Qwen3.8-Flash-Next Intelligence, Performance and Price Analysis

Alibaba's Qwen3.8-Flash-Next, released on August 26, 2026, scores 56 on the Artificial Analysis Intelligence Index, well above the median of 28 for comparable open-weight models, and is priced at $0.15 per 1M input tokens and $0.47 per 1M output tokens. The model supports text, image, and video input, outputs text, has a 256k token context window, and uses 6B active parameters out of 180B total.

Qwen3.8-Flash-Next Intelligence, Performance & Price Analysis 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 - $0.15–$1 per 1M tokens - $1 per 1M tokens Highlights Speed Intelligence Artificial Analysis Intelligence Index /evaluations/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 /models/qwen3-8-flash-next/providers 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