Qwen3.8-Flash-Next
Qwen3.8-Flash-Next is a chat-oriented large language model from Alibaba, part of the Qwen line, with measured throughput of roughly 54 output tokens per second.
API Pricing
Cheapest on Heabsy — 68% below avg
Prices updated daily. Last check: Oct 12, 2026
Compare API pricing for every Qwen model →Qwen3.8-Flash-Next pricing by provider
Input, output, and batch rates, plus alternatives, for one provider at a time.
Performance & Benchmarks
Source: Artificial Analysis →Reasoning & Knowledge
- GPQA Diamond92.3%
- Humanity's Last Exam38.0%
Coding
- SciCode50.6%
Agentic & Tool Use
- Terminal-Bench v2.186.1%
- τ-bench Banking45.4%
Instruction & Long Context
- Long-Context Reasoning79.7%
Benchmarks measured Oct 2026. Scores are independent evaluations, not vendor-reported.
Model Details
General
- Creator
- Alibaba
- Modalities
- Text
Capabilities
- Open Source
- No
Strengths & Limitations
Strengths
- Measured output throughput of approximately 54 tokens per second in independent Artificial Analysis testing, giving a concrete streaming-speed reference point
- Time to first token measured at roughly 1.4 seconds, a figure that can be compared directly against other catalogued chat models
- Part of Alibaba's Qwen line, a family with a broad public track record and multiple deployment options
- Chat-tuned for instruction following and multi-turn dialogue rather than requiring prompt engineering around a base model
- Independent third-party benchmarking data is available, rather than only vendor-reported figures
- Positioned as a "Flash" variant, a naming convention Alibaba has used for responsiveness-oriented serving configurations
Limitations
- We do not currently track a confirmed context window for this model, so long-document workloads need verification against provider documentation
- No confirmed accuracy benchmarks (reasoning, coding, or math scores) are tracked for this entry, making quality comparisons against peers difficult
- Time to first token of roughly 1.4 seconds is a meaningful wait for latency-sensitive interactive interfaces
- Measured generation speed near 54 tokens per second is moderate; workloads that stream very long responses will feel the pacing
- Modality support beyond text is not tracked here, so multimodal requirements should be confirmed before adoption
- Provider availability for this specific variant may be narrower than for more widely hosted Qwen models
Key Features
About Qwen3.8-Flash-Next
Common Use Cases
Qwen3.8-Flash-Next suits general chat and text-generation workloads where a steady streaming response is acceptable: customer-facing assistants, drafting and rewriting copy, summarizing meeting notes or articles, converting unstructured text into structured formats, and internal knowledge-base Q&A. Its measured throughput of roughly 54 output tokens per second and ~1.4 second time to first token make it a reasonable fit for asynchronous or semi-interactive interfaces — batch content processing, background enrichment jobs, and chat surfaces where a short spinner is tolerable — while ultra-low-latency use cases such as voice interfaces or autocomplete may want a model with a shorter first-token delay. Because we do not track confirmed context window or accuracy benchmark data for this variant, teams evaluating it for long-context retrieval pipelines, complex agentic tool chains, or competitive coding tasks should run their own evaluation against the specific provider deployment before committing.
Frequently Asked Questions
How much does Qwen3.8-Flash-Next cost?
Pricing varies by provider and by pricing type — input tokens, output tokens, and any cached or batch rates are typically billed separately, and different hosts set different rates for the same model. Check the pricing table on this page for current per-provider figures rather than relying on a fixed number, since rates change frequently.
What is Qwen3.8-Flash-Next best used for?
It is a chat model, so it fits assistant-style dialogue, summarization, drafting, rewriting, and text-to-structured-data transformation. Its measured throughput of about 54 output tokens per second and roughly 1.4 second time to first token make it workable for streaming chat interfaces and batch text processing, while very latency-sensitive applications may prefer a model with a faster first-token response.
How fast is Qwen3.8-Flash-Next?
Artificial Analysis measured approximately 53.99 output tokens per second of generation throughput and a time to first token of about 1,432 milliseconds. In practice that means a short reply begins appearing after roughly a second and a half, then streams at a moderate pace. Actual results depend on the hosting provider, prompt length, and current load.
Who created Qwen3.8-Flash-Next, and what family is it part of?
It comes from Alibaba and belongs to the Qwen model line. The "Flash" designation in that line has generally been used for variants tuned toward responsive serving rather than maximum parameter count.
What context window does Qwen3.8-Flash-Next support?
We do not currently track a confirmed context window for this specific variant. If your workload depends on long documents or extended conversation history, verify the supported limit with the provider you plan to use — hosted deployments of the same model sometimes cap context below the model's maximum.