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Same-model provider benchmark

NextBit vs Parasail: LLM provider comparison

Compare NextBit and Parasail on 3 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.

NextBit

13 indexed models

Headquarters
Spain
Server regions
Spain
Model types
13 text

Parasail

35 indexed models

Headquarters
United States
Server regions
N/a
Model types
34 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

2.44× typical advantage

3 exact models with complete recent speed data

Lowest token cost

$0.28 / 1M

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

Most models available

35 models

Complete catalog coverage across all indexed modalities

Shared-model benchmark summary

MetricNextBitParasail
Typical 500-token response32.88 s13.46 s
Typical response start1.91 s0.64 s
Typical output speed16.0 tok/s39.0 tok/s
Blended token price$0.3733 / 1M$0.28 / 1M
Typical route uptime99.38%98.97%

Visual comparison

Price and performance charts

NextBitParasail
500-token response by shared model

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

Parasail has the lower typical same-model response ratio across 3 measured models.

Blended token price by shared model

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

Parasail has the lower typical price ratio across 3 priced shared models.

Shared text models

3 exact models · newest first

ModelNextBitParasail
DeepSeek V4 FlashWinner · Parasail

deepseek/deepseek-v4-flash

NextBit
Blended price
$0.2367 / 1M
500-token response
32.88 s
Response starts
1.63 s
Output speed
16.0 tok/s
Route uptime
94.46%
Context
1M
Route
nextbit/fp8
Parasail
Blended price
$0.1867 / 1M
500-token response
13.46 s
Response starts
0.64 s
Output speed
39.0 tok/s
Route uptime
98.69%
Context
1M
Route
parasail/fp8
Gemma 4 26B A4BWinner · Parasail

google/gemma-4-26b-a4b-it

NextBit
Blended price
$0.1967 / 1M
500-token response
75.94 s
Response starts
4.51 s
Output speed
7.0 tok/s
Route uptime
99.38%
Context
262.1K
Route
nextbit/bf16
Parasail
Blended price
$0.22 / 1M
500-token response
17.86 s
Response starts
0.61 s
Output speed
29.0 tok/s
Route uptime
98.97%
Context
262.1K
Route
parasail/bf16
Qwen3.5-35B-A3BWinner · Parasail

qwen/qwen3.5-35b-a3b

NextBit
Blended price
$0.6867 / 1M
500-token response
18.04 s
Response starts
1.91 s
Output speed
31.0 tok/s
Route uptime
99.41%
Context
262.1K
Route
nextbit/fp8
Parasail
Blended price
$0.4333 / 1M
500-token response
11.69 s
Response starts
0.82 s
Output speed
46.0 tok/s
Route uptime
100.00%
Context
262.1K
Route
parasail/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.

NextBit vs Parasail analysis

How NextBit and Parasail compare for AI inference

NextBit and Parasail share 3 indexed text models, including DeepSeek V4 Flash, Gemma 4 26B A4B, Qwen3.5-35B-A3B. Parasail has the stronger typical response-time result on the directly measured set.

Same-model speed evidence

3 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

3 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

NextBit has 13 indexed models and lists 1 published server region; Parasail has 35 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.