Key features
- 50+ open-source models: Llama 3, Mistral, Qwen, DeepSeek via APAC API
- LoRA fine-tuning: APAC domain-specific model fine-tuning with hosted deployment
- Dedicated instances: reserved GPU capacity for APAC production SLAs
- Competitive pricing: lower per-token cost than APAC cloud provider managed inference
- OpenAI SDK: APAC drop-in compatible (base_url + api_key swap)
- APAC models: Qwen 2.5 and regional open-source model access
Best for
- APAC developers and AI teams building applications on open-source LLMs who need a cost-effective managed inference API with fine-tuning capability — particularly APAC teams evaluating Qwen and other APAC-optimized open models for regional language tasks.
Limitations to know
- ! Open-source only — APAC teams needing GPT-4o or Claude must use multiple providers
- ! Performance varies by model — APAC latency benchmarking required before production commitment
- ! Data sovereignty concerns — APAC enterprise teams must review Together AI data handling policies
About Together AI
Together AI is an open-source LLM cloud platform providing API access to 50+ open-source models — including Llama 3.1 (8B, 70B, 405B), Mistral 7B, Mixtral 8x7B, Qwen 2.5, DeepSeek, Code Llama, and specialized APAC task models — via an OpenAI-compatible API. APAC developers and AI teams use Together AI as a managed alternative to self-hosting open-source models when APAC GPU infrastructure is not available.
Together AI's per-token pricing makes open-source inference economically accessible for APAC development teams — Llama 3.1 8B costs $0.0002/1K tokens on Together AI versus $0.0006/1K on AWS Bedrock for the same model. For APAC prototype and development workloads, this price difference enables faster APAC experimentation without AWS Bedrock minimum commitments.
Together AI's fine-tuning service accepts JSONL training data and produces a hosted API endpoint for the fine-tuned model — APAC teams building domain-specific assistants (APAC legal, financial, technical support) can fine-tune Llama on proprietary APAC data and deploy without managing APAC training or inference infrastructure. Fine-tuning on Together AI uses LoRA adapters for efficiency, reducing APAC training costs versus full fine-tuning.
Together AI's dedicated instances allow APAC enterprise teams to reserve exclusive GPU capacity for consistent APAC inference performance — avoiding shared infrastructure latency variability for APAC production applications that require predictable response times. Dedicated Together AI instances are priced per hour rather than per token, suitable for APAC high-volume inference workloads.
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