3 ms·

If the performances are comparable, and there is no evidence it's not. in/out ($) Gemini : 1.5 / 9.0 | Qwen 3.8: 0.15 / 0.47 That is a massive cost reduction.

• killingtime74 8d ago
  You can't just look at the per token cost, but how many tokens it takes on average to do a task. The difference can be massive.
  • vntok 8d ago
    True, but it would have to be more than massive (order(s) of magnitude) to offset that gap.
    • kaliqt 8d ago
      We notice with frontier models like Astra and Fable that one might use a lot less tokens than the other to complete the task thereby being the better deal in spite of the far higher token cost.
      • LeBit 8d ago
        What is Astra $/task? Even if OpenAI end up using 1 token for per task, if the token costs 1M$ , some people will find it expensive.
        • nater5000 8d ago
          https://artificialanalysis.ai/#intelligence-comparison-tabs https://artificialanalysis.ai/#intelligence-comparison-tabs Astra on xhigh has a cost per task of $2.31 with an intelligence index of 53. Qwen3.8 Max has a cost per task of $5.41 with an intelligence index of 45. Pricing for GPT-6 Astra (xhigh) is $10.00 per 1M input tokens and $50.00 per 1M output tokens. Pricing for Qwen3.8 Max (0902) is $2.00 per 1M input tokens and $6.00 per 1M output tokens. Obviously this is just one measure of all of this (and Qwen 3.8 Omni Flash isn't yet available), but I think this illustrates the point well. These relative task costs are pretty consistent across different analysts. Cost per token is arguably a useless measure at this point in most circumstances.
    • alphabettsy 8d ago
      On some benchmarks models like Qwen 3.8 Max which cost < $6/m out cost more than Astra 6 to run at $50/m out. That’s a huge price gap and yet Astra would be cheaper if your work looks like the benchmark.
  • tidbeck 8d ago
    Also cache write/read cost + cache efficiency.
    • npodbielski 8d ago
      Yes, for fun I tried OVH AI Endpoint and they do not have cache read at all. They bill you every time you send a prompt regardless if you are hit cache or not. One agent session was like 80M input and 300K output and I paid 30$ for that. Or rather I interrupted it and let my local Qwen finish it because cost was getting radicoulous.
  • _ache_ 8d ago
    I know, but it's a good enough proxy.
    • nater5000 8d ago
      But it's not lol If Gemini can complete a task for $1 and Qwen completes that same task for $1, then the cost per token is irrelevant in most use-cases. One would think this stuff should correlate well enough that you can use it as a proxy, but I think a lot of people are noticing this is a serious mistake and that these "cheap" models aren't as cheap as they appear when you consider this.
      • _ache_ 7d ago
        You point is valid for textual LLM, with large CoT, not Omni which will respond quick with a voice. In this case, token price is a good enough proxy. What matter the most and isn't told by token price is the latency. You expect a voice LLM to respond very quick. If it takes 5s to response to a simple "Hello, what the weather today?", them not much people will use it.