Kimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto line

Proprietary model Released October 2026 Kimi K3.1 Pro Intelligence, Performance & Price Analysis Model summary Intelligence Speed Cost Verbosity Comparison Summary Kimi K3.1 Pro is amongst the leading models in intelligence and reasonably priced when comparing to other models of similar price. It's also slower than average and very verbose. The model supports text and image input, outputs text, and has a 1M tokens context window. Kimi K3.1 Pro scores 55 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 27). When evaluating the Intelligence Index, it generated 150M tokens, which is very verbose in comparison to the median of 87M. Pricing for Kimi K3.1 Pro is $2.00 per 1M input tokens (moderately priced, median: $2.00) and $10.00 per 1M output tokens (moderately priced, median: $10.00). On average, it costs $2.11 per task to evaluate Kimi K3.1 Pro on the Intelligence Index. At 73 tokens per second, Kimi K3.1 Pro is slower than average (81). Technical specifications This page shows the reasoning version of this model. A non-reasoning variant may also exist. Supports: text and image Supports: text 217 models in this class 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 Intelligence Speed Cost per Task Intelligence Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them. Artificial Analysis Intelligence Index by Open Weights / Proprietary Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them. Open Weights Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use. Intelligence Index vs. Cost per Task Cost per Intelligence Index Task Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight. Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them. Capability Indexes Measures the performance of models on specific capabilities and industries Artificial Analysis Finance & Accounting Index Benchmarks Evaluations Agentic knowledge work, Elo Knowledge 1 - hallucination rate Agentic SaaS workflows Agentic real-world work tasks, Elo Reasoning & knowledge Professional document reasoning, All-pass Agentic coding & terminal use Long context reasoning Coding Physics reasoning Agentic scientific research workflows in a terminal Agentic software engineering in open-source repositories Quantitative analysis on spreadsheets & documents Legal agentic work, Hallucination-Gated All-Pass Rate Agentic business operations Agentic interactive 3D experiences, Elo Kubernetes incident root-cause analysis Medical long context reasoning Visual reasoning Rich, varied, well-crafted language Well-structured, scannable, answer-first Truthful, acknowledges uncertainty, non-sycophantic Use of filler and generic language Intelligence Evaluation Relevance While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases. Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them. AA-Briefcase v1.1 AA-Briefcase Elo AA-Briefcase Elo AA-Briefcase Elo is a combined metric that aggregates analytical quality Elo, presentation Elo, and rubric pass rate, with rubric performance converted into Elo via synthetic head-to-head matches. Elo and 95% confidence interval bounds are clamped at 0. AA-Omniscience AA-Omniscience Index AA-Omniscience Index AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. Intelligence Index Comparisons Intelligence Index vs. Cost per Task Cost per Intelligence Index Task Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight. Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them. Token Use Output Tokens per Intelligence Index Task Output Tokens per Intelligence Index Task The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats). Cost Cost per Intelligence Index Task Cost per Intelligence Index Task Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight. Cost to Run Artificial Analysis Intelligence Index Cost to Run Artificial Analysis Intelligence Index The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats). Pricing: Cache Hit, Input, and Output Cache Hit Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail. Context Window Context Window Context Window for RAG Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data. Context Window Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model). Speed Measured by Output Speed (tokens per second) Output Speed Output Speed Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming). Model Performance Representation Figures represent performance of the model's first-party API or the median across providers where a first-party API is not available. Time per Intelligence Index Task Time per Intelligence Index Task The weighted average time (seconds) per Artificial Analysis Intelligence Index task. This is calculated by dividing output tokens per task by output speed, weighted by the relative weights of each benchmark in the Intelligence Index. Latency Measured by Time (seconds) to First Token Latency: Time To First Answer Token Time to First Answer Token Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion. 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 End-to-End Response Time Seconds to receive a 500 token response. Key components: Input time: Time to receive the first response token Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details). Answer time: Time to generate 500 output tokens, based on output speed Model Performance Representation Figures represent performance of the model's first-party API or the median across providers where a first-party API is not available. Frequently Asked Questions Common questions about Kimi K3.1 Pro When was Kimi K3.1 Pro released? Kimi K3.1 Pro was released on October 23, 2026. Who created Kimi K3.1 Pro? Kimi K3.1 Pro was created by Kimi. How intelligent is Kimi K3.1 Pro? Kimi K3.1 Pro scores 55 on the Artificial Analysis Intelligence Index, placing it well above average among other models in a similar price tier (median: 27). How fast is Kimi K3.1 Pro? Kimi K3.1 Pro generates output at 73.5 tokens per second (based on Kimi's API), which is below average compared to other models in a similar price tier (median: 81.1 t/s). What is the latency of Kimi K3.1 Pro? Kimi K3.1 Pro has a time to first token (TTFT) of 3.20s (based on Kimi's API), which is better than average compared to other models in a similar price tier (median: 3.62s). How much does Kimi K3.1 Pro cost? Kimi K3.1 Pro costs $2.00 per 1M input tokens (better than average, median: $2.00) and $10.00 per 1M output tokens (better than average, median: $10.00), based on Kimi's API. What is Kimi K3.1 Pro API pricing? Kimi K3.1 Pro costs $2.00 per 1M input tokens and $10.00 per 1M output tokens (based on Kimi's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $1.54 per 1M tokens. Pricing may vary by provider. Compare provider pricing How verbose is Kimi K3.1 Pro? When evaluated on the Intelligence Index, Kimi K3.1 Pro generated 150M output tokens, which is at the higher end compared to other models in a similar price tier (median: 87M). Is Kimi K3.1 Pro a reasoning model? Yes, Kimi K3.1 Pro is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer. What input modalities does Kimi K3.1 Pro support? Kimi K3.1 Pro supports text and image input. What output modalities does Kimi K3.1 Pro support? Kimi K3.1 Pro supports text output. Can Kimi K3.1 Pro process images? Yes, Kimi K3.1 Pro supports image input and can analyze, describe, and answer questions about images. Is Kimi K3.1 Pro multimodal? Yes, Kimi K3.1 Pro is multimodal. It can process text and image input and generate text output. What is the context window of Kimi K3.1 Pro? Kimi K3.1 Pro has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request. Is Kimi K3.1 Pro open source? No, Kimi K3.1 Pro is proprietary. The model weights are not publicly available. How many parameters does Kimi K3.1 Pro have? Kimi K3.1 Pro has 2.8 trillion parameters. How does Kimi K3.1 Pro perform on benchmarks? Kimi K3.1 Pro achieves a score of 55 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding. Is Kimi K3.1 Pro available via API? Yes, Kimi K3.1 Pro is available via API through 1 provider. Compare API providers Where can I use Kimi K3.1 Pro? Kimi K3.1 Pro is available through 1 API provider. Compare providers