Are we using the same
Thing? Sol 6.1 has run <30 t/s for me for weeks.
This is why "tokens per second" alone is a deeply flawed comparator.
This is also why discussions of Chinese models focus on tokens per second- they struggle to compete on intelligence so they dramatically increase effort levels to compensate, meaning they require massive total output tokens.
For example, flash 1017 isn't benchmarked yet, but 0731 required 15.4M tokens to complete the artificial analysis benchmark, and Sol 6.1 high required just 2.8M.
Sol 6.1 uses 2.8M at 64 tok/s = 12h 9m
Flash 0731 reported 149 token/s at 15.4M needed = 28h 42m
And in my example in the first line, scenario A (30 t/s) completes 6 minutes faster than scenario B, despite 10X slower inference.
The best way to answer this question: [Pareto frontier or cost/per task curve](https://api-docs.deepseek.com/img/v4.1_261017_perf_cost_en.p...)
Sol 6.1 High: 50 intelligence, $0.32 per task, 4.4 min per task, 13k output tokens per task
Sol 6.1 Medium: 48 intelligence, $0.21 per task, 2.9 min per task, 8k output tokens per task
Deepseek 4.1 1017: 45 intelligence, $0.26 per task, 4.8 min per task, 89k output tokens per task
If you look at the actual pareto frontier across the full benchmark, Sol 6.1 remains firmly on the pareto line, while deepseek remains firmly under it, just as it was before https://i.imgur.com/N72p5NF.png
This result is exactly as I expected, and seems to run counter to the effusive praise of this thread. Sol 6.1 Medium is producing higher quality output at a lower price with nearly 10X less output tokens! And this is not surprising.
And finally, Mimo V2.6 Pro continues to look like a stunning release, clearly smarter, cheaper and faster than deepseek v4.1 1017