar size median: 1.89s . DeepSeek V4 Pro 0813 Reasoning, Max Effort costs $0.43 per 1M input tokens better than average, median: $0.56 and $0.87 per 1M output tokens very competitive, median: $2.20 , based on DeepSeek's API. DeepSeek V4 Pro 0813 Reasoning, Max Effort costs $0.43 per 1M input tokens and $0.87 per 1M output tokens based on DeepSeek's API . For a blended rate 7:2:1 cache hit/input/output ratio , this is $0.18 per 1M tokens. Pricing may vary by provider. Compare provider pricing /models/deepseek-v4-pro/providers When evaluated on the Intelligence Index, DeepSeek V4 Pro 0813 Reasoning, Max Effort generated 130M output tokens, which is somewhat higher than average compared to other open weight models of similar size median: 100M . Yes, DeepSeek V4 Pro 0813 Reasoning, Max Effort is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer. DeepSeek V4 Pro 0813 Reasoning, Max Effort supports text input. DeepSeek V4 Pro 0813 Reasoning, Max Effort supports text output. No, DeepSeek V4 Pro 0813 Reasoning, Max Effort does not support image input. It can only process text. No, DeepSeek V4 Pro 0813 Reasoning, Max Effort is not multimodal. It only supports text input. DeepSeek V4 Pro 0813 Reasoning, Max Effort has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request. Yes, DeepSeek V4 Pro 0813 Reasoning, Max Effort is open weights. The model weights are publicly available. DeepSeek V4 Pro 0813 Reasoning, Max Effort has 1.6 trillion parameters 49 billion active . DeepSeek V4 Pro 0813 Reasoning, Max Effort is a Mixture of Experts MoE model with 1.6 trillion total parameters, but only 49 billion active parameters are used during inference. DeepSeek V4 Pro 0813 Reasoning, Max Effort achieves a score of 53 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding. Yes, DeepSeek V4 Pro 0813 Reasoning, Max Effort is available via API through 1 provider. Compare API providers /models/deepseek-v4-pro/providers DeepSeek V4 Pro 0813 Reasoning, Max Effort is available through 1 API provider. Compare providers /models/deepseek-v4-pro/providers