Xiaomi

MiMo v2.6 FlashOpen

Xiaomi open-weights hybrid active parameter MoE running at 100+ tok/s with 1M context and frontier terminal agent benchmarks.

#27released Oct 2, 2026·Open Weights·310B/15B MoE
textimage1M ctx
Intelligence
88.4 #27
AAQI 88.0
Output Speed
118 t/s
ITL 8.5 ms/tok
Blended price (3:1)
$0.18 /1M
In $0.1/M · Out $0.3/M
Context
1M
≈ 2,500 A4 pages · max out 32,768

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

MiMo v2.6 Flash
Claude Mythos Preview (#1)
Average (68)
Coding (86)Mathematics (85)Hard Science (GPQA) (87)Agentic & Tool Use (84)Knowledge (MMLU) (84)Vision / Multimodal (87)

Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.

Strengths & Trade-offs

Where it wins

  • Fastest open-weights flagship — 118 tok/s
  • SWE-bench-tier coding at flash pricing ($0.10/$0.30)
  • 1M context self-hostable for regulated stacks
  • Strong thinking/non-thinking dual-mode scores

Trade-offs to watch

  • Nuance and long-tail reasoning below frontier closed models
  • 310B weights still need serious VRAM even at 15B active
  • Smaller ecosystem than DeepSeek/Qwen

Killer Use Cases

High-throughput coding agents
Flash-speed agent loops at open-model prices.
On-prem copilots
Self-hosted coding assistants for enterprises.
Batch document processing
1M-context extraction at $0.10/M input.

Developer Quickstart & API

Set MIMO_API_KEY first — get an API key
curl https://api.mimo.mi.com/v1/chat/completions \
  -H "Authorization: Bearer $MIMO_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "mimo-v2.6-flash",
    "messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
  }'

Official Resources & Links

API deployment

Compare hosts & latency

Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
View providers matrix →

Scores by Source

Head-to-head Live Matchups

Live Specs & Architecture

Under the hood
310B hybrid MoE, ~15B active per token
  • Hybrid active-parameter MoE — 310B total, ~15B live per token
  • 1M context at 100+ tok/s sustained
  • Open weights under a permissive license
  • Pretraining-to-posttraining pipeline detailed in the MiMo paper
Release date
Oct 2, 2026
Architecture
310B hybrid MoE, ~15B active per token
Parameters
310B/15B MoE
License
Open Weights
Context Window
1,000,000 tokens
Max Output
32,768 tokens
Modalities
text + image
Cache Pricing
read $0.02 · write $0.1 /1M
Reasoning
—
Input Price
$0.1/M
Output Price
$0.3/M
Output Speed
118 t/s
Time to First Token
—
Data Updated
Oct 4, 2026

Estimated monthly bill

Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...

Cite & embed

GitHub Markdown badge
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BibTeX
@misc{llmpodium2026mimov26flash,
  title = {Benchmark Analysis and Intelligence Evaluation of MiMo v2.6 Flash},
  author = {LLMPodium Research},
  year = {2026},
  url = {https://llmpodium.com/models/mimo-v2-6-flash}
}

Embed Score Badge

Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.

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MiMo v2.6 Flash LLMPodium Score
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