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MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis

Xiaomi's MiMo-V2.6-Pro scored 46 on the Artificial Analysis Intelligence Index, well above the median of 18 for comparable open weight models, according to Artificial Analysis. The reasoning model has 1.0T total parameters with 42B active per token, a 1M-token context window, supports text, image, speech, and video input, and is priced at $0.43 per 1M input tokens and $0.87 per 1M output tokens, with a total cost of $206.66 to evaluate on the Intelligence Index. MiMo-V2.6-Pro runs at 125 tokens per second and is released under an MIT license with weights on Hugging Face.

read5 min views1 publishedSep 22, 2026
MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis
Image: source

Model 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).

Reasoning Yes This 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 42B Number of parameters active per token during inference
License MIT

| Model weights | Hugging Face | 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

IntelligenceUpdated #

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Measures the performance of models on specific capabilities and industries

Artificial Analysis Finance & Accounting Index

Intelligence Evaluations

[AA-Briefcase v1.1](https://artificialanalysis.ai/evaluations/aa-briefcase)Updated

Agentic knowledge work, (Elo-500)/2000

[GDPval-AA v2.1](https://artificialanalysis.ai/evaluations/gdpval-aa)Updated

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

[AutomationBench-AA](https://artificialanalysis.ai/evaluations/automationbench-aa)Updated

Agentic SaaS workflows

Agentic coding & terminal use

Coding

Reasoning & knowledge

GDP.pdfNew Professional document reasoning, All-pass

Physics reasoning

Knowledge

1 - hallucination rate

Long context reasoning

Legal agentic work, criterion pass rate

Agentic business operations

Quantitative analysis on spreadsheets & documents

Agentic tool use

Kubernetes incident root-cause analysis

Visual reasoning

MLCR-AANew Medical long context reasoning

AA-Briefcase v1.1Updated

AA-Briefcase Elo

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

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

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).

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). 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.

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

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).

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.

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

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

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

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.

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

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

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

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.

Yes, MiMo-V2.6-Pro is available via API through 1 provider. [Compare API providers](https://artificialanalysis.ai/models/mimo-v2-6-pro/providers)

MiMo-V2.6-Pro is available through 1 API provider. [Compare providers](https://artificialanalysis.ai/models/mimo-v2-6-pro/providers)
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