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[ARTICLE · art-140572] src=artificialanalysis.ai ↗ pub= topic=artificial-intelligence verified=true sentiment=· neutral

MiMo-v2.6-Flash: on intelligence/price Pareto frontier

MiMo-V2.6-Flash scored 38 on the Artificial Analysis Intelligence Index, well above the median of 8 for comparable models, according to Artificial Analysis's analysis. The open-weights reasoning model supports text and image input with a 1M-token context window, but is priced at $0.14 per 1M input tokens and $0.28 per 1M output tokens versus medians of $0.07 and $0.22, and runs at 62 tokens per second against an average of 132. Evaluating MiMo-V2.6-Flash on the Intelligence Index cost $0.06 per task and generated 240M tokens, more than double the 100M median.

read4 min views1 publishedSep 27, 2026
MiMo-v2.6-Flash: on intelligence/price Pareto frontier
Image: source

Model summary

MiMo-V2.6-Flash is amongst the leading models in intelligence, but somewhat expensive when comparing to other open weight models of similar size. 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.

MiMo-V2.6-Flash scores 38 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 8). When evaluating the Intelligence Index, it generated 240M tokens, which is very verbose in comparison to the median of 100M.

Pricing for MiMo-V2.6-Flash is $0.14 per 1M input tokens (somewhat expensive, median: $0.07) and $0.28 per 1M output tokens (somewhat expensive, median: $0.22). On average, it costs $0.06 per task to evaluate MiMo-V2.6-Flash on the Intelligence Index.

At 62 tokens per second, MiMo-V2.6-Flash is slower than average (132).

Reasoning Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist.
Input modality Supports: text and image
Output modality Supports: text
Context window 1M ~1500 A4 pages of size 12 Arial font

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

CritPtUnder review Physics reasoning

Knowledge

1 - hallucination rate

Long context reasoning

Legal agentic work, criterion pass rate

Agentic business operations

Agentic scientific research workflows in a terminal

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

MiMo-V2.6-Flash was created by Xiaomi. MiMo-V2.6-Flash scores 38 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 8).

MiMo-V2.6-Flash generates output at 62.4 tokens per second (based on Xiaomi's API), which is below average compared to other open weight models of similar size (median: 132.1 t/s).

MiMo-V2.6-Flash has a time to first token (TTFT) of 3.10s (based on Xiaomi's API), which is at the higher end compared to other open weight models of similar size (median: 2.13s). MiMo-V2.6-Flash costs $0.14 per 1M input tokens (very competitive, median: $0.30) and $0.28 per 1M output tokens (very competitive, median: $0.72), based on Xiaomi's API.

MiMo-V2.6-Flash costs $0.14 per 1M input tokens and $0.28 per 1M output tokens (based on Xiaomi's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.06 per 1M tokens. Pricing may vary by provider. Compare provider pricing

When evaluated on the Intelligence Index, MiMo-V2.6-Flash generated 240M output tokens, which is at the higher end compared to other open weight models of similar size (median: 100M).

Yes, MiMo-V2.6-Flash 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-Flash supports text and image input.

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

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

MiMo-V2.6-Flash 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-Flash is open weights. The model weights are publicly available.

MiMo-V2.6-Flash achieves a score of 38 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

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

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