GLM 5 Turbo
glm-5-turboz-ai-glm-5-turbo- 🎯 Fast-inference model tuned for agents and coding
- 🔧 Function calling plus built-in web search
- 🧠 Reasoning-capable, code-optimized workflows
- 📏 200K-token context window
- 📜 Open-source MIT license
- 🏢 From China's Z.ai (GLM family)
Z.ai, formally Knowledge Atlas Technology Joint Stock Co., Ltd., is a Chinese technology company specializing in artificial intelligence. Previously known internationally as Zhipu AI, the company rebranded to Z.ai in 2025. Its core focus is the GLM family of large language…
Explore 14 more models by Z.ai →GLM 5 Turbo is Z.ai's speed-optimized member of the GLM 5 line, released in March 2026 and built for low-latency inference in agent-driven environments and production coding workflows. It pairs reasoning and code-optimization with native function calling and web search, and exposes a 200K-token context window that comfortably handles large codebases and multi-step tool chains. Like the rest of the GLM lineup, it ships under the permissive MIT license, continuing Z.ai's open-source approach since the GLM family rebrand in 2025.
Within Z.ai's catalogue, GLM 5 Turbo sits as the throughput-focused counterpart to the heavier flagship GLM 5 releases. It is now joined by [[sibling:z-ai-glm-5v-turbo|GLM 5V Turbo]] (released April 2026), which extends the same fast-inference Turbo recipe, while the broader line has advanced through releases like [[sibling:zai-org-glm-5-2|GLM 5.2]]. Users may still favor the Turbo tier specifically for its speed and cost profile.
It is best suited for developers building responsive coding assistants, autonomous agents, and tool-using applications where fast turnaround and reliable function calling matter more than maximum model size.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Routing | Input $/M | Cached $/M | Output $/M | Categories | API |
|---|---|---|---|---|---|---|---|
| Venice.ai Proxy 0x1f22…18c9 | 99 | #3 | $0.60 | $0.12 | $2.00 | chat,reasoning,coding,web-search | openai-chat-completions |
| ▲ Apex Ant 0x73b4…e736 | 83 | #2 | $0.54 | $0.108 | $1.80 | chat,fast,reasoning,long-context,agents | openai-chat-completions |
| surplusintelligence.ai 0x0e49…8927 | 68 | #1 | $0.36 | $0.072 | $1.20 | agents,chat,cheap,code,coding,developer,fast,frontier,function-calling,reasoning,research,tasks,tools,translate,web-search | openai-chat-completions |
| NovaRoute AI 0xc50d…ed7b | 60 | gated | $0.4455 | $0.4455 | $1.485 | chat,coding,code,reasoning,tasks,glm,value,surplus,openai-compatible,low-cost,verified,github,response-auth,base-usdc,monitored | openai-chat-completions |
| Super Seeder 0xd19f…41f3 | 40 | gated | $0.60 | $0.12 | $2.00 | chat,coding,reasoning,tools | openai-chat-completions |
| Fire Ant 🔥🐜 0xbe05…bc5d | 37 | gated | $1.0534 | $0.216 | $3.5112 | base-usdc,chat,code,coding,github,glm,json,low-cost,math,monitored,openai-compatible,reasoning,response-auth,surplus,tasks,tools,value,verified | — |
| Meridian AI 0x8c8c…06f5 | 22 | gated | $0.1296 | $0.1296 | $0.432 | chat,coding,reasoning | openai-chat-completions |
| antseed-neon-puma-944e 0x6650…944e | 3 | gated | $0.4092 | $0.24 | $1.364 | chat,coding,math | openai-chat-completions |
| antseed-opal-badger-2580 0xc85d…2580 | 2 | gated | $0.60 | $0.60 | $2.00 | chat | openai-chat-completions |
| Apex TEE Test 0xe672…7955 | 0 | gated | $0.264 | $0.0648 | $0.96 | chat,fast,reasoning,long-context,agents | openai-chat-completions |
| Leftermute 0x388b…5389 | 0 | gated | $0.2424 | $0.2424 | $0.808 | chat,coding,json,tools | openai-chat-completions |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = on-chain trust (0-100). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.