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, with 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.