Model summary
Speed
Qwen3.8-Flash-Next is amongst the leading models in intelligence and reasonably priced when comparing to other open weight models of similar size. The model supports text, image, and video input, outputs text, and has a 256k tokens context window.
Qwen3.8-Flash-Next scores 56 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 28). When evaluating the Intelligence Index, it generated 200M tokens, which is very verbose in comparison to the median of 110M.
Pricing for Qwen3.8-Flash-Next is $0.15 per 1M input tokens (moderately priced, median: $0.30) and $0.47 per 1M output tokens (moderately priced, median: $1.17). In total, it cost $218.39 to evaluate Qwen3.8-Flash-Next on the Intelligence Index.
| Reasoning | Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist. |
|---|---|
| Input modality | Supports: text, image, and video |
| Output modality | Supports: text |
| Context window | 256k ~384 A4 pages of size 12 Arial font |
| Total parameters | 180B |
| Active parameters | 6B Number of parameters active per token during inference |
| License | Qwen Community License 1.0 |
| Model weights | |
Metrics are compared against models of the same class:
- Non-reasoning models → compared only with other non-reasoning models
- Reasoning models → compared across both reasoning and non-reasoning
- Open weights models → compared only with other open weights models of the same size class:
- Tiny: ≤4B parameters
- Small: 4B–40B parameters
- Medium: 40B–150B parameters
- Large: >150B parameters
-
Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:
-
<$0.15 per 1M tokens
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$0.15–$1 per 1M tokens
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$1 per 1M tokens Highlights
Speed
Intelligence #
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Intelligence Evaluations
Agentic real-world work tasks, (Elo-500)/2000 Agentic tool use
Agentic coding & terminal use
Coding
Reasoning & knowledge
Scientific reasoning
Physics reasoning
Knowledge
1 - hallucination rate
Long context reasoning
Agentic knowledge work, Elo
Agentic SaaS workflows
Legal agentic work, criterion pass rate
Agentic business operations
Quantitative analysis on spreadsheets & documents
Instruction following
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
AA-Omniscience
AA-Omniscience Index
Openness Index #
Artificial Analysis Openness Index: Score
Intelligence Index Comparisons #
Intelligence Index vs. Cost per Intelligence Index Task
Token Use #
Output Tokens per Intelligence Index Task
Cost #
Cost per Intelligence Index Task
Cost to Run Artificial Analysis Intelligence Index
Pricing: Cache Hit, Input, and Output
Context Window #
Context Window
Model Size (Open Weights Models Only) #
Model Size: Total and Active Parameters
Frequently Asked Questions #
Common questions about Qwen3.8-Flash-Next
Qwen3.8-Flash-Next was released on August 26, 2026.
Qwen3.8-Flash-Next was created by Alibaba.
Qwen3.8-Flash-Next scores 56 on the Artificial Analysis Intelligence Index, placing it well above average among other open weight models of similar size (median: 28).
Qwen3.8-Flash-Next costs $0.15 per 1M input tokens (very competitive, median: $0.50) and $0.47 per 1M output tokens (very competitive, median: $2.00), based on Alibaba's API.
Qwen3.8-Flash-Next costs $0.15 per 1M input tokens and $0.47 per 1M output tokens (based on Alibaba's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.09 per 1M tokens. Pricing may vary by provider. Compare provider pricing
When evaluated on the Intelligence Index, Qwen3.8-Flash-Next generated 200M output tokens, which is at the higher end compared to other open weight models of similar size (median: 110M).
Yes, Qwen3.8-Flash-Next is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
Qwen3.8-Flash-Next supports text, image, and video input.
Qwen3.8-Flash-Next supports text output.
Yes, Qwen3.8-Flash-Next supports image input and can analyze, describe, and answer questions about images.
Yes, Qwen3.8-Flash-Next is multimodal. It can process text, image, and video input and generate text output.
Qwen3.8-Flash-Next has a context window of 260k tokens. This determines how much text and conversation history the model can process in a single request.
Yes, Qwen3.8-Flash-Next is open weights. The model weights are publicly available and can be downloaded for self-hosting.
Qwen3.8-Flash-Next has 180 billion parameters (6 billion active). Qwen3.8-Flash-Next is a Mixture of Experts (MoE) model with 180 billion total parameters, but only 6 billion active parameters are used during inference.
Qwen3.8-Flash-Next is released under the Qwen Community License 1.0 license. Commercial use is allowed with restrictions.
Qwen3.8-Flash-Next achieves a score of 56 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Yes, Qwen3.8-Flash-Next is available via API through 1 provider. [Compare API providers](/models/qwen3-8-flash-next/providers)
Qwen3.8-Flash-Next is available through 1 API provider. [Compare providers](/models/qwen3-8-flash-next/providers)