Xiaomi MiMo Hits 1,000 Tokens/Second on a Trillion-Parameter Model Using Standard GPUs

The UltraSpeed mode is not a new model class but an engineering-driven serving mode layered on top of MiMo-V2.5-Pro, a 1.02-trillion-parameter Mixture-of-Experts architecture with 42 billion active parameters and a 1-million-token context window .

Three Techniques Behind the Speedup

Xiaomi's official documentation describes a full-stack model-system co-design that combines three coordinated techniques to push throughput past 1,000 tokens/s .

1. FP4 Mixed-Precision Quantization

Only the MoE (Mixture of Experts) expert layers are quantized to FP4 precision, while all other layers retain their original precision . Quantization-aware training (QAT) reduces the model's memory footprint and bandwidth pressure with the goal of maintaining near-lossless quality . This selective approach avoids degrading non-expert components that are more sensitive to precision loss.

2. DFlash Speculative Decoding

DFlash replaces traditional autoregressive draft generation with block-level masked parallel prediction . The draft model uses sliding-window attention (SWA) to keep prediction cost near constant, rather than scaling with sequence length . A Muon optimizer and self-distillation are used to improve acceptance rates, directly boosting inference throughput . In coding scenarios, reports indicate an average accepted length around 6.30 tokens per verification step .

3. TileRT Persistent Kernel Engine with Warp Specialization

The TileRT system abandons the conventional per-operator kernel launch model in favor of a persistent kernel engine where the compute pipeline stays resident on the GPU . Full-pipeline prefetching overlaps data movement with computation, dramatically reducing idle GPU cycles . The system also decomposes communication, data movement, and tensor computation across different warps with dedicated roles, effectively turning the GPU into a continuously flowing, heterogeneous execution system .

Pricing: "3× the Price, 10× the Output Experience"

The UltraSpeed API trial price is set at exactly 3× the standard MiMo-V2.5-Pro output price .

• Standard tier: $0.87 per million output tokens (international) or CN¥6 per million (domestic)
• UltraSpeed trial: $2.61 per million output tokens (international) or CN¥18 per million (domestic)

Input pricing follows the same 3× multiplier, with cache-hit input at $0.0108 per million tokens and cache-miss input at $1.305 per million tokens . Xiaomi markets this as "3× the price, 10× the output experience," emphasizing the roughly 10× throughput gain for 3× the token cost .

Limited Trial Window and Access Rules

The UltraSpeed trial period is explicitly time-boxed: June 9 through June 23, 2026, at 23:59 . Access is application-based due to limited high-speed inference resources, with priority given to enterprise and professional developer use cases .

Approved users receive a free chat experience during the two-week window, subject to fairness rules: a maximum of 10 successful queue entries per account per day, a 30-minute session limit, and automatic resource release after 5 minutes of idle time . Xiaomi does not guarantee review timeliness or approval rates .

Open-Source Release

The underlying model, referred to as MiMo-V2.5-Pro-FP4-DFlash, was released as open-source alongside the UltraSpeed announcement . The FP4-quantized weights and DFlash model checkpoints are available on HuggingFace, consistent with Xiaomi's documentation identifying FP4 quantization and DFlash speculative decoding as core system components .

What This Means for Developers

The UltraSpeed mode demonstrates that trillion-parameter inference at interactive speeds can run on commodity infrastructure without custom silicon, a departure from the specialized-hardware approach seen elsewhere in the industry . For developers building latency-sensitive agentic applications, tool-calling pipelines, or real-time code generation, the combination of high throughput and a 1-million-token context window signals a practical path toward faster, more capable production systems — provided they can gain access during the limited trial window.