GLM 5.3 on QuickSilver Pro
GLM 5.3 is Z.ai's newest reasoning flagship, tuned for complex software engineering and long-horizon agent tasks, with a 1M-token context window and 131K max output. On QuickSilver Pro it's $1.12 input / $3.52 output per million tokens, ~20% below Z.ai's own list price of $1.40 / $4.40. Unlike GLM 5.2, reasoning is always on for this endpoint and cannot be disabled — control depth with `reasoning_effort` instead.
At a glance
Complex software engineering and long-horizon agents — Z.ai's newest reasoning flagship with a 1M-token context window.
Pricing comparison ($/1M tokens)
| Provider | Input | Output | vs QSP |
|---|---|---|---|
| QuickSilver Pro | $1.12 | $3.52 | lowest-cost |
| Z.ai (z-ai/glm-5.3) | $1.40 | $4.40 | 20% lower |
| OpenAI (GPT-4o) | $2.50 | $10.00 | 65% lower |
When to use
Reach for GLM 5.3 on the hardest Z.ai-family workloads: repo-scale refactors, plan-then-act agents coordinating many tool calls over long horizons, and tasks that need both a large working set in its 1M-token context and up to 131K tokens of output in one call. It succeeds GLM 5.2 at the same per-token price, so for new projects that want deliberate reasoning it's the default pick of the family. Reasoning is always on; use `reasoning_effort` to trade depth against latency and cost.
When to use something else
Reasoning is mandatory here, so it spends thinking tokens even on trivial turns — if you want a GLM that replies directly, GLM 5.2 is the better family pick at the same price. For routine chat, short-context codegen, or single-shot tasks, the per-token price and reasoning overhead are overkill — DeepSeek V4 Flash ($0.112/$0.224) or V4 Pro ($0.435/$0.87) land most of those for less. If you have an existing prompt suite tuned on GLM 5.2, A/B before switching — same price, but traces and tool-call cadence differ. For agentic coding specifically, also 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-5.3",
"messages": [{"role": "user", "content": "Hello!"}]
}'OpenAI-compatible. One-line migration via base_url.
FAQ
Reasoning is always on — it is mandatory on this endpoint and cannot be disabled (a request that tries to turn it off is rejected upstream). Use `reasoning_effort` to trade depth against latency and cost. Reasoning tokens bill as output tokens and are drawn from your `max_tokens` budget before the visible answer, so set `max_tokens` generously or the reply can come back truncated. If you want a GLM without always-on thinking, use GLM 5.2 — same price, direct replies by default.
GLM 5.3 is Z.ai's successor release (2026-08-18) with improved complex software engineering and long-horizon agent performance, the same 1M-token context window, and an explicit 131K max-output limit. One behavioral difference matters: GLM 5.3 reasoning is mandatory and cannot be disabled, while GLM 5.2 replies directly by default. Both are priced identically at $1.12 input / $3.52 output per million tokens, so upgrading is a model-ID swap — budget extra output tokens for the always-on thinking.
Yes — GLM 5.3 is an OpenAI-compatible chat completions endpoint on QuickSilver Pro (the Responses API works too). Set base_url=https://api.quicksilverpro.io/v1, paste your QSP key, and use model="glm-5.3". Streaming, tool calling (`tool_choice: "auto"` — this endpoint rejects forcing a specific function), and usage.cost accounting all work. `response_format: json_schema` is not enforced on this endpoint yet; if you need strict structured output, use GLM 5.2.
Z.ai lists GLM 5.3 at $1.40 input / $4.40 output per million tokens; QuickSilver Pro is $1.12 / $3.52, ~20% below on both legs. Same OpenAI-compatible surface; migration is a base_url + key swap, dropping the `z-ai/` provider prefix from the model ID.