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Start freeGPT-5 · Claude · DeepSeek V4 · Qwen3 — in ₹One OpenAI-compatible endpointBilled in rupeesGST invoiceNo international cardGet started →Start freeGPT-5 · Claude · DeepSeek V4 · Qwen3 — in ₹One OpenAI-compatible endpointBilled in rupeesGST invoiceNo international cardGet started →
API Alternatives

Groq Alternative for India

Replace Groq with unoblox for India: Sub-500ms latency, all models (Llama, Qwen, GPT, Claude), ₹ billing, data residency.

Groq users in India: keep the speed, fix the billing

Groq's LPU hardware is genuinely fast, but it settles internationally — payment friction and no GST input-tax credit for Indian teams. unoblox pairs sub-500ms responses from India with ₹-native invoicing, GST compliance, and India-hosted infrastructure, through the OpenAI SDK you already use.

Speed and cost side by side

ModelTypical latency from India₹ input / output (1M tokens)
DeepSeek V4 Flash<300ms₹9.07 / ₹18.14
Llama 4 Scout<400ms₹10.08 / ₹30.24
Qwen3.8-27B<400ms₹16.32 / ₹48.96
Llama 4 Maverick<500ms₹20.16 / ₹80.64
Claude Sonnet<500ms₹201.6 / ₹1008
Qwen3 1.7B<150ms₹0 (free)

The real trade-off

Groq's custom silicon still wins on raw single-request latency for ultra-low-latency use-cases like live voice. If your workload is throughput-heavy and cost-sensitive — batch document processing, dataset labeling, high-volume chat — unoblox wins on ₹ pricing, GST recovery, and not managing a second international vendor relationship.

For latency-sensitive but budget-constrained apps, Qwen3 1.7B streams free and fast enough for most conversational UIs; step up to DeepSeek V4 Flash when you need stronger reasoning without losing speed. Either way, stream=True delivers incremental tokens the same way Groq's SDK does, so a real-time chat UI doesn't need any front-end changes.

Switch your endpoint

# OLD (Groq SDK)
from groq import Groq
client = Groq(api_key="gsk_...")

# NEW (unoblox) — plain OpenAI SDK
from openai import OpenAI
client = OpenAI(
    api_key="ub-gw-...",
    base_url="https://api.unoblox.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek-ai/deepseek-v4-flash",
    messages=[{"role": "user", "content": "Fast answer, please"}]
)

Why teams switch

  • ₹-billed, GST-invoiced. No international statement to reconcile; claim your 18% input-tax credit.
  • Broader model roster. Llama, Qwen, DeepSeek, Gemma, GPT, and Claude on one key — Groq's catalog is narrower.
  • India-hosted. Meets data-residency requirements that come up in vendor security review.
  • Batch-friendly pricing. No per-query premium for high-volume, non-real-time jobs.
  • One contract, not two. Chat, embeddings, and reranking all bill on the same GST invoice as your LLM traffic — no separate vendor relationship to manage for retrieval work.

Frequently asked questions

Will I lose Groq's raw speed advantage? For single-request latency, Groq's hardware is still faster. For chat, search, and content generation, unoblox's sub-500ms-from-India is fast enough that users won't notice, and Qwen3 1.7B runs well under that for free.

Do you support the Groq SDK directly? No, but the OpenAI SDK format is a full match — stream=True, tool calls, and JSON mode all carry over with just the endpoint and key changed.

Can I keep Groq as a failover? Yes — configure both endpoints in your client and route to unoblox first, falling back to Groq if a request errors.

What's your uptime commitment? 99.95% SLA with a 7-working-day refund path for extended outages; request logs are kept 90–180 days.

Can I reserve throughput for a launch? Not as a dedicated GPU reservation, but sustained volumes above ₹50k/month get priority queueing — email sales@unoblox.ai to set it up ahead of time.

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

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Start building in rupees

Call every major model through one OpenAI-compatible endpoint, billed in ₹ on a GST invoice.