4 ms·
Qwen 3.6 is ~$2/m tok, 3.8 should be drop in replacement. Gemma 31B is $0.34/m tok. The price differential on these models is massive on openrouter.
by piyh 1mo ago
Qwen 3.6 is ~$2/m tok, 3.8 should be drop in replacement. Gemma 31B is $0.34/m tok. The price differential on these models is massive on openrouter.
- jjice 1mo agoWhere do you see that? From what I can see on Open Router, Qwen 3.6 27B (the closest dense equivalent to Gemma 31) is $0.28/m. Am I missing something? https://openrouter.ai/qwen/qwen3.6-27b https://openrouter.ai/qwen/qwen3.6-27b
- deleted 1mo ago[deleted]
- satvikpendem 1mo agoThey're comparing Qwen 3.8 Max to Gemma 31B, fundamental mistake.
- deleted 1mo ago[deleted]
- piyh 1mo agoYour own link says: In / Out Price $0.289 / $2.40per 1M
- SparkyMcUnicorn 1mo agoYeah, I would appreciate if someone could make sense of the pricing differences between these models. How can a provider run DSv4F at lower cost than a 27B dense or 35B A3B model? Does it come down to utilization and/or specific model tricks and efficiencies (attention, kv cache, etc.)? DeepInfra prices: Qwen 3.6 27B: $0.32 in / $3.20 out Gemma 3 27B: $0.08 in / $0.16 out DeepSeek V4 Flash 0731: $0.08 in / $0.18 out Qwen 3.6 35B A3B: $0.10 in / $0.95 out https://openrouter.ai/qwen/qwen3.6-27b https://openrouter.ai/qwen/qwen3.6-27b https://openrouter.ai/google/gemma-3-27b-it https://openrouter.ai/google/gemma-3-27b-it https://openrouter.ai/qwen/qwen3.6-35b-a3b https://openrouter.ai/qwen/qwen3.6-35b-a3b https://openrouter.ai/deepseek/deepseek-v4-flash-0731 https://openrouter.ai/deepseek/deepseek-v4-flash-0731
- mordae 1mo agoDeepSeek V4 Flash is natively FP4 MoE with very compact KV cache. Say 8 GB/s. Qwen 27B is about 60 GB/s at full FP16 precision.
- SparkyMcUnicorn 1mo agoIf active weight bandwidth is everything, then wouldn't Qwen 35b a3b (FP8) be roughly half the cost of dsv4f (FP4)? dsv4f appears bigger and more memory/computationally expensive to run any way I look at it.
- mordae 1mo agoYeah, it should be basically free. No idea why it is not. I guess KV cache taking up RAM and possibly bad business sense or amortized engineering costs, I honestly do not know.
- petu 1mo ago> and more memory/computationally expensive to run any way I look at it. Just speculating, but look at attention. 35B-A3B context is heavier -- about 20GB per 1M tokens vs ~7GB. So if you have ≥10M tokens of context per inference node, then DS4 Flash uses less memory than Qwen 35B. Qwen attention is probably more computationaly expensive as well. Also I guess not much interest/competition in serving Qwen edge model.
- satvikpendem 1mo agoWhy are you comparing a 2.4 trillion Max model to a 31 billion model?