High-Throughput MoE with Full 1M Context Window
MiMo-V2.6-Flash is Xiaomi's speed-optimized MoE model, delivering instantaneous response times and exceptional throughput while preserving a full 1,048,576-token context window.
15B Active Parameter Efficiency
Featuring 309 billion total parameters with 15 billion active per token, Flash is built for massive concurrency and sub-second time-to-first-token.
Full 1,048,576-Token Memory
Zero compromises on memory: feed entire documentation sites, high-volume transaction logs, or extensive codebases into a high-speed inference pipeline.
Same inputs as Pro
Text, images, video, and audio in. Text out.
Rate on this page
Input $0.14 and output $0.28 per million tokens, about one third of Pro. The figures at the top of the page are the billed rates.
Engineered for High-Concurrency Production Pipelines
Engineered for scenarios where throughput, latency, and operational cost dictate success.
Sub-Agent Swarms & Task Fanouts
The ideal engine for parallel worker agents, iterative search loops, automated data reconciliation, and autonomous task triage pipelines.
Wire-Speed Code Review & Linting
Rapidly scan pull requests, verify syntax and style conformance, suggest inline optimizations, and generate unit tests at wire speed.
Scaled Document Parsing & JSON Extraction
Parse thousands of unstructured invoices, PDFs, reports, and multimodal captures into clean, validated JSON schemas with minimal latency.
Low-Latency Real-Time Conversational UX
Deliver snappy, responsive conversational experiences for customer service, educational tutoring, and live copilots without lag.
Hybrid Fleet Design: The 80/20 Production Blueprint
80% Workload Allocation to Flash
Route 80% of daily conversational volume, data triage, summarizing, and initial drafting to Flash for maximum throughput and minimal bill size.
Instant Escalation to Pro
When an edge case requires multi-repository architectural reasoning or complex mathematical verification, seamlessly elevate that prompt to MiMo V2.6 Pro.
Up to 131,072 Output Tokens
Unlike typical lightweight models that limit generation size, Flash can emit up to 128K tokens when large synthetic data or reports are required.
Flat Rates with No Cliff Multipliers
Consistent token pricing across the entire 1M context span, with no penalty tiers or unexpected surges as prompt size grows.
Drop-in Deployment in Two Steps
Deploy MiMo V2.6 Flash with standard OpenAI-compatible libraries in seconds.
Configure Standard OpenAI Client
Set base URL to https://aireiter.com/api/v1 and provide your AIReiter API key. Compatible with all major orchestration frameworks.
Execute High-Speed Completion Request
POST https://aireiter.com/api/v1/chat/completions Authorization: Bearer $AIREITER_API_KEY Content-Type: application/json { "model": "mimo-v2.6-flash", "messages": [ {"role": "user", "content": "Extract all line items and tax totals from this invoice into structured JSON."} ], "temperature": 0.1 }
Scale Across Workers
High concurrency limits and rapid token emission make Flash the optimal choice for multi-tenant background workers and batch jobs.
MiMo V2.6 Flash Technical FAQ
Architecture details, performance metrics, and deployment tips.
/ 01Is Flash's context window smaller than Pro's?
No. Both MiMo V2.6 Flash and Pro share the exact same 1,048,576-token context window and 128K maximum generation limit.
/ 02What makes Flash significantly faster and cheaper?
Flash activates approximately 15 billion parameters per token (out of 309B total MoE), compared to Pro's 42 billion, cutting computational latency by more than 60%.
/ 03Does Flash support multimodal inputs like images and audio?
Yes. Flash natively processes text, image files, video frame sequences, and audio inputs with full feature parity.
/ 04Which model identifier should I send in API calls?
Specify mimo-v2.6-flash in the model field of your Chat Completions request.
/ 05When should I upgrade a request to MiMo V2.6 Pro?
Upgrade when tasks require deep multi-file architectural refactoring, complex mathematical proofs, or exhaustive cross-domain verification where deep reasoning is essential.