Moonshot AI
3 indexed models
- Headquarters
Singapore- Server regions
- Singapore
- Model types
- 3 text
Same-model provider benchmark
Moonshot AI vs SiliconFlow: LLM provider comparison
Compare Moonshot AI and SiliconFlow on 3 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
SiliconFlow
36 indexed models
- Headquarters
- Singapore
- Server regions
United States- Model types
- 35 text, 1 embeddings
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
1.43× typical advantage
3 exact models with complete recent speed data
Lowest token cost
$1.512 / 1M
3 exact models using a 1K-input/500-output mix
Most models available
36 models
Complete catalog coverage across all indexed modalities
Shared-model benchmark summary
| Metric | Moonshot AI | SiliconFlow |
|---|---|---|
| Typical 500-token response | 25.58 s | 28.31 s |
| Typical response start | 2.58 s | 1.99 s |
| Typical output speed | 22.0 tok/s | 19.0 tok/s |
| Blended token price | $1.7778 / 1M | $1.512 / 1M |
| Typical route uptime | 100.00% | 97.48% |
Visual comparison
Price and performance charts
SiliconFlowEstimated seconds using recent median response-start and output-speed data. Lower is better.
Moonshot AI has the lower typical same-model response ratio across 3 measured models.
USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.
SiliconFlow has the lower typical price ratio across 3 priced shared models.
| Model | Moonshot AI | SiliconFlow |
|---|---|---|
 Kimi K2.7 CodeWinner · SiliconFlow moonshotai/kimi-k2.7-code | Moonshot AI
| SiliconFlow
|
Kimi K2.6Winner · Moonshot AI moonshotai/kimi-k2.6 | Moonshot AI
| SiliconFlow
|
Kimi K2.5Winner · Moonshot AI moonshotai/kimi-k2.5 | Moonshot AI
| SiliconFlow
|
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.
Moonshot AI vs SiliconFlow analysis
How Moonshot AI and SiliconFlow compare for AI inference
Moonshot AI and SiliconFlow share 3 indexed text models, including Kimi K2.7 Code, Kimi K2.6, Kimi K2.5. Moonshot AI 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
Moonshot AI has 3 indexed models and lists 1 published server region; SiliconFlow has 36 models and lists 1 region. 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 Moonshot AI and SiliconFlow.
