Artificial Analysis’s model page for Xiaomi MiMo-V2.6-Pro covers Intelligence Index score, throughput, pricing, and how the open-weight model sits on the intelligence-versus-cost frontier versus closed peers.

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Open weights model

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Released September 2026

MiMo-V2.6-Pro Intelligence, Performance & Price Analysis

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Model summary

IntelligenceUpdated

#1 / 114

Artificial Analysis Intelligence Index

4 out of 4 units for Intelligence.

Speed

#12 / 114

124.5

Output tokens per second

4 out of 4 units for Speed.

Cost

#12 / 114

In $0.435Out $0.87Cache Discount 99%

$0.13

Cost per Intelligence Index task

2 out of 4 units for Cost.

Verbosity

#18 / 114

140M

Output tokens from Intelligence Index

3 out of 4 units for Verbosity.

Comparison Summary

MiMo-V2.6-Pro is amongst the leading models in intelligence and reasonably priced when comparing to other open weight models of similar size. It's also notably fast, however somewhat verbose. The model supports text, image, speech, and video input, outputs text, and has a 1M tokens context window.

MiMo-V2.6-Pro scores 46 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 18). When evaluating the Intelligence Index, it generated 140M tokens, which is somewhat verbose in comparison to the median of 140M.

Pricing for MiMo-V2.6-Pro is $0.43 per 1M input tokens (somewhat expensive, median: $0.30) and $0.87 per 1M output tokens (moderately priced, median: $1.13). In total, it cost $206.66 to evaluate MiMo-V2.6-Pro on the Intelligence Index.

At 125 tokens per second, MiMo-V2.6-Pro is notably fast (75).

Technical specifications

Reasoning	YesThis page shows the reasoning version of this model.A non-reasoning variant may also exist.
Input modality	Supports: text, image, speech, and video
Output modality	Supports: text
Context window	1M~1500 A4 pages of size 12 Arial font
Total parameters	1.0T
Active parameters	42BNumber of parameters active per token during inference
License	MIT
Model weights	Hugging Face

114 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

Highlights

Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

Speed

Output tokens per second · Higher is better

Cost per Task

Weighted average cost (USD) per Intelligence Index task · Lower is better

Prompt Options

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: 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

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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 / ProprietaryReasoning / Non-ReasoningText Only / Multimodal Inputs

Artificial Analysis Intelligence Index by Open Weights / Proprietary

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ProprietaryOpen WeightsOpen Weights (Commercial Use Restricted)

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Artificial Analysis Intelligence Index

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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.

Capability Indexes

Measures the performance of models on specific capabilities and industries

Finance & AccountingStrategy & OpsLegalEngineeringEconomics

Artificial Analysis Finance & Accounting Index

Incorporates 7 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, Humanity's Last Exam, AutomationBench-AA, AA-LCR v1.1, GDP.pdf · Higher is better

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Benchmarks

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

CodingAgenticTool UsePrivate DatasetUser InteractionFinanceMedicalLegalIntelligence IndexLong ContextMultimodalInstruction FollowingFaithfulnessWritingBusinessSee more

18 of 26 evaluations

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AA-Briefcase v1.1Updated

Agentic knowledge work, (Elo-500)/2000

GDPval-AA v2.1Updated

Agentic real-world work tasks, (Elo-500)/2000

AutomationBench-AAUpdated

Agentic SaaS workflows

Terminal-Bench 4.0New

Agentic coding & terminal use

SciCode

Coding

Humanity's Last Exam

Reasoning & knowledge

GDP.pdfNew

Professional document reasoning, All-pass

CritPt

Physics reasoning

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AA-LCR v1.1

Long context reasoning

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AA

Agentic business operations

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

𝜏³-Banking

Agentic tool use

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

Visual reasoning

MLCR-AANew

Medical long context reasoning

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Intelligence Evaluation Relevance

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

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Artificial Analysis Intelligence Index

AA-Briefcase v1.1Updated

AA-Briefcase EloAA-Briefcase Rubric Score (%)Analytical Quality & Presentation Elo

AA-Briefcase Elo

AA-Briefcase v1.1 is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better

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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 IndexAA-Omniscience AccuracyAA-Omniscience Hallucination Rate

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.

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AA-Omniscience Index

Openness Index

Openness IndexOpenness Index ComponentsOpenness vs. Intelligence

Artificial Analysis Openness Index: Score

Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)

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Intelligence Index Comparisons

Intelligence Index vs. Cost per TaskIntelligence Index vs. Time per TaskIntelligence Index vs. Output SpeedIntelligence Index vs. End-to-End Response Time

Intelligence Index vs. Cost per Intelligence Index Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

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Most attractive quadrant

Pareto line

Context window: tokens limit · Higher is better

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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.

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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 SpeedOutput Speed by Prompt TypeOutput Speed VarianceOutput Speed Over TimeOutput Speed vs. PriceLatency vs. Output Speed

Output Speed

Output tokens per second · Higher is better

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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).

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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 TaskIntelligence Index vs. Time per TaskCost vs. Time per Task

Time per Intelligence Index Task

Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better

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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

Time To First Answer TokenTime To First TokenLatency by Prompt TypeLatency VarianceLatency Over Time

Latency: Time To First Answer Token

Seconds to first answer token received · Accounts for reasoning model 'thinking' time

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Thinking (reasoning models, when applicable)Input processing

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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 TimeEnd-to-End Response Time by Prompt TypeEnd-to-End Response Time Over Time

End-to-End Response Time

Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better

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Outputting time'Thinking' time (reasoning models)Input processing time

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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

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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.

Model Size (Open Weights Models Only)

Total & Active ParametersIntelligence Index vs. Active ParametersIntelligence Index vs. Total Parameters

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference

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Active ParametersPassive Parameters

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Total Parameters

The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.

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Active Parameters at Inference Time

The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.

Frequently Asked Questions

Common questions about MiMo-V2.6-Pro

When was MiMo-V2.6-Pro released?

MiMo-V2.6-Pro was released on September 21, 2026.

Who created MiMo-V2.6-Pro?

MiMo-V2.6-Pro was created by Xiaomi.

How intelligent is MiMo-V2.6-Pro?

MiMo-V2.6-Pro scores 46 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 18).

How fast is MiMo-V2.6-Pro?

MiMo-V2.6-Pro generates output at 124.5 tokens per second (based on Xiaomi's API), which is well above average compared to other open weight models of similar size (median: 74.8 t/s).

What is the latency of MiMo-V2.6-Pro?

MiMo-V2.6-Pro has a time to first token (TTFT) of 2.34s (based on Xiaomi's API), which is better than average compared to other open weight models of similar size (median: 2.33s).

How much does MiMo-V2.6-Pro cost?

MiMo-V2.6-Pro costs $0.43 per 1M input tokens (better than average, median: $0.45) and $0.87 per 1M output tokens (very competitive, median: $1.68), based on Xiaomi's API.

What is MiMo-V2.6-Pro API pricing?

MiMo-V2.6-Pro costs $0.43 per 1M input tokens and $0.87 per 1M output tokens (based on Xiaomi'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

How verbose is MiMo-V2.6-Pro?

When evaluated on the Intelligence Index, MiMo-V2.6-Pro generated 140M output tokens, which is somewhat higher than average compared to other open weight models of similar size (median: 140M).

Is MiMo-V2.6-Pro a reasoning model?

Yes, MiMo-V2.6-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 MiMo-V2.6-Pro support?

MiMo-V2.6-Pro supports text, image, speech, and video input.

What output modalities does MiMo-V2.6-Pro support?

MiMo-V2.6-Pro supports text output.

Can MiMo-V2.6-Pro process images?

Yes, MiMo-V2.6-Pro supports image input and can analyze, describe, and answer questions about images.

Is MiMo-V2.6-Pro multimodal?

Yes, MiMo-V2.6-Pro is multimodal. It can process text, image, speech, and video input and generate text output.

What is the context window of MiMo-V2.6-Pro?

MiMo-V2.6-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 MiMo-V2.6-Pro open source?

Yes, MiMo-V2.6-Pro is open weights. The model weights are publicly available and can be downloaded for self-hosting.

How many parameters does MiMo-V2.6-Pro have?

MiMo-V2.6-Pro has 1.0 trillion parameters (42 billion active).

What are the active parameters of MiMo-V2.6-Pro?

MiMo-V2.6-Pro is a Mixture of Experts (MoE) model with 1.0 trillion total parameters, but only 42 billion active parameters are used during inference.

What is the license for MiMo-V2.6-Pro?

MiMo-V2.6-Pro is released under the MIT license. This license allows commercial use.

How does MiMo-V2.6-Pro perform on benchmarks?

MiMo-V2.6-Pro achieves a score of 46 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Is MiMo-V2.6-Pro available via API?

Yes, MiMo-V2.6-Pro is available via API through 1 provider. Compare API providers

Where can I use MiMo-V2.6-Pro?

MiMo-V2.6-Pro is available through 1 API provider. Compare providers