Kimi K2.7 Code API Provider Benchmarking & Analysis
This analysis is intended to support you in choosing the best API provider of Kimi K2.7 Code for your use-case.
Fastest
CoreWeave
Nebius (FP4)
Modular
Baseten
FireworksOutput speed
Total 9 providers
Lowest Latency
CoreWeaveModularNebius (FP4)BasetenFireworksTime to first answer token
Total 9 providers
Lowest Price
DeepInfraCoreWeaveModularBaseten
GMI (FP8)Blended price (per 1M tokens)
Total 9 providers
Kimi K2.7 Code is available through 9 API providers, each offering different performance characteristics and pricing. Below is a comparison of the key metrics across providers.
- For output speed, the top providers are CoreWeave (301.5 t/s), Nebius (FP4) (216.8 t/s), and Modular (202.8 t/s). Speed varies significantly across providers, with a 696% difference between the fastest and slowest.
- For latency, CoreWeave (8.48s), Modular (11.58s), and Nebius (FP4) (12.00s) offer the lowest time to first answer token.
- For pricing, DeepInfra (0.57), CoreWeave (0.60), and Modular (0.63) offer the lowest blended prices per 1M tokens. Prices vary up to 2.2x across providers.
- CoreWeave offers the best performance with both the highest speed and lowest latency. For cost optimization, DeepInfra provides the most competitive pricing.
Highlights
Update: Default performance benchmarking workload has updated to 10k input tokens to better reflect production use cases. You can still select different workloads above.
Pricing
Pricing: Cache Hit, Input, and Output
Pricing: Blended Price
Pricing: Cache Discount
Output Speed vs. Price
Speed
Measured by Output Speed (tokens per second)
Output Speed: Kimi K2.7 Code
Latency vs. Output Speed
Latency
Measured by Time (seconds) to First Token
Time to First Answer Token
End-to-End Response Time
Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time
Key Comparison Metrics & API Features
| Nebius | 256k | Open | $1.89 | 217 | 1.72 | 14.31 | 10.28 | ||
| GMI | 65.5k | Open | $1.20 | 76 | 5.09 | 40.81 | 29.17 | ||
| CoreWeave | 262k | Open | $0.89 | 301 | 1.09 | 10.14 | 7.39 | ||
| Baseten | 262k | Open | $0.76 | 175 | 0.45 | 16.04 | 12.73 | ||
| Modular | 262k | Open | $0.46 | 203 | 0.59 | 14.05 | 10.99 | ||
 Novita | 262k | Open | $0.55 | 76 | 3.67 | 39.52 | 29.28 | ||
| DeepInfra | 262k | Open | $0.39 | 38 | 1.05 | 73.08 | 58.84 | ||
| Fireworks | 262k | Open | $0.52 | 101 | 0.70 | 27.82 | 22.16 | ||
 Kimi | 256k | Open | $0.54 | 64 | 2.88 | 45.42 | 34.75 | ||
Frequently Asked Questions
Common questions about Kimi K2.7 Code providers
Kimi K2.7 Code is currently available through 9 API providers that we benchmark and track.
The fastest providers for Kimi K2.7 Code by output speed are CoreWeave (301.5 t/s), Nebius (FP4) (216.8 t/s), and Modular (202.8 t/s). Output speed measures how quickly tokens are generated after the model starts responding.
The providers with the lowest time to first answer token for Kimi K2.7 Code are CoreWeave (8.48s), Modular (11.58s), and Nebius (FP4) (12.00s). Lower latency means faster initial response time.
Prices for Kimi K2.7 Code vary up to 2.2x across providers. The most affordable is DeepInfra at $0.57 per 1M tokens, while Nebius (FP4) charges $1.25 per 1M tokens.
All 9 providers of Kimi K2.7 Code support JSON mode for structured output.
All 9 providers of Kimi K2.7 Code support function calling (tool use).
When choosing a provider for Kimi K2.7 Code, consider: output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and API features like JSON mode or function calling.
Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.
For information about Kimi K2.7 Code's intelligence, capabilities, modalities, and how it compares to other models, see the model overview page. View model overview