MiMo-V2-Flash is Xiaomi’s open-source AI model, released in December 2025. While its bigger sibling MiMo-V2-Pro grabbed headlines by being mistaken for DeepSeek V4, Flash quietly became one of the most popular open-source models for developers who want to self-host or need ultra-cheap inference.
The specs
| MiMo-V2-Flash | |
|---|---|
| Architecture | Mixture-of-Experts (MoE) |
| Total parameters | 309B |
| Active parameters | 15B per token |
| Context window | 56K tokens |
| Speed | 150 tokens/sec |
| Pricing (API) | $0.10/$0.30 per million tokens |
| Open source | Yes (HuggingFace) |
| SWE-Bench Verified | 73.4% (#1 open-source) |
The key insight: 309B total parameters but only 15B active per request. That’s the MoE trick — you get the knowledge of a massive model with the inference cost of a small one.
What makes it special
It’s the fastest model in its class. 150 tokens per second is significantly faster than most models at this capability level. The hybrid sliding-window attention architecture (128-token window, 5:1 ratio) is what enables this — it processes nearby tokens cheaply and only uses full attention for long-range dependencies.
It’s genuinely good at coding. 73.4% on SWE-Bench Verified makes it the #1 open-source model for real-world coding tasks. That’s comparable to Claude Sonnet 4.5 — a closed-source model that costs roughly 30x more.
Multi-Token Prediction (MTP). Instead of predicting one token at a time, Flash predicts multiple tokens simultaneously. This is a key reason for the speed advantage.
It’s actually open source. Weights are on HuggingFace. You can download it, run it locally, fine-tune it. No API dependency required.
How it compares
| Model | SWE-Bench | Pricing (in/out) | Open source |
|---|---|---|---|
| MiMo-V2-Flash | 73.4% | $0.10/$0.30 | ✅ Yes |
| MiMo-V2-Pro | ~80%+ | $1.00/$3.00 | ❌ No |
| DeepSeek V3.2 | 65.4% | $0.28/$1.10 | ✅ Yes |
| Claude Sonnet 4.5 | 72.8% | $3.00/$15.00 | ❌ No |
| Claude Opus 4.6 | 84.2% | $5.00/$25.00 | ❌ No |
Flash sits in a sweet spot: better than DeepSeek V3.2 on coding, comparable to Claude Sonnet, and dramatically cheaper than both closed-source options.
When to use MiMo-V2-Flash
Use Flash when:
- You need fast, cheap inference at scale
- You want to self-host and control your data
- Coding tasks where “good enough” beats “perfect”
- High-volume processing where cost matters more than peak quality
- You’re building prototypes and iterating quickly
Use MiMo-V2-Pro instead when:
- You need the best possible agent performance
- Complex multi-step workflows requiring deep reasoning
- Tasks that benefit from the 1M token context window
- You don’t need open-source weights
Use Claude/GPT instead when:
- Absolute accuracy is critical
- You need the most reliable instruction following
- Enterprise compliance requirements
How to access it
Via API (cheapest): Available on OpenRouter at $0.10/$0.30 per million tokens. Uses the standard OpenAI-compatible format.
Self-hosted: Download weights from HuggingFace. Requires significant GPU resources due to the 309B total parameter count, but the 15B active parameters mean inference is manageable on modern hardware.
Free tiers: Several platforms offer free access including Kilo Code and Puter.js.
The bottom line
MiMo-V2-Flash is the model that makes you question why you’re paying for closed-source APIs. It’s not the best model available — MiMo-V2-Pro and Claude Opus are both better. But it’s open source, blazing fast, and costs almost nothing. For the majority of development tasks, that’s more than enough.
Related: MiMo-V2-Pro vs MiMo-V2-Flash — Which Xiaomi Model Should You Use?
Related: The Complete MiMo-V2 Family Guide — Pro, Flash, Omni, and TTS
Related: MiMo-V2-Flash vs DeepSeek V3 — Open-Source AI Showdown