Qwen3.8-27B — Specifications
Compilato da Mustafa Ihsan dalla documentazione pubblicata del fornitore · Ultimo aggiornamento
| Sviluppatore | Alibaba |
|---|---|
| Tipo | LLM (dense, multimodal) |
| Modalità | Text, Image, Video → Text |
| Parametri | 27B |
| Finestra contestuale | 256K native (up to 1M) |
| Output massimo | 128K |
| Licenza | Apache 2.0 (open) |
| Pesi aperti | Sì |
| Pubblicato | 2026-08 |
| Prezzo dell’input | $0.50 /1M |
| Prezzo dell’output | $3.00 /1M |
| Provider API | Alibaba Cloud Model Studio (International), OpenRouter; Ollama (local) |
Esegui localmente
| VRAM (4-bit) | ~18 GB (Ollama 4-bit build) |
|---|
Benchmark
| Qwen-reported | Terminal Bench 2.1 (Terminus) 73.0; SWE-bench Pro 61.7 (Qwen3.6-27B: 53.5); NL2Repo-Bench 42.3. Prices shown are Alibaba Cloud Model Studio (International). |
|---|
What is Qwen3.8-27B?
Qwen3.8-27B is the dense, 27-billion-parameter member of Alibaba’s Qwen3.8 family and a native vision-language model: it reads text, images and video and writes text. The weights are on Hugging Face under Apache 2.0, and Alibaba added it to Model Studio (International) on 17 August 2026. It has a 262,144-token native context that Qwen says extends to 1,000,000 tokens, and it thinks by default, though thinking can be switched off per request. Alibaba says it improves on Qwen3.6-27B mainly in coding and office tasks; Qwen reports 61.7 on SWE-bench Pro against 53.5 for Qwen3.6-27B.
Alibaba Cloud Model Studio (International) charges $0.50 per million input tokens and $3.00 per million output tokens, with implicit cache hits at $0.10 per million, and serves it with a 1,000,000-token context and up to 131,072 output tokens. Those are the prices on this page. Qwen says a hosted version on its Qwen Cloud service is coming soon.
For local use, Qwen’s own downloads are the BF16 weights, about 55.6 GB, and an FP8 version. Ollama’s library carries 4-bit builds such as qwen3.8:27b-q4_K_M, an 18 GB download, so plan on a 24 GB GPU. It is the modern counterpart to the April 2025 Qwen3 32B and a step up in size from Qwen3 14B, adding image and video input and a much longer context. For Alibaba’s hosted flagship, see Qwen3.8-Max. Check your quantisation and context length with the Calcolatore VRAM per LLM.
Qwen3.8-27B pricing: API cost per 1M tokens
| Input (per ogni milione di token) | $0.500 |
|---|---|
| Output (per ogni milione di token) | $3.00 |
| Rapporto output/input | 6× |
| Combinato (4:1 in:out) | $1.00 per 1 milione di token |
What Qwen3.8-27B costs per month
Spesa mensile reale con un mix input-to-output 4:1 — il rapporto effettivamente prodotto da un tipico carico di lavoro basato su chat o RAG.
| Carico di lavoro | Token/mese | Costo/mese |
|---|---|---|
| Progetto secondario | 1 milione in ingresso / 0,25 milioni in uscita | $1.25 |
| Piccolo team | 20 milioni in ingresso / 5 milioni in uscita | $25 |
| Produzione | 200 milioni in ingresso / 50 milioni in uscita | $250 |
Calcola i tuoi numeri personalizzati nel Calcolatore dei costi delle API per l'IA.
Cheaper alternatives to Qwen3.8-27B
| Modello | Costo combinato ($/1 milione) | Risparmi |
|---|---|---|
| Llama 3.1 8B aperta | $0.0240 | 98% cheaper |
| Mistral NeMo 12B aperta | $0.0292 | 97% più economico |
| Gemma 3 4B aperta | $0.0600 | 94% cheaper |
Eseguirlo in autonomia o pagare l’API?
Qwen3.8-27B is open-weight, so you can run it yourself. It needs ~18 GB (Ollama 4-bit build) of VRAM at 4-bit. Self-hosting only beats the API once your volume is high enough to keep that hardware busy — the calcolatore self-hosting vs API calcola il punto di pareggio in base al tuo volume di token.
Domande frequenti
How much does Qwen3.8-27B cost per 1M tokens?
Qwen3.8-27B costs $0.500 per 1M input tokens and $3.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $1.00 per 1M tokens.
How much does Qwen3.8-27B cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $25 on Qwen3.8-27B. A side project (1M in / 0.25M out) costs roughly $1.25.
What is a cheaper alternative to Qwen3.8-27B?
Llama 3.1 8B is the strongest cheaper option in our database at $0.0240 per 1M blended — about 98% less than Qwen3.8-27B. It is also open-weight, so self-hosting is an option.
Can I run Qwen3.8-27B locally?
Yes. Qwen3.8-27B is open-weight and needs about ~18 GB (Ollama 4-bit build) of VRAM at 4-bit quantisation.
Why does Qwen3.8-27B charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. Qwen3.8-27B charges 6× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
I prezzi indicati sono le tariffe ufficiali pubblicate per l'API principale del modello e vengono aggiornati man mano che i fornitori li modificano. Sconti per volumi elevati, elaborazione batch e input memorizzati nella cache non sono inclusi. Confronta tutti i modelli fianco a fianco nel database dei modelli AI o il Classifica LLM.