DeepSeek-V4-Flash and Qwen3.8-27B Now Available for Telnyx Inference

Two new smaller, faster LLMs are now available on the Telnyx Inference API: DeepSeek-V4-Flash for cost-efficient high-volume workloads, and Qwen3.8-27B for low-latency routing and classification tasks. Both run on Telnyx-owned GPU infrastructure through the existing OpenAI-compatible Chat Completions endpoint, with no new endpoints or SDK updates required.

What's new

• DeepSeek-V4-Flash: Available with model ID deepseek-ai/DeepSeek-V4-Flash-0731. A smaller, faster DeepSeek variant tuned for cost-efficient inference at high volume.
• Qwen3.8-27B: Available with model ID Qwen/Qwen3.8-27B. A 27B-parameter model from the Qwen team, sized for low-latency tasks where a full-scale LLM is overkill.
• Drop-in integration: Both models work with the existing OpenAI-compatible Chat Completions API. No new endpoints, no SDK updates required.

Why it matters

• Not every agent step needs the largest available model. Routing a lightweight task to DeepSeek-V4-Flash or Qwen3.8-27B instead of a flagship LLM cuts cost per call without forcing a second inference provider into your stack.
• Running these smaller models on Telnyx-owned GPUs keeps them on the same private backbone as your STT, TTS, and telephony, so the latency hop of routing to a separate inference provider is gone.
• Evaluating open-weight models without changing your integration means zero migration cost when switching between models on the platform.

Example use cases

• Voice AI teams routing low-complexity agent turns to a cheaper model and reserving flagship LLMs for hard reasoning steps, without a second vendor.
• Developers building classification, summarization, or intent-routing layers where a 27B model is enough and response time matters more than parameter count.
• Engineering teams running high-volume batch inference that need cost per token down without changing their existing Telnyx integration.

Pricing

Full rate details on the inference pricing page.

Getting started

1. Open the LLM Playground in Mission Control.
2. Select deepseek-ai/DeepSeek-V4-Flash-0731 or Qwen/Qwen3.8-27B from the model dropdown.
3. Send a prompt to test the model, or integrate it into your application using the Chat Completions API.

curl https://api.telnyx.com/v2/ai/chat/completions   -H "Authorization: Bearer $TELNYX_API_KEY"   -H "Content-Type: application/json"   -d '{
    "model": "deepseek-ai/DeepSeek-V4-Flash-0731",
    "messages": [
      {"role": "user", "content": "Classify this support ticket into one of: billing, technical, account."}
    ]
  }'

Learn more in the Inference API docs or on the pricing page.