Alibaba

Qwen3.8 Flash NextAperto

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

#221rilasciato il 18 ago 2026·Open Weights·Not disclosed
textimagevideo260K ctx
Provider APIOttieni chiave API →Classifica
Intelligenza
66.8 #221
AAQI 61.5
Velocità Uscita
168 t/s
TTFT 210 ms · ITL 6.0 ms/tok
Prezzo combinato (3:1)
$0.19 /1M
Input $0.12/M · Output $0.4/M
Contesto
260K
≈ 650 pagine A4 · output max 8,192

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)

Gli assi radar sono approssimati dai punteggi di categoria dove mancano misurazioni dirette — vedi Metodologia.

Punti di forza e compromessi

Dove vince

  • Open weights — self-host, fine-tune and audit with no vendor lock-in
  • 168 tok/s output — fast enough for real-time agents
  • Sub-400ms time-to-first-token
  • Very low blended price — $0.19/1M mixed tokens

Casi d'uso killer

Real-time agents
Low-latency loops for voice, gaming and interactive copilots.
High-volume batch jobs
Classification, extraction and summarization at minimal cost per call.
Vision & document OCR
Extracts structure from scans, charts, screenshots and mixed-media inputs.

Quickstart per sviluppatori e API

Imposta prima DASHSCOPE_API_KEY — ottieni una chiave API
curl https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "qwen3-8-flash-next",
    "messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
  }'

Risorse e link ufficiali

Deployment API

Confronta host e latenza

Throughput, TTFT e prezzi cache su Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock e Azure.

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Vedi matrice provider →

Punteggi per Fonte

Specifiche live e architettura

Sotto il cofano
  • Prompt caching supported — cached input reads at $0.02/1M tokens.
  • Native multimodality: text, image, video in a single model.
Data di Rilascio
18 ago 2026
Parametri
Not disclosed
Licenza
Open Weights
Finestra di Contesto
260,000 tokens
Output max
8,192 tokens
Modalità
text + image + video
Prezzi cache
lettura $0.02 · scrittura $0.16 /1M
Ragionamento
—
Prezzo Ingresso
$0.12/M
Prezzo Uscita
$0.4/M
Velocità Uscita
168 t/s
Tempo al Primo Token
210 ms
Dati aggiornati
28 ago 2026

Stima bolletta mensile

Spesa mensile stimata
$0.00
Calcolo risparmio vs GPT-4o…

Cita e incorpora

Badge Markdown GitHub
Loading badge markdown...
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}
}

Incorpora il badge del punteggio

Aggiungi un badge Podium Score live al tuo README su GitHub o Hugging Face — rimanda alla classifica live.

Anteprima
Qwen3.8 Flash Next LLMPodium Score
Markdown
Loading badge snippet...
HTML
Loading badge snippet...

Altri modelli di Alibaba

Modelli alternativi

Migliori alternative a Qwen3.8 Flash Next in base a capacità, prezzi e benchmark.

0 / 4