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Qwen: Qwen3.5-27B provider comparison

qwen/qwen3.5-27b

The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...

Endpoints:
6
Context:
262.1K
Input:
text, image, video
Output:
text
Compare this model in a set →

At a glance

Comparison winners

Based on 1,000 input and 500 output tokens using the latest published median speed data.

Best cost/speed trade-off

$0.65 / 1M tokens

25.48 s estimated response

Fastest

Phalaphala

24.08 s estimated response

$1 / 1M tokens

Visual comparison

Price and performance charts

Compare published endpoint pricing and estimated response time visually.

Effective price by endpoint

USD per 1 million tokens for input and output. Lower is better.

Alibaba Cloud Int. has the lowest estimated cost for 1,000 input and 500 output tokens at $0.000975.

Estimated cost vs. response time

Based on 1,000 input and 500 output tokens. Cost is shown in USD per 1 million tokens. Lower and further left is better; the single best cost/speed trade-off appears at full opacity.

6 providers have complete pricing and speed data. Alibaba Cloud Int. is closest to the ideal combination of lowest cost and fastest response.

Server-rendered comparison

Provider endpoints

Prompt and completion prices are effective USD per token as published by OpenRouter. Missing speed data never removes an endpoint.

Endpoint comparison for Qwen: Qwen3.5-27B
Provider / routeCurrent pricing ↗Speed measurementsEndpoint details
Provider / route
Alibaba Cloud Int.alibaba
CheapestBest cost/speed trade-off
Current pricing
Input price
$0.195 / 1M tokens
Output price
$1.56 / 1M tokens
Sample cost
$0.000975
Discount
35.0%
Speed measurements
500-token response
25.48 s
Response starts
2.75 s
Output speed
22.0 tok/s
Endpoint details
Uptime (30 min)
99.83%
Context
262.1K
Model format
unknown
Max output
65.5K
13 parameters

include_reasoning, logprobs, max_tokens, presence_penalty, reasoning, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_logprobs, top_p

Provider / route
SiliconFlowsiliconflow/fp8
Current pricing
Input price
$0.25 / 1M tokens
Output price
$2 / 1M tokens
Sample cost
$0.00125
Speed measurements
500-token response
35.80 s
Response starts
2.47 s
Output speed
15.0 tok/s
Endpoint details
Uptime (30 min)
97.73%
Context
262.1K
Model format
fp8
Max output
262.1K
13 parameters

frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, repetition_penalty, response_format, structured_outputs, temperature, tool_choice, tools, top_k, top_p

Provider / route
DeepInfradeepinfra/fp8
Current pricing
Input price
$0.26 / 1M tokens
Output price
$2.6 / 1M tokens
Sample cost
$0.00156
Speed measurements
500-token response
37.85 s
Response starts
2.13 s
Output speed
14.0 tok/s
Endpoint details
Uptime (30 min)
100.00%
Context
262.1K
Model format
fp8
Max output
81.9K
17 parameters

frequency_penalty, include_reasoning, logit_bias, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p

Provider / route
AtlasCloudatlas-cloud/fp8
Current pricing
Input price
$0.27 / 1M tokens
Output price
$2.16 / 1M tokens
Sample cost
$0.00135
Speed measurements
500-token response
42.70 s
Response starts
2.70 s
Output speed
12.5 tok/s
Endpoint details
Uptime (30 min)
99.87%
Context
262.1K
Model format
fp8
Max output
65.5K
16 parameters

frequency_penalty, include_reasoning, logit_bias, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_k, top_p

Provider / route
NovitaAInovita/bf16
Current pricing
Input price
$0.3 / 1M tokens
Output price
$2.4 / 1M tokens
Sample cost
$0.0015
Speed measurements
500-token response
32.70 s
Response starts
3.28 s
Output speed
17.0 tok/s
Endpoint details
Uptime (30 min)
99.87%
Context
262.1K
Model format
bf16
Max output
65.5K
16 parameters

frequency_penalty, include_reasoning, logprobs, max_tokens, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, temperature, tool_choice, tools, top_k, top_logprobs, top_p

Provider / route
Phalaphala
Fastest
Current pricing
Input price
$0.3 / 1M tokens
Output price
$2.4 / 1M tokens
Sample cost
$0.0015
Speed measurements
500-token response
24.08 s
Response starts
1.35 s
Output speed
22.0 tok/s
Endpoint details
Uptime (30 min)
99.64%
Context
262.1K
Model format
unknown
Max output
65.5K
16 parameters

frequency_penalty, include_reasoning, logprobs, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_logprobs, top_p

Endpoint data fetched .

Qwen3.5-27B deployment guide

How to choose a Qwen3.5-27B inference provider

Qwen3.5-27B is indexed here as a text model by Qwen, with 6 provider endpoints from Alibaba Cloud Int., SiliconFlow, DeepInfra, AtlasCloud, NovitaAI, and others. The comparison preserves each exact OpenRouter routing tag so pricing and performance observations can be connected to the route an application would actually request.

Match the endpoint to the workload

The model publishes a 262.1K-token context window. It accepts text, image, video input and returns text output. 19 distinct supported parameters appear across the listed routes. Confirm limits on the specific endpoint rather than assuming every host exposes the same configuration.

Compare the real request economics

Alibaba Cloud Int. currently has the lowest estimated cost for the standard 1,000-input/500-output-token sample at $0.000975. Input-heavy and output-heavy applications can produce a different result, so review both per-million-token prices in the endpoint table.

Balance response start and generation speed

Phala currently has the shortest estimated 500-token response at 24.08 seconds. Alibaba Cloud Int. is the single endpoint closest to the current ideal cost/speed combination. Recent observations can change, so validate finalists with your own prompts.