Why high: an exact fingerprint shared with 40 models that declare the same family, without a second signal of a different kind yet.
Qwen: Qwen3 Coder Next is Alibaba (Qwen)'s model. Its measured tokenizer sits with the Qwen group, which is evidence that it builds on the Qwen tokenizer. Tokenizer reuse is normal engineering, open vocabularies travel between labs, and this says nothing against Alibaba (Qwen)'s authorship of the model itself.
| We checked | What we found | Where it came from |
|---|---|---|
| How it counts tokens | Counts every one of the 50 test strings exactly like 40 other models | tk_5410b38e |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_ce94462c |
| How much it can read and write | Reads up to 262,144 tokens at onceOpenRouter's listing shows 235,929 output tokens, which is 90% of the context window, the figure it carries where the provider declares no maximum. | its own listing |
| Who served our requests | Parasail | we measured it, 21 August 2026 |
Click a row to open the full comparison.
We sent Qwen: Qwen3 Coder Next fifty short pieces of text and recorded what each one cost it in tokens. The bars below are those costs. Two models built on the same tokenizer produce the same bars; a model built on a different one produces a different set, which is what makes this a fingerprint.
Overhead subtracted: 8 prompt tokens.
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Supported parameters
frequency_penaltylogit_biaslogprobsmax_tokenspresence_penaltyrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
defaults: {"temperature":1,"top_p":0.95,"frequency_penalty":null}
