Cost-Optimised AI
Replace expensive GPT-4 API calls with Qwen2.5 72B at 80–90% lower cost — for high-volume workloads where cost is the primary constraint.
Alibaba Qwen
Alibaba Qwen
Cost-efficient open AI built on Qwen
Alibaba's open-weight Qwen models deliver competitive quality at a fraction of the cost — ideal for high-volume workloads, multilingual applications and cost-conscious deployments.
Qwen2.5 / QwQLatest models
MultilingualEN, ZH, HI + more
Cost-efficientVs GPT-4
Models We Work With
Every Qwen model, for every workload
Flagship
Qwen2.5 72B
Alibaba's best open-weight model — competitive with GPT-4 on code, maths and reasoning at a fraction of the API cost.
Efficient
Qwen2.5 7B / 14B
Smaller Qwen2.5 models that outperform similarly-sized competitors — ideal for self-hosted deployments with limited GPU resources.
Reasoning
QwQ-32B
Qwen's reasoning-focused model with chain-of-thought capabilities — used for maths, science and complex problem-solving tasks.
Vision
Qwen2-VL
Qwen's multimodal model — accepts text and images, with strong performance on document understanding and visual Q&A.
Code
Qwen2.5-Coder
Qwen's code-specialist model — strong performance on code generation, debugging and code review across 40+ languages.
Audio
Qwen Audio
Qwen's audio-language model for speech understanding, audio transcription and voice-based AI applications.
What We Build
Qwen-powered applications built to scale
Multilingual Applications
Qwen has particularly strong Chinese, Hindi and Southeast Asian language support — ideal for AU/IN businesses serving multilingual markets.
Code Generation Tools
Qwen2.5-Coder is among the best open-source coding models — use for internal coding assistants, code review and automated testing.
Maths & Science AI
QwQ-32B for educational platforms, scientific analysis and quantitative reasoning — chain-of-thought for step-by-step problem solving.
Private Deployments
Self-hosted Qwen on your infrastructure — all the capability of a frontier model with full data privacy and no per-token costs.
Document Processing
High-volume document extraction, classification and summarisation — Qwen2.5's long context and accuracy make it efficient for document workflows.
What We Deliver
Every Qwen project includes
✓Model selection across Qwen2.5 / QwQ / Qwen-VL
✓Self-hosted deployment on your infrastructure or cloud
✓Quantisation (AWQ / GGUF) for cost and speed optimisation
✓OpenAI-compatible API endpoint setup
✓Fine-tuning pipeline if domain adaptation is needed
✓RAG integration with your data sources
✓Multilingual prompt engineering and testing
✓Production monitoring and cost tracking
FAQ
Common questions
How does Qwen compare to LLaMA and GPT-4?
Qwen2.5 72B is competitive with LLaMA 3.1 70B and within 15–20% of GPT-4 on most benchmarks. It's particularly strong on code and maths, and has better multilingual support.
Is Qwen truly open-source?
Qwen models are available on Hugging Face under open licences for most sizes. Commercial use is permitted — check the specific licence for the model size you need.
Why would I choose Qwen over LLaMA?
Qwen often outperforms LLaMA at the same size, and has stronger Chinese and Hindi language support. If multilingual capability matters, Qwen is frequently our recommendation.
What GPU do I need to self-host Qwen?
Qwen2.5 7B on a single A10G (24GB). Qwen2.5 72B on 2× A100 (80GB) or 4× A10G with quantisation. We spec hardware based on your throughput needs.
Ready to build with Qwen?
Cost-efficient, multilingual, self-hostable — tell us your use case.
Build With Us
Ready to build with AI?
Tell us your use case. We reply within 4 business hours with a practical approach.
AI ServicesView all AI services →
ResponseWithin 4 business hours (AEST)
Tell Us Your Use Case