Phala
18 indexed models
- Headquarters
United States- Server regions
- N/a
- Model types
- 18 text
Same-model provider benchmark
Phala vs StreamLake: LLM provider comparison
Compare Phala and StreamLake on 10 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
StreamLake
20 indexed models
- Headquarters
China- Server regions
- N/a
- Model types
- 20 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
1.22× typical advantage
10 exact models with complete recent speed data
Lowest token cost
$1.0772 / 1M
10 exact models using a 1K-input/500-output mix
Most models available
20 models
Complete catalog coverage across all indexed modalities
Shared-model benchmark summary
| Metric | Phala | StreamLake |
|---|---|---|
| Typical 500-token response | 22.33 s | 21.84 s |
| Typical response start | 2.47 s | 2.41 s |
| Typical output speed | 25.0 tok/s | 27.0 tok/s |
| Blended token price | $1.531 / 1M | $1.0772 / 1M |
| Typical route uptime | 94.22% | 99.87% |
Visual comparison
Price and performance charts
Estimated seconds using recent median response-start and output-speed data. Lower is better.
StreamLake has the lower typical same-model response ratio across 10 measured models.
USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.
StreamLake has the lower typical price ratio across 10 priced shared models.
| Model | Phala | StreamLake |
|---|---|---|
 GLM 5.2Winner · StreamLake z-ai/glm-5.2 | Phala
| StreamLake
|
 Kimi K2.6Winner · StreamLake moonshotai/kimi-k2.6 | Phala
| StreamLake
|
GLM 5.1Winner · StreamLake z-ai/glm-5.1 | Phala
| StreamLake
|
 Qwen3.5 397B A17BWinner · StreamLake qwen/qwen3.5-397b-a17b | Phala
| StreamLake
|
 MiniMax M2.5Winner · StreamLake minimax/minimax-m2.5 | Phala
| StreamLake
|
GLM 5Winner · StreamLake z-ai/glm-5 | Phala
| StreamLake
|
Kimi K2.5Winner · StreamLake moonshotai/kimi-k2.5 | Phala
| StreamLake
|
GLM 4.7Winner · StreamLake z-ai/glm-4.7 | Phala
| StreamLake
|
 DeepSeek V3.2Winner · StreamLake deepseek/deepseek-v3.2 | Phala
| StreamLake
|
Qwen3 30B A3B Instruct 2507Winner · Phala qwen/qwen3-30b-a3b-instruct-2507 | Phala
| StreamLake
|
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.
Phala vs StreamLake analysis
How Phala and StreamLake compare for AI inference
Phala and StreamLake share 10 indexed text models, including GLM 5.2, Kimi K2.6, GLM 5.1, Qwen3.5 397B A17B, MiniMax M2.5. StreamLake has the stronger typical response-time result on the directly measured set.
Same-model speed evidence
10 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
10 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
Phala has 18 indexed models and lists no published server regions; StreamLake has 20 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.
Related same-model benchmarks
Compare with other providers
Explore qualified alternatives with the most shared measured models. Recommendations include comparisons for both Phala and StreamLake.
