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Same-model provider benchmark

ModelRun vs Together: LLM provider comparison

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

ModelRun

4 indexed models

Headquarters
United States
Server regions
United States
Model types
4 text

Together

19 indexed models

Headquarters
United States
Server regions
N/a
Model types
17 text, 2 transcription

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

1.03× typical advantage

3 exact models with complete recent speed data

Lowest token cost

$1.2489 / 1M

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

Most models available

19 models

Complete catalog coverage across all indexed modalities

Shared-model benchmark summary

MetricModelRunTogether
Typical 500-token response6.85 s5.21 s
Typical response start0.90 s0.54 s
Typical output speed84.0 tok/s107.0 tok/s
Blended token price$1.2489 / 1M$1.58 / 1M
Typical route uptime98.64%99.29%

Visual comparison

Price and performance charts

ModelRunTogether
500-token response by shared model

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

ModelRun 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.

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

Shared text models

3 exact models · newest first

ModelModelRunTogether
Kimi K2.7 CodeWinner · ModelRun

moonshotai/kimi-k2.7-code

ModelRun
Blended price
$1.8167 / 1M
500-token response
3.35 s
Response starts
0.46 s
Output speed
173.0 tok/s
Route uptime
98.81%
Context
262.1K
Route
modelrun/fp4
Together
Blended price
$1.9667 / 1M
500-token response
3.47 s
Response starts
0.49 s
Output speed
168.0 tok/s
Route uptime
99.29%
Context
262.1K
Route
together
Kimi K2.6Winner · Together

moonshotai/kimi-k2.6

ModelRun
Blended price
$1.6 / 1M
500-token response
13.99 s
Response starts
1.49 s
Output speed
40.0 tok/s
Route uptime
98.64%
Context
262.1K
Route
modelrun/fp4
Together
Blended price
$2.3 / 1M
500-token response
5.21 s
Response starts
0.54 s
Output speed
107.0 tok/s
Route uptime
99.73%
Context
262.1K
Route
together
Gemma 4 31BWinner · ModelRun

google/gemma-4-31b-it

ModelRun
Blended price
$0.33 / 1M
500-token response
6.85 s
Response starts
0.90 s
Output speed
84.0 tok/s
Route uptime
97.84%
Context
262.1K
Route
modelrun/fp4
Together
Blended price
$0.4733 / 1M
500-token response
24.13 s
Response starts
2.39 s
Output speed
23.0 tok/s
Route uptime
83.73%
Context
262.1K
Route
together

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.

ModelRun vs Together analysis

How ModelRun and Together compare for AI inference

ModelRun and Together share 3 indexed text models, including Kimi K2.7 Code, Kimi K2.6, Gemma 4 31B. ModelRun 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

ModelRun has 4 indexed models and lists 1 published server region; Together has 19 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.