Model
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MiMo-V2.6-Pro

OPEN
Xiaomi · MiMo family · released Sep 22, 2026

Xiaomi's 2026-09-22 flagship, released with open MIT weights alongside a technical report, training environments and RL code. Same 1.02T / 42B MoE scale as V2.5-Pro but now natively omnimodal (text, image, video, audio); the release centres on a single mixed RL run across coding, agent, visual and cybersecurity tasks plus multi-teacher on-policy distillation (MOPD2). Xiaomi's table shows huge gains over V2.5-Pro (DeepSWE v1.1 19.0 -> 71.9, Terminal Bench 2.1 65.2 -> 89.9) and a CyberGym 94.0, while ExploitBench (47.9) stays far behind the closed frontier (70-78.5). API price unchanged at $0.435/$0.87 per Mtok; an UltraSpeed serving tier is sold separately.

ReasoningCodingVisionFunction callingTool useAgentic
3019.9
Elo · rank #5
Parameters
1020B
Active params
42B (MoE)
Context
1M tokens
Architecture
Sparse MoE, 1.02T total / 42B active; 70 layers (60 SWA / 10 GA), 384 routed experts with 8 active, no shared experts; 681M MiMo ViT + 308M AudioTokenizer + 127M audio patch encoder; 5-layer MTP speculative decoder predicting 7 tokens. Natively omnimodal (unlike text-only V2.5-Pro)
License
MIT
Languages
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API price (in/out)
$0.435 / $0.87
Modalities
text · vision · audio · video
Benchmark results
Bar shows position within the tracked field; marker = field best
AutomationBenchAgents53.1%#2
best: DeepSeek-V4.1-Flash · 54.8%
CyberGymCoding94.0%#2
best: MiMo-V2.6-Flash · 95.1%
DeepSWECoding71.9%#7
best: Gemini 4 Argon · 77.9%
ExploitBenchAgents47.9%#6
best: GPT-6 Astra · 100.0%
JobBenchAgents62.0%#4
best: Claude Opus 5 · 65.7%
OSWorld-VerifiedAgents82.0%#5
best: Claude Fable 5 · 85.0%
SEC-Bench ProCoding66.3%#1
best: this model · 66.3%
Terminal-Bench 2.0Coding89.9%#2
best: DeepSeek-V4.1-Flash · 90.6%
Terminal-Bench 4.0Agents34.9%#12
best: Claude Sonnet 5.5 · 70.6%
best: GLM-5.3-Flash · 78.4%
Run it locally
VRAM @ Q4
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VRAM @ FP16
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Fits on (Q4)
Multi-node cluster required
Throughput data unavailable.
Quantizations
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Fine-tune it
Permissive
QLoRA693.6 GB4× B200 192GB
LoRA2172.6 GBbeyond 8× B200
Full fine-tune16371.0 GBbeyond 8× B200
QLoRA SFT on ~10k samples ≈ $15.02 (4× B200 192GB)
API price $0.435/$0.87 · each benchmark row carries its own source badge (see methodology)