Skip to content

Fastest First-Token GLM 4.6V Inference Providers

Ranks providers by how quickly the first generated token appears. Providers without enough recent data remain visible after ranked rows.

NovitaAI currently ranks first at 3.71 s via novita/bf16.

Provider options:
2
Ranked:
2
Metric:
Time to first token

Fastest first token endpoint ranking

Fastest First-Token GLM 4.6V Inference Providers
RankProvider / routeTime to first tokenSpeed measurementsEndpoint details
#1Provider / route
NovitaAInovita/bf16
Time to first token3.71 sSpeed measurements
500-token response
18.41 s
Response starts
3.71 s
Output speed
34.0 tok/s
Endpoint details
Input price
$0.3 / 1M tokens
Output price
$0.9 / 1M tokens
Uptime (30 min)
91.79%
Context
131.1K
#2Provider / route
Z.aiz-ai/fp8
Time to first token4.54 sSpeed measurements
500-token response
18.62 s
Response starts
4.54 s
Output speed
35.5 tok/s
Endpoint details
Input price
$0.3 / 1M tokens
Output price
$0.9 / 1M tokens
Uptime (30 min)
91.26%
Context
131.1K

Endpoint data fetched .

GLM 4.6V endpoint guide

How to interpret the Fastest First-Token GLM 4.6V Inference Providers

2 of 2 GLM 4.6V endpoints currently have the published data required for this ranking. NovitaAI leads at 3.71 s via novita/bf16. The table keeps unranked routes visible so missing measurements do not look like missing provider availability.

How response-start time is ranked

The first-token ranking orders endpoints by the recent median time before output begins. This is useful for interactive applications, but it should be read alongside throughput because the first provider to start is not always the first to finish a long answer.

Compare NovitaAI with the next option

Z.ai currently ranks second at 4.54 s. Compare that gap with input and output price, response-start time, output speed, 30-minute uptime, context length, and the exact route before deciding whether first place is meaningful for your workload.

Use the route, not only the provider name

GLM 4.6V has 2 published provider options, and performance data is matched to each exact OpenRouter routing tag. Different quantization, context, regional deployment, or provider configuration can change price and behavior even when the underlying model name is identical.