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Same-model provider benchmark

Fireworks vs Weights & Biases: LLM provider comparison

Compare Fireworks and Weights & Biases on 6 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.

Fireworks

8 indexed models

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

Weights & Biases

19 indexed models

Headquarters
United States
Server regions
United States
Model types
19 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

Weights & Biases

1.43× typical advantage

6 exact models with complete recent speed data

Lowest token cost

Weights & Biases

$1.4817 / 1M

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

Most models available

Weights & Biases

19 models

Complete catalog coverage across all indexed modalities

Shared-model benchmark summary

MetricFireworksWeights & Biases
Typical 500-token response9.72 s4.39 s
Typical response start1.13 s0.52 s
Typical output speed63.0 tok/s129.0 tok/s
Blended token price$1.4978 / 1M$1.4817 / 1M
Typical route uptime98.68%99.68%

Visual comparison

Price and performance charts

FireworksWeights & Biases
500-token response by shared model

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

Weights & Biases has the lower typical same-model response ratio across 6 measured models.

Blended token price by shared model

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

Weights & Biases has the lower typical price ratio across 6 priced shared models.

Shared text models

6 exact models · newest first

ModelFireworksWeights & Biases
GLM 5.2Winner · Weights & Biases

z-ai/glm-5.2

Fireworks
Blended price
$2.4 / 1M
500-token response
11.65 s
Response starts
1.23 s
Output speed
48.0 tok/s
Route uptime
99.00%
Context
1M
Route
fireworks
Weights & Biases
Blended price
$2.3933 / 1M
500-token response
4.48 s
Response starts
0.58 s
Output speed
128.0 tok/s
Route uptime
99.89%
Context
262.1K
Route
wandb/fp4
Kimi K2.7 CodeWinner · Weights & Biases

moonshotai/kimi-k2.7-code

Fireworks
Blended price
$1.9667 / 1M
500-token response
11.81 s
Response starts
2.19 s
Output speed
52.0 tok/s
Route uptime
N/a
Context
262.1K
Route
fireworks
Weights & Biases
Blended price
$1.96 / 1M
500-token response
3.20 s
Response starts
0.46 s
Output speed
182.0 tok/s
Route uptime
N/a
Context
262.1K
Route
wandb/int4
DeepSeek V4 ProWinner · Fireworks

deepseek/deepseek-v4-pro

Fireworks
Blended price
$2.32 / 1M
500-token response
34.18 s
Response starts
2.93 s
Output speed
16.0 tok/s
Route uptime
98.35%
Context
1M
Route
fireworks
Weights & Biases
Blended price
$2.32 / 1M
500-token response
126.79 s
Response starts
1.79 s
Output speed
4.0 tok/s
Route uptime
97.62%
Context
1M
Route
wandb/fp8
DeepSeek V4 FlashWinner · Fireworks

deepseek/deepseek-v4-flash

Fireworks
Blended price
$0.1867 / 1M
500-token response
7.79 s
Response starts
1.04 s
Output speed
74.0 tok/s
Route uptime
98.04%
Context
1M
Route
fireworks
Weights & Biases
Blended price
$0.1867 / 1M
500-token response
23.36 s
Response starts
0.63 s
Output speed
22.0 tok/s
Route uptime
99.69%
Context
1M
Route
wandb/fp8
Kimi K2.6Winner · Weights & Biases

moonshotai/kimi-k2.6

Fireworks
Blended price
$1.9667 / 1M
500-token response
6.99 s
Response starts
0.41 s
Output speed
76.0 tok/s
Route uptime
N/a
Context
262.1K
Route
fireworks
Weights & Biases
Blended price
$1.9667 / 1M
500-token response
4.30 s
Response starts
0.45 s
Output speed
130.0 tok/s
Route uptime
100.00%
Context
262.1K
Route
wandb/fp4
gpt-oss-20bWinner · Weights & Biases

openai/gpt-oss-20b

Fireworks
Blended price
$0.1467 / 1M
500-token response
4.43 s
Response starts
0.34 s
Output speed
122.0 tok/s
Route uptime
99.62%
Context
131.1K
Route
fireworks
Weights & Biases
Blended price
$0.0633 / 1M
500-token response
3.58 s
Response starts
0.27 s
Output speed
151.0 tok/s
Route uptime
99.67%
Context
131.1K
Route
wandb/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.

Fireworks vs Weights & Biases analysis

How Fireworks and Weights & Biases compare for AI inference

Fireworks and Weights & Biases share 6 indexed text models, including GLM 5.2, Kimi K2.7 Code, DeepSeek V4 Pro, DeepSeek V4 Flash, Kimi K2.6. Weights & Biases has the stronger typical response-time result on the directly measured set.

Same-model speed evidence

6 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

6 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

Fireworks has 8 indexed models and lists no published server regions; Weights & Biases has 19 models and lists 1 region. Verify data residency, privacy terms, limits, and production latency directly before choosing.

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