Skip to content

Most Reliable Qwen3.5-35B-A3B Inference Providers

Ranks providers by the uptime OpenRouter measured during the latest 30-minute window.

DeepInfra currently ranks first at 100.00% via deepinfra/fp8.

Provider options:
9
Ranked:
9
Metric:
Uptime (last 30 min)

Highest uptime endpoint ranking

Most Reliable Qwen3.5-35B-A3B Inference Providers
RankProvider / routeUptime (last 30 min)Speed measurementsEndpoint details
#1Provider / route
DeepInfradeepinfra/fp8
Uptime (last 30 min)100.00%Speed measurements
500-token response
5.29 s
Response starts
0.24 s
Output speed
99.0 tok/s
Endpoint details
Input price
$0.14 / 1M tokens
Output price
$1 / 1M tokens
Uptime (30 min)
100.00%
Context
262.1K
#2Provider / route
AkashMLakashml/fp8
Uptime (last 30 min)100.00%Speed measurements
500-token response
9.58 s
Response starts
1.31 s
Output speed
60.5 tok/s
Endpoint details
Input price
$0.14 / 1M tokens
Output price
$1 / 1M tokens
Uptime (30 min)
100.00%
Context
262.1K
#3Provider / routeUptime (last 30 min)100.00%Speed measurements
500-token response
3.83 s
Response starts
0.56 s
Output speed
153.0 tok/s
Endpoint details
Input price
$0.1625 / 1M tokens
Output price
$1.3 / 1M tokens
Uptime (30 min)
100.00%
Context
262.1K
#4Provider / route
AtlasCloudatlas-cloud/fp8
Uptime (last 30 min)100.00%Speed measurements
500-token response
31.47 s
Response starts
2.06 s
Output speed
17.0 tok/s
Endpoint details
Input price
$0.225 / 1M tokens
Output price
$1.8 / 1M tokens
Uptime (30 min)
100.00%
Context
262.1K
#5Provider / route
NextBitnextbit/fp8
Uptime (last 30 min)100.00%Speed measurements
500-token response
15.62 s
Response starts
1.73 s
Output speed
36.0 tok/s
Endpoint details
Input price
$0.23 / 1M tokens
Output price
$1.6 / 1M tokens
Uptime (30 min)
100.00%
Context
262.1K
#6Provider / route
Uptime (last 30 min)100.00%Speed measurements
500-token response
3.69 s
Response starts
0.35 s
Output speed
150.0 tok/s
Endpoint details
Input price
$0.25 / 1M tokens
Output price
$1.25 / 1M tokens
Uptime (30 min)
100.00%
Context
262.1K
#7Provider / route
Parasailparasail/fp8
Uptime (last 30 min)99.97%Speed measurements
500-token response
6.58 s
Response starts
0.49 s
Output speed
82.0 tok/s
Endpoint details
Input price
$0.15 / 1M tokens
Output price
$1 / 1M tokens
Uptime (30 min)
99.97%
Context
262.1K
#8Provider / route
Venicevenice
Uptime (last 30 min)99.66%Speed measurements
500-token response
8.83 s
Response starts
1.68 s
Output speed
70.0 tok/s
Endpoint details
Input price
$0.3125 / 1M tokens
Output price
$1.25 / 1M tokens
Uptime (30 min)
99.66%
Context
256K
#9Provider / route
SiliconFlowsiliconflow/fp8
Uptime (last 30 min)65.81%Speed measurements
500-token response
32.37 s
Response starts
4.59 s
Output speed
18.0 tok/s
Endpoint details
Input price
$0.24 / 1M tokens
Output price
$1.8 / 1M tokens
Uptime (30 min)
65.81%
Context
262.1K

Endpoint data fetched .

Qwen3.5-35B-A3B endpoint guide

How to interpret the Most Reliable Qwen3.5-35B-A3B Inference Providers

9 of 9 Qwen3.5-35B-A3B endpoints currently have the published data required for this ranking. DeepInfra leads at 100.00% via deepinfra/fp8. The table keeps unranked routes visible so missing measurements do not look like missing provider availability.

How recent uptime is ranked

The reliability ranking uses the published 30-minute endpoint uptime measurement. This short operational window can reveal current instability, but it is not a service-level agreement or a substitute for longer-term availability monitoring.

Compare DeepInfra with the next option

AkashML currently ranks second at 100.00%. 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

Qwen3.5-35B-A3B has 9 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.