Glm 4.6 Fp8
Pricing & Specs
Zhipu AI · $0.6 input / $2.2 output per 1M tokens · 202.752K context window
The per-token price never tells the full story. A typical task (1K input + 500 output tokens) on Glm 4.6 Fp8 costs about $0.0017 — roughly $1.70 per 1,000 runs. But if it needs 3x the tokens of a cheaper model to match quality on YOUR task, the economics flip. The only way to know is to benchmark it on your actual workload.
Glm 4.6 Fp8 API Pricing
| Tokens | Price |
|---|---|
| Input | $0.6 / 1M tokens |
| Output | $2.2 / 1M tokens |
50% discount available for batch API requests. Batch API pricing is available via Together at 50%; cache pricing is not published.
What that means in practice
Glm 4.6 Fp8 Specs
| Spec | Value |
|---|---|
| Context window | 202.752K tokens |
| Input modalities | text |
| Output modalities | text |
| Latency (measured by OpenMark) | ~1.3s median response |
| Reasoning model | Yes |
| Tool / function calling | Yes |
| JSON mode | Yes |
| Streaming | Yes |
| Prompt caching | No |
| Batch API | Yes |
FAQ
How much does Glm 4.6 Fp8 cost?
Glm 4.6 Fp8 costs $0.6 per 1M input tokens and $2.2 per 1M output tokens.
What is Glm 4.6 Fp8's context window?
Glm 4.6 Fp8 has a 202.752K-token context window.
Can I test Glm 4.6 Fp8 on my own task?
Yes. OpenMark lets you benchmark Glm 4.6 Fp8 against 100+ models on your own task with real API calls — no API keys needed, free tier available.
Is Glm 4.6 Fp8 the right model for YOUR task?
Pricing tables can't answer that. Benchmark it against 100+ models
on your actual workload — real API calls, real costs. Free tier available.