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Same-model provider benchmark

Cerebras vs NovitaAI: LLM provider comparison

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

Cerebras

3 indexed models

Headquarters
United States
Server regions
N/a
Model types
3 text

NovitaAI

66 indexed models

Headquarters
United States
Server regions
N/a
Model types
66 text

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

11.67× typical advantage

3 exact models with complete recent speed data

Lowest token cost

$0.4544 / 1M

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

Most models available

66 models

Complete catalog coverage across all indexed modalities

Shared-model benchmark summary

MetricCerebrasNovitaAI
Typical 500-token response2.40 s33.56 s
Typical response start0.23 s1.04 s
Typical output speed253.0 tok/s16.0 tok/s
Blended token price$1.3522 / 1M$0.4544 / 1M
Typical route uptime100.00%98.00%

Visual comparison

Price and performance charts

CerebrasNovitaAI
500-token response by shared model

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

Cerebras 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.

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

Shared text models

3 exact models · newest first

ModelCerebrasNovitaAI
Gemma 4 31BWinner · NovitaAI

google/gemma-4-31b-it

Cerebras
Blended price
$1.1567 / 1M
500-token response
11.57 s
Response starts
0.21 s
Output speed
44.0 tok/s
Route uptime
100.00%
Context
131.1K
Route
cerebras/fp16
NovitaAI
Blended price
$0.2267 / 1M
500-token response
34.37 s
Response starts
1.04 s
Output speed
15.0 tok/s
Route uptime
98.00%
Context
262.1K
Route
novita/bf16
GLM 4.7Winner · Cerebras

z-ai/glm-4.7

Cerebras
Blended price
$2.4167 / 1M
500-token response
2.40 s
Response starts
0.42 s
Output speed
253.0 tok/s
Route uptime
100.00%
Context
131.1K
Route
cerebras/fp16
NovitaAI
Blended price
$1.02 / 1M
500-token response
33.56 s
Response starts
2.31 s
Output speed
16.0 tok/s
Route uptime
84.86%
Context
204.8K
Route
novita/fp8
gpt-oss-120bWinner · Cerebras

openai/gpt-oss-120b

Cerebras
Blended price
$0.4833 / 1M
500-token response
0.80 s
Response starts
0.23 s
Output speed
882.5 tok/s
Route uptime
99.95%
Context
131.1K
Route
cerebras/fp16
NovitaAI
Blended price
$0.1167 / 1M
500-token response
9.33 s
Response starts
0.71 s
Output speed
58.0 tok/s
Route uptime
98.36%
Context
131.1K
Route
novita/fp4

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.

Cerebras vs NovitaAI analysis

How Cerebras and NovitaAI compare for AI inference

Cerebras and NovitaAI share 3 indexed text models, including Gemma 4 31B, GLM 4.7, gpt-oss-120b. Cerebras 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

Cerebras has 3 indexed models and lists no published server regions; NovitaAI has 66 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.

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Compare with other providers

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