GLM 5.2 on QuickSilver Pro
GLM 5.2 is Z.ai's large-scale reasoning flagship: a 1M-token context window tuned for long-horizon agent workflows and project-level software engineering. On QuickSilver Pro it is $0.70 input / $2.20 output per million tokens, at parity with the OpenRouter endpoint selected by this route, with no markup or discount. QuickSilver Pro serves it in non-thinking mode, so replies are direct with no reasoning trace.
At a glance
Long-horizon agents and project-level coding — Z.ai's reasoning flagship with a 1M-token context window.
Pricing comparison ($/1M tokens)
| Provider | Input | Output | vs QSP |
|---|---|---|---|
| QuickSilver Pro | $0.70 | $2.20 | — |
| OpenRouter (z-ai/glm-5.2) | $0.70 | $2.20 | same |
| OpenAI (GPT-4o) | $2.50 | $10.00 | 78% lower |
When to use
Reach for GLM 5.2 on long-horizon agent loops and repo-scale software engineering: multi-step refactors, plan-then-act agents coordinating many tool calls, and tasks that need to hold a large working set in its 1M-token context.
When to use something else
For routine chat, short-context codegen, or single-shot tasks, the per-token price and reasoning overhead are overkill — DeepSeek V4 Flash ($0.06/$0.18) or V4 Pro ($0.70/$2.10) land most of those for less. For pure mathematical reasoning, DeepSeek V4 Pro. For agentic coding specifically, A/B against Kimi K2.7 Code.
Quickstart (curl)
curl https://api.quicksilverpro.io/v1/chat/completions \
-H "Authorization: Bearer $QSP_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5.2",
"messages": [{"role": "user", "content": "Hello!"}]
}'OpenAI-compatible. One-line migration via base_url.
FAQ
GLM 5.2 is a reasoning-capable model, but QuickSilver Pro serves it in non-thinking mode: you get a direct reply and never bill a hidden reasoning trace. A `reasoning` field in the request does not turn it on. If a task needs step-by-step reasoning in the same family, use GLM 5.3, where reasoning is always on.
Yes — GLM 5.2 is an OpenAI-compatible chat completions endpoint on QuickSilver Pro. Set base_url=https://api.quicksilverpro.io/v1, paste your QSP key, and use model="glm-5.2". Streaming, tool calling, json_schema strict mode, and usage.cost accounting all work.
$0.70 input / $2.20 output and $0.105 cache read per million tokens, matching the route-selected OpenRouter endpoint (digitalocean) with no markup or discount. The route uses its pinned provider order or the cheapest eligible endpoint under sort: price and its quantization filters; the /models headline can differ. More expensive fallback hosts do not change your price. Use base_url=https://api.quicksilverpro.io/v1 and model="glm-5.2".