Parasail
35 indexed models
- Headquarters
United States
- Server regions
- N/a
- Model types
- 34 text, 1 embeddings
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Same-model provider benchmark
Compare Parasail and Weights & Biases on 12 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
35 indexed models
19 indexed models
At a glance
There is no overall score. Each winner answers one specific question using only directly comparable data.
Fastest on shared models
1.65× typical advantage
12 exact models with complete recent speed data
Lowest token cost
$0.8892 / 1M
12 exact models using a 1K-input/500-output mix
Most models available
35 models
Complete catalog coverage across all indexed modalities
| Metric | Parasail | Weights & Biases |
|---|---|---|
| Typical 500-token response | 11.39 s | 6.32 s |
| Typical response start | 0.62 s | 0.46 s |
| Typical output speed | 46.5 tok/s | 84.8 tok/s |
| Blended token price | $0.8892 / 1M | $0.9697 / 1M |
| Typical route uptime | 99.12% | 99.84% |
Visual comparison
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 12 measured models.
USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.
Parasail has the lower typical price ratio across 12 priced shared models.
| Model | Parasail | Weights & Biases |
|---|---|---|
GLM 5.2Winner · Weights & Biases z-ai/glm-5.2 | Parasail
| Weights & Biases
|
Kimi K2.7 CodeWinner · Weights & Biases moonshotai/kimi-k2.7-code | Parasail
| Weights & Biases
|
Qwen3.6 35B A3BWinner · Weights & Biases qwen/qwen3.6-35b-a3b | Parasail
| Weights & Biases
|
DeepSeek V4 ProWinner · Parasail deepseek/deepseek-v4-pro | Parasail
| Weights & Biases
|
DeepSeek V4 FlashWinner · Parasail deepseek/deepseek-v4-flash | Parasail
| Weights & Biases
|
Kimi K2.6Winner · Weights & Biases moonshotai/kimi-k2.6 | Parasail
| Weights & Biases
|
Gemma 4 31BWinner · Weights & Biases google/gemma-4-31b-it | Parasail
| Weights & Biases
|
Qwen3.5-35B-A3BWinner · Weights & Biases qwen/qwen3.5-35b-a3b | Parasail
| Weights & Biases
|
MiniMax M2.5Winner · Parasail minimax/minimax-m2.5 | Parasail
| Weights & Biases
|
gpt-oss-120bWinner · Weights & Biases openai/gpt-oss-120b | Parasail
| Weights & Biases
|
gpt-oss-20bWinner · Weights & Biases openai/gpt-oss-20b | Parasail
| Weights & Biases
|
Llama 3.3 70B InstructWinner · Parasail meta-llama/llama-3.3-70b-instruct | Parasail
| Weights & Biases
|
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.
Parasail vs Weights & Biases analysis
Parasail and Weights & Biases share 12 indexed text models, including GLM 5.2, Kimi K2.7 Code, Qwen3.6 35B A3B, DeepSeek V4 Pro, DeepSeek V4 Flash. Weights & Biases has the stronger typical response-time result on the directly measured set.
12 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.
12 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.
Parasail has 35 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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