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Same-model provider benchmark

AkashML vs SiliconFlow: LLM provider comparison

Compare AkashML and SiliconFlow on 4 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.

AkashML

5 indexed models

Headquarters
N/a
Server regions
N/a
Model types
5 text

SiliconFlow

36 indexed models

Headquarters
Singapore
Server regions
United States
Model types
35 text, 1 embeddings

At a glance

Metric winners

There is no overall score. Each winner answers one specific question using only directly comparable data.

Fastest on shared models

1.77× typical advantage

4 exact models with complete recent speed data

Lowest token cost

$0.8433 / 1M

4 exact models using a 1K-input/500-output mix

Most models available

36 models

Complete catalog coverage across all indexed modalities

Shared-model benchmark summary

MetricAkashMLSiliconFlow
Typical 500-token response12.69 s19.30 s
Typical response start1.21 s2.56 s
Typical output speed47.5 tok/s29.5 tok/s
Blended token price$0.8433 / 1M$0.9597 / 1M
Typical route uptime98.75%98.20%

Visual comparison

Price and performance charts

AkashMLSiliconFlow
500-token response by shared model

Estimated seconds using recent median response-start and output-speed data. Lower is better.

AkashML has the lower typical same-model response ratio across 4 measured models.

Blended token price by shared model

USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.

AkashML has the lower typical price ratio across 4 priced shared models.

Shared text models

4 exact models · newest first

ModelAkashMLSiliconFlow
GLM 5.2Winner · AkashML

z-ai/glm-5.2

AkashML
Blended price
$2.3333 / 1M
500-token response
16.05 s
Response starts
1.34 s
Output speed
34.0 tok/s
Route uptime
97.94%
Context
131.1K
Route
akashml/fp8
SiliconFlow
Blended price
$2.232 / 1M
500-token response
20.11 s
Response starts
3.44 s
Output speed
30.0 tok/s
Route uptime
99.96%
Context
1M
Route
siliconflow/fp8
Qwen3.6 35B A3BWinner · AkashML

qwen/qwen3.6-35b-a3b

AkashML
Blended price
$0.4267 / 1M
500-token response
6.18 s
Response starts
0.56 s
Output speed
89.0 tok/s
Route uptime
98.13%
Context
262.1K
Route
akashml/fp8
SiliconFlow
Blended price
$0.6667 / 1M
500-token response
18.49 s
Response starts
1.25 s
Output speed
29.0 tok/s
Route uptime
97.82%
Context
262.1K
Route
siliconflow/fp8
DeepSeek V4 FlashWinner · SiliconFlow

deepseek/deepseek-v4-flash

AkashML
Blended price
$0.1867 / 1M
500-token response
51.28 s
Response starts
1.28 s
Output speed
10.0 tok/s
Route uptime
99.38%
Context
131.1K
Route
akashml/fp8
SiliconFlow
Blended price
$0.18 / 1M
500-token response
11.49 s
Response starts
1.69 s
Output speed
51.0 tok/s
Route uptime
98.57%
Context
1M
Route
siliconflow/fp8
Qwen3.5-35B-A3BWinner · AkashML

qwen/qwen3.5-35b-a3b

AkashML
Blended price
$0.4267 / 1M
500-token response
9.34 s
Response starts
1.14 s
Output speed
61.0 tok/s
Route uptime
100.00%
Context
262.1K
Route
akashml/fp8
SiliconFlow
Blended price
$0.76 / 1M
500-token response
33.86 s
Response starts
4.44 s
Output speed
17.0 tok/s
Route uptime
83.07%
Context
262.1K
Route
siliconflow/fp8

A per-model winner combines blended price and estimated 500-token response time with equal proportional weight. Ties and rows missing either measurement receive no badge. Comparison data calculated . Values use one deterministic route per provider and model; missing measurements remain visible as N/a.

AkashML vs SiliconFlow analysis

How AkashML and SiliconFlow compare for AI inference

AkashML and SiliconFlow share 4 indexed text models, including GLM 5.2, Qwen3.6 35B A3B, DeepSeek V4 Flash, Qwen3.5-35B-A3B. AkashML has the stronger typical response-time result on the directly measured set.

Same-model speed evidence

4 shared models currently have complete response-start and output-speed measurements on both providers. The speed comparison uses per-model ratios before taking the median, so naturally faster model catalogs do not improve the result.

Token pricing on one workload

4 shared models have complete input and output prices on both providers. Prices use the same 1,000-input/500-output-token mix and are normalized to one million tokens for readability.

Catalog and deployment differences

AkashML has 5 indexed models and lists no published server regions; SiliconFlow has 36 models and lists 1 region. Verify data residency, privacy terms, limits, and production latency directly before choosing.