Together AI Alternative for India

Together AI users: same class of open models, India-first billing

Together AI is a well-built platform for open-source and hosted inference, but it settles internationally, leaving Indian teams with payment friction and no GST input-tax credit. unoblox runs a comparable class of open-weight and proprietary models — Llama, Qwen, Gemma, DeepSeek, GPT, Claude — through one OpenAI-compatible endpoint, invoiced monthly in rupees.

Feature parity

Aspect	Together AI	unoblox
API style	OpenAI-compatible	OpenAI-compatible
Open-weight models	Llama, Qwen, and others	Llama 4, Qwen3, Gemma 4, DeepSeek, Kimi K2.7
Proprietary models	Limited	GPT, Claude — same key
Embeddings	Yes	Yes — Qwen3-Embedding, ₹0
Billing	International	₹, monthly GST invoice
Infrastructure	International	India (Yotta)

One-line migration

curl -X POST https://api.unoblox.ai/v1/chat/completions \
  -H "Authorization: Bearer ub-gw-..." \
  -H "Content-Type: application/json" \
  -d '{"model": "meta-llama/Llama-4-Maverick", "messages": [{"role": "user", "content": "Hello"}]}'

Same request shape, same response schema — only the host and key change.

Real ₹ pricing (per 1M tokens, input / output)

Model	Input	Output
Llama 4 Maverick	₹20.16	₹80.64
Qwen3 235B-A22B	₹9.07	₹55.44
DeepSeek V4 Flash	₹9.07	₹18.14
Gemma 4 31B	₹13.10	₹38.30
Qwen3 1.7B	₹0	₹0

Anything outside this list — check live rates on /models rather than trust a stale number.

Why teams switch

• No international payment step. Lock in rupee pricing; finance stops tracking a foreign-currency vendor.
• GST input-credit. Claim 18% back on every rupee of eligible spend — roughly ₹18k back per ₹100k billed.
• One endpoint for open-weight and proprietary models. Stop juggling a second API key just to reach GPT or Claude.
• India-hosted. Answers data-residency questions from DPDP and internal security review directly.
• Works with your existing tooling. LangChain, LlamaIndex, and any OpenAI-SDK-based framework point at the new base_url without extra adapters or wrapper libraries.

Frequently asked questions

Do you support custom fine-tuning like Together does? Not yet on the hosted API — we're prioritizing inference breadth first. You can fine-tune open-weight models like Qwen3.8-27B locally with LoRA and serve the adapter yourself.

Does my existing request structure carry over? Yes — headers, stream=True, temperature, top_p, and tool calls all work identically; only base_url and the key change.

What if a model you use gets deprecated upstream? We give 30 days' notice before retiring a model and keep the core lineup (Llama, Qwen, Gemma, DeepSeek) stable long-term.

How reliable is uptime? 99.95% SLA, with a 7-working-day refund path for extended outages and 90–180 days of request-log retention.

Can I reserve throughput ahead of a launch? Sustained volumes above ₹50k/month get priority queueing — email sales@unoblox.ai a week ahead of any expected traffic spike to arrange it in advance.

Get started in rupees → https://unoblox.ai/sign-in