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Model garden Router · beschikbaar Dedicated · op aanvraag

Qwen2.5 1.5B Instruct

Direct via de EU-router of als dedicated GPU-deployment. Data blijft in Europa.

Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:

Start gratis ← Alle modellen
Qwen/Qwen2.5-1.5B-Instruct vLLM ready
text->text · Qwen · EU-hosted
1.5B
Parameters
33K
Contextvenster
8GB
Minimale VRAM
POST /api/v1/chat/completions 200 OK

Specificaties

Parameters 1.5B
Contextvenster 32,768 tokens
Minimale VRAM 8 GB
Architectuur Qwen2ForCausalLM (vLLM)
Licentie apache-2.0
Modaliteit text->text
Uitgebracht September 2024
Uitgever Qwen ↗

Prijzen

Gedeelde router · per token
€0.02
Input (per 1M tokens)
€0.05
Output (per 1M tokens)
Dedicated GPU · per uur
Op aanvraag
Dedicated deployment, vanaf 8 GB VRAM. Afgerekend per GPU-uur.

Gedeelde EU-router, pay-per-token, scale-to-zero. Dedicated GPU-deployments worden per uur afgerekend, zie prijzen.

✓ Werkend geverifieerd op 15-07-2026, respons in 793 ms op onze EU-infrastructuur.

Direct aanroepen

Drop-in vervanger voor OpenAI: wijzig alleen de base-URL en de API-key. Ook het Anthropic-formaat (/v1/messages) wordt ondersteund.

curl https://hostyourai.com/api/v1/chat/completions \
  -H "Authorization: Bearer hyai-..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen2.5-1.5B-Instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Veelgestelde vragen

Kan ik Qwen2.5 1.5B Instruct in de EU draaien?

Ja. HostYourAI draait Qwen2.5 1.5B Instruct op GPU's in Europese datacenters via vLLM. Prompts en outputs verlaten de EU niet en er is geen Amerikaanse cloudprovider in de keten.

Is Qwen2.5 1.5B Instruct hosten AVG/GDPR-compliant?

Ja. Alle verwerking vindt plaats binnen de EU, er is een verwerkersovereenkomst (DPA) beschikbaar en de subprocessor-lijst is openbaar. Open-source gewichten betekenen ook: geen training op jouw data.

Wat kost Qwen2.5 1.5B Instruct?

Via de gedeelde EU-router betaal je €0.02 per miljoen input-tokens en €0.05 per miljoen output-tokens, zonder vaste kosten. Voor hoge volumes of isolatie kun je Qwen2.5 1.5B Instruct ook als dedicated GPU-instance per uur draaien.

Is de API compatibel met OpenAI?

Ja. Je gebruikt de standaard OpenAI-SDK's met een aangepaste base-URL (https://hostyourai.com/api/v1). Ook de Anthropic Messages API wordt ondersteund als drop-in.

Andere modellen van Qwen

Qwen3.6 27B FP8

[!Note] This repository contains FP8-quantized model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc. The quantization method is fine-grained fp8 quantization with block size of 128, and its performance metrics are nearly identical to those of the original model.

28B 262K context Bekijk model →
Qwen3.6 27B

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

28B 262K context Bekijk model →
Qwen3.6 35B A3B FP8

[!Note] This repository contains FP8-quantized model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc. The quantization method is fine-grained fp8 quantization with block size of 128, and its performance metrics are nearly identical to those of the original model.

36B 262K context Bekijk model →
Qwen3.6 35B A3B

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

36B 262K context Bekijk model →
Qwen3.5 35B A3B GPTQ Int4

[!Note] This repository contains int4-quantized model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

36B 262K context Bekijk model →
Qwen3.5 0.8B Base

[!Note] This repository contains model weights and configuration files for the pre-trained only model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, etc. The intended use cases are fine-tuning, in-context learning experiments, and other research or development purposes, not direct interaction. However, the control tokens, e.g., <|imstart| and <|imend| were trained to allow efficient LoRA-style PEFT with the official chat template, mitigating the need to finetune embeddings, a significant optimization given Qwen3.5's larger

0.9B 262K context Bekijk model →

Probeer Qwen2.5 1.5B Instruct gratis

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