Quick Take

Google’s Gemini 3.5 Flash (released May 19, 2026) and Xiaomi’s MiMo-V2.5 (released April 22, 2026) represent two different approaches to mid-tier model deployment. Gemini 3.5 Flash prioritizes raw output speed and coding utility, whereas MiMo-V2.5 focuses on high-level reasoning and cost-effectiveness.

Benchmark Read

MiMo-V2.5 leads in overall intelligence with an index of 49 compared to Gemini 3.5 Flash’s 43.3. In specific benchmarks, MiMo-V2.5 outperforms Gemini in GPQA (0.849 vs 0.828), HLE (0.252 vs 0.231), IFBench (0.671 vs 0.473), LCR (0.627 vs 0.533), and notably in TAU2 (0.906 vs 0.588). Conversely, Gemini 3.5 Flash demonstrates stronger coding capabilities with a 47.1 index versus MiMo-V2.5’s 42.1, and it maintains a higher score in SciCode (0.488 vs 0.431) and TerminalBench Hard (0.462 vs 0.417). Math index data remains unavailable for both models.

Cost and Speed

There is a significant disparity in pricing. Gemini 3.5 Flash costs $1.50/1M input and $9.00/1M output, resulting in a blended cost of $3.38/1M. MiMo-V2.5 is substantially more affordable, with a blended cost of $0.72/1M ($0.36 input / $1.80 output).

Regarding performance, Gemini 3.5 Flash is built for speed, delivering 225.728 tokens per second with a time-to-first-token of 0.891s. MiMo-V2.5 is slower, outputting at 91.485 tokens per second with a time-to-first-token of 2.699s.

Best Fit

Gemini 3.5 Flash is optimized for high-velocity development environments where latency is the primary bottleneck. Its coding index and rapid response times make it ideal for real-time code completion and interactive agentic tasks.

MiMo-V2.5 is best suited for resource-intensive reasoning tasks and large-scale data processing where cost-per-token is a critical factor. Its superior performance in benchmarks like TAU2 and IFBench suggests better instruction following and complex task execution.