 | Qwen 3 Baseline: 36 trillion tokens Qwen 3.5 Description: Described as having a *significantly larger scale of visual-text tokens* compared to Qwen 3. Multimodal Factor: Transition from text-only training to native visual-text (multimodal) training increases total token volume due to image-text pair encoding and richer data representation. **Conservative Estimate: 42–48 trillion tokens** Reasoning:
This range stays conservative while avoiding speculative overestimation. **Sources:** [link] [comments] |
Token Estimate for Qwen 3.5-397B. Based on official source only :)
Reddit r/LocalLLaMA / 4/20/2026
💬 OpinionSignals & Early TrendsIdeas & Deep AnalysisModels & Research
Key Points
- The article estimates that Qwen 3.5-397B was trained on about 42–48 trillion tokens, starting from an assumed baseline of 36T tokens for Qwen 3.
- It attributes the increase mainly to the shift from text-only training to native multimodal (visual-text) training, which encodes image-text pairs and adds extra token streams.
- The estimated range is described as conservative, reflecting an implied 15–30% growth over the 36T figure rather than speculative extrapolation.
- It cites official Qwen blog posts for Qwen 3 and Qwen 3.5 as the basis for the estimate.
- The core takeaway is that multimodal training can substantially raise effective token volume even at the same overall model size class.
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