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Fastest Qwen3.5-35B-A3B Inference Providers

Ranks providers by estimated time to return 500 tokens, combining the wait for the first token with output speed.

Weights & Biases currently ranks first at 3.69 s via wandb/fp8.

Provider options:
9
Ranked:
9
Metric:
Estimated response time

Fastest response endpoint ranking

Fastest Qwen3.5-35B-A3B Inference Providers
RankProvider / routeEstimated response timeSpeed measurementsEndpoint details
#1Provider / route
Estimated response time3.69 sSpeed 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
#2Provider / routeEstimated response time3.83 sSpeed 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
#3Provider / route
DeepInfradeepinfra/fp8
Estimated response time5.29 sSpeed 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
#4Provider / route
Parasailparasail/fp8
Estimated response time6.58 sSpeed 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
#5Provider / route
Venicevenice
Estimated response time8.83 sSpeed 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
#6Provider / route
AkashMLakashml/fp8
Estimated response time9.58 sSpeed 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
#7Provider / route
NextBitnextbit/fp8
Estimated response time15.62 sSpeed 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
#8Provider / route
AtlasCloudatlas-cloud/fp8
Estimated response time31.47 sSpeed 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
#9Provider / route
SiliconFlowsiliconflow/fp8
Estimated response time32.37 sSpeed 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 Fastest Qwen3.5-35B-A3B Inference Providers

9 of 9 Qwen3.5-35B-A3B endpoints currently have the published data required for this ranking. Weights & Biases leads at 3.69 s via wandb/fp8. The table keeps unranked routes visible so missing measurements do not look like missing provider availability.

How complete response time is ranked

The fastest ranking estimates a 500-token answer by adding the recent median first-token wait to 500 divided by median output throughput. It represents an example complete response, not a guarantee for every prompt or request size.

Compare Weights & Biases with the next option

Alibaba Cloud Int. currently ranks second at 3.83 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

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.