MiMo-V2.6-Pro

Name: MiMo-V2.6-Pro
Author: Xiaomi

Multimodal

Xiaomi

MiMo-V2.6-Pro is Xiaomi's MIT-licensed omnimodal sparse Mixture-of-Experts model with 1.02T total parameters and 42B active parameters. It supports text, image, video, and audio understanding with a 1,048,576-token context window and text output. MiMo-V2.6 scales reinforcement learning across coding, general agents, visual tasks, and cybersecurity. Xiaomi's launch article is dated September 22, 2026; released weights are named MiMo-V2.6-Pro-RL. Benchmark results are Xiaomi-reported release evaluations, distinct from intermediate live-training checkpoints. UltraSpeed serves the same model at higher speed for $4.35 input and $8.70 output per million tokens.

Key Specifications

Parameters

1.0T

Context

1.0M

Release Date

September 22, 2026

Average Score

59.7%

API Documentation Research Paper Model Weights Results Blog

Timeline

Key dates in the model's history

Announcement / Last Update

September 22, 2026

Today

October 5, 2026

Technical Specifications

Parameters

1.0T

Training Tokens

Knowledge Cutoff

Family

Capabilities

MultimodalZeroEval

Pricing & Availability

Input (per 1M tokens)

$0.43

Output (per 1M tokens)

$0.87

Max Input Tokens

1.0M

Max Output Tokens

Supported Features

Function CallingStructured OutputCode ExecutionWeb SearchBatch InferenceFine-tuning

Benchmark Results

Model performance metrics across various tests and benchmarks

Other Tests

Specialized benchmarks

AA Intelligence Index v4.3

AA Intelligence Index v4.3; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

46.3%

Agents' Last Exam

Agents' Last Exam; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

31.6%

AutomationBench v1.0.6

Automation Bench v1.0.6; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

53.1%

CyberGym

CyberGym; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

94.0%

DeepSWE 1.1

DeepSWE v1.1; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

71.9%

ExploitBench

ExploitBench; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

47.9%

ExploitGym

ExploitGym; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

17.8%

GDPval-AA 2.1

GDPVal 2.1 (AA); MiMo-V2.6-Pro. Elo rating; normalized against max_score 3000. • Self-reported

55.8%

JobBench

JobBench; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

62.0%

MiMo Coding Bench

MiMo Code Bench; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

63.2%

MiMo Cyber Bench

MiMo Cyber Bench; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

81.7%

MiMo Visual Coding

MiMo Visual Coding; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

72.3%

OSWorld-Verified

OSWorld-Verified; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

82.0%

Program Bench

ProgramBench; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

26.5%

SEC-bench Pro

SEC Bench Pro; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

66.3%

Terminal-Bench 2.1

Terminal Bench 2.1; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

89.9%

Terminal-Bench 4.0

Terminal Bench 4.0; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

34.9%

Toolathlon-Verified

Toolathlon-verified; MiMo-V2.6-Pro. Published score divided by 100. • Self-reported

76.9%

License & Metadata

License

mit

Announcement Date

September 22, 2026

Last Updated

September 22, 2026

Compare MiMo-V2.6-Pro

All comparisons

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