Alibaba

Qwen3.8 Flash Nextオープン

Alibaba Qwen3.8 Flash Next experimental high-throughput multimodal preview model.

#163リリース日: 2026年8月18日·Open Weights·Not disclosed
textimagevideo260K ctx
API providersランキング
Intelligence
66.8 #163
AAQI 61.5
Output speed
168 t/s
TTFT 210 ms · ITL 6.0 ms/tok
Blended price (3:1)
$0.19 /1M
In $0.12/M · Out $0.4/M
Context
260K
≈ 650 A4 pages · max out 8192

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

Qwen3.8 Flash Next
Claude Mythos Preview (#1)
Average (68)
Coding (60.5)Mathematics (68)Hard Science (GPQA) (66)Agentic & Tool Use (63.5)Knowledge (MMLU) (64)Vision / Multimodal (66)

Radar axes are approximated from category scores where direct benchmark measurements are missing — see 評価方法.

API deployment

Compare hosts & latency

Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
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ソース別スコア

モデル詳細

リリース日
2026年8月18日
パラメータ数
Not disclosed
ライセンス
Open Weights
コンテキストウィンドウ
260,000 tokens
入力価格
$0.12/M
出力価格
$0.4/M
出力速度
168 t/s
最初のトークンまでの時間
210 ms

Estimated monthly bill

Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...

Cite & embed

GitHub Markdown badge
[![LLMPodium Rank](https://llmpodium.com/badge/qwen3-8-flash-next/rank.svg)](https://llmpodium.com/models/qwen3-8-flash-next)
BibTeX
@misc{llmpodium2026qwen38flashnext,
  title = {Benchmark Analysis and Intelligence Evaluation of Qwen3.8 Flash Next},
  author = {LLMPodium Research},
  year = {2026},
  url = {https://llmpodium.com/models/qwen3-8-flash-next}
}

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代替モデル

機能、価格、ベンチマークスコアに基づく Qwen3.8 Flash Next の最適な代替モデル。

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