GLM-5.3 Now Available on Telnyx Inference

GLM-5.3 is now available on the Telnyx Inference API. It is a frontier-class reasoning model with intelligence comparable to Kimi K3, at roughly half the cost and twice the speed. The model runs on Telnyx-owned GPU infrastructure.

What's new

• GLM-5.3: Available with model ID zai-org/GLM-5.3. A 753B-parameter reasoning model with a 1M token context window, hosted on Telnyx-owned GPUs.
• Frontier-class intelligence: Scores 60 on the Artificial Analysis Intelligence Index, placing it well above the reasoning-model average of 35 and comparable to Kimi K3.
• Cost advantage: Priced at $1.40/1M input and $4.40/1M output tokens, roughly 48% cheaper than Kimi K3 on input and 67% cheaper on output. Cached input available at $0.26/1M tokens.
• Speed: 85 tokens per second output, roughly twice Kimi K3's throughput and faster than the reasoning-model average of 74 t/s. Time to first token: 1.57s.
• Scaled post-training: Uses the same base model as GLM-5.2. All gains come from reinforcement learning on long-horizon tasks including coding, agentic workflows, and security analysis. Terminal Bench 3.0 jumped from 4.6 to 28.3 and DeepSWE v1.1 from 46.2 to 66.9.
• Thinking effort levels: Supports low, high, and max reasoning effort. max is recommended for coding and complex analysis.
• OpenAI-compatible API: Drop-in integration via the Chat Completions API. No new endpoints or SDK updates required.

Why it matters

Frontier intelligence has been locked behind premium pricing. GLM-5.3 changes that math. It matches Kimi K3 on the Artificial Analysis Intelligence Index while costing roughly half as much per token and generating output at twice the speed. Running on Telnyx-owned GPU infrastructure means inference stays on the same private backbone as your voice, messaging, and compute traffic. No cross-vendor hops, no reseller markup, no separate billing surface. For teams building AI agents that need frontier reasoning at production scale, the cost-per-task difference compounds fast.

Example use cases

• AI agent builders who need frontier reasoning for tool use, coding assistance, and multi-step planning without paying $13.50/1M output tokens.
• Developers building coding agents that need long-context reasoning with 1M token context windows.
• Teams migrating from Kimi K3 or Claude Opus who want comparable intelligence at lower cost per task.

Getting started

1. Open the LLM Playground in Mission Control.
2. Select zai-org/GLM-5.3 from the model dropdown.
3. Send a prompt to test, 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": "zai-org/GLM-5.3",
    "messages": [
      {"role": "user", "content": "Debug this Python function and explain the fix."}
    ],
    "thinking": {"type": "enabled"},
    "reasoning_effort": "max"
  }'

Learn more in the Z.ai GLM-5.3 blog post, the Artificial Analysis model profile, or the Inference API docs.