AI Rate Card

Qwen3.6 35B-A3B vs Qwen3.8 27B: API price and specs

Qwen3.6 35B-A3B is 69% cheaper than Qwen3.8 27B on input price.

Qwen3.6 35B-A3B is 72% cheaper than Qwen3.8 27B on output price.

Qwen3.6 35B-A3B is 71% cheaper than Qwen3.8 27B on a 1M-in / 200k-out workload.

Qwen3.8 27B has a 331.5% larger context than Qwen3.6 35B-A3B.

FieldQwen3.6 35B-A3BQwen3.8 27B
Lowest input, per 1M$0.012$0.039 +225%
Median input, per 1M$0.17$0.40 +136.5%
Lowest output, per 1M$0.09$0.32 +255.6%
Median output, per 1M$1.01$2.50 +148.3%
Lowest unit price——
Cost of 1M in + 200k out$0.03$0.10 +243.3%
Context262K +76.8%1.1M
Max output262K +47.6%500K
Providers27 +43.8%48
RegionsEU, GLOBAL, TW, USAU, CH, CZ, EU, GLOBAL, US
Acceptsaudio, image, image/bmp, image/heic, image/jpeg, image/png, image/tiff, image/webp, text, video, video/mp4, video/quicktime, video/x-flv, video/x-matroska, video/x-ms-wmv, video/x-msvideoapplication/pdf, file, image, image/bmp, image/gif, image/heic, image/jpeg, image/png, image/tiff, image/webp, pdf, text, video, video/mp4, video/quicktime, video/webm, video/x-flv, video/x-matroska, video/x-ms-wmv, video/x-msvideo
Returnstexttext
TypeText modelsText models
Free optionnono
Cheapest providerinferxchutes

Your own workload: how many tokens the model gets (input) and gives back (output) - for example, in a month. The "Cost" row of the table above is recalculated for these numbers, for each model.

Computed from current offers each time the page opens; the best value of a row is bold, the percent is how far behind the best.

Providers selling both

aihubmix, aiml, aki-io, ambient, cortecs, deepinfra, edenai, empiriolabs, fastrouter, huggingface, inferx, io-net, kilo, meganova, mixlayer, moark, nearai, neuralwatt, novita, openrouter, orcarouter, trustedrouter

Frequently asked questions

Which is cheaper, Qwen3.6 35B-A3B or Qwen3.8 27B?

Qwen3.6 35B-A3B is 69% cheaper than Qwen3.8 27B on input price. Qwen3.6 35B-A3B is 72% cheaper than Qwen3.8 27B on output price. Qwen3.6 35B-A3B is 71% cheaper than Qwen3.8 27B on a 1M-in / 200k-out workload.

Which has the larger context, Qwen3.6 35B-A3B or Qwen3.8 27B?

Qwen3.6 35B-A3B: 262K tokens; Qwen3.8 27B: 1.1M tokens.

Where can I use both Qwen3.6 35B-A3B and Qwen3.8 27B?

aihubmix, aiml, aki-io, ambient, cortecs, deepinfra, edenai, empiriolabs, fastrouter, huggingface, inferx, io-net, kilo, meganova, mixlayer, moark, nearai, neuralwatt, novita, openrouter, orcarouter, trustedrouter