Xiaomi

MiMo v2.6 FlashTerbuka

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

#27dirilis 2 Okt 2026·Open Weights·310B/15B MoE
textimage1M ctx
Penyedia APIJalankan Model →Peringkat
Inteligensi
88.4 #27
AAQI 88.0
Kecepatan output
118 t/s
ITL 8.5 ms/tok
Harga gabungan (3:1)
$0.18 /1M
Input $0.1/M · Output $0.3/M
Konteks
1M
≈ 2,500 halaman A4 · output maks 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)

Sumbu radar diaproksimasi dari skor kategori jika pengukuran benchmark langsung tidak tersedia — lihat Metodologi.

Kelebihan & Trade-off

Di mana ia menang

  • 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

Hal yang perlu diperhatikan

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

Kasus Penggunaan Killer

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.

Quickstart Developer & API

Atur MIMO_API_KEY dulu — dapatkan kunci API
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."}]
  }'

Sumber Daya & Tautan Resmi

Deployment API

Bandingkan host & latensi

Throughput, TTFT, dan harga cache di Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock, dan Azure.

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Lihat matriks penyedia →

Skor per sumber

Spesifikasi Live & Arsitektur

Di balik kap
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
Tanggal rilis
2 Okt 2026
Arsitektur
310B hybrid MoE, ~15B active per token
Parameter
310B/15B MoE
Lisensi
Open Weights
Jendela konteks
1,000,000 tokens
Output maks
32,768 tokens
Modalitas
text + image
Harga cache
baca $0.02 · tulis $0.1 /1M
Penalaran
—
Harga input
$0.1/M
Harga output
$0.3/M
Kecepatan output
118 t/s
Waktu ke token pertama
—
Data diperbarui
4 Okt 2026

Estimasi tagihan bulanan

Estimasi pengeluaran bulanan
$0.00
Menghitung penghematan vs GPT-4o…

Kutip & sematkan

Badge Markdown GitHub
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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}
}

Sematkan Lencana Skor

Tambahkan lencana Podium Score langsung ke README GitHub atau Hugging Face Anda — menautkan ke peringkat langsung.

Pratinjau
MiMo v2.6 Flash LLMPodium Score
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