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Kimi K2 0905 API Benchmarks: Latency, Throughput & Cost
Published on 2026.04.03 by han
Kimi K2 0905 API Benchmarks: Latency, Throughput & Cost

About Kimi K2 0905

Kimi K2 0905 is a state-of-the-art large language model developed by Moonshot AI, representing a significant advancement in open-weight AI capabilities. This Mixture-of-Experts (MoE) model features 1 trillion total parameters with 32 billion activated parameters per forward pass, making it highly efficient while maintaining frontier-level performance. The model supports a 256k token context window and excels at agentic coding intelligence, tool calling, frontend development, and long-horizon autonomous tasks.

Trained using the innovative MuonClip optimizer on 15.5 trillion tokens, Kimi K2 0905 delivers exceptional performance across coding, math, and reasoning benchmarks. It is specifically designed for tool use, reasoning, and autonomous problem-solving — making it well suited for developers building AI agents and complex automation workflows.

Kimi K2 0905 is now available across multiple inference providers. This analysis breaks down which one delivers the best performance, lowest cost, and fastest response times for your use case.

Kimi K2 0905 API Review Summary

  • DeepInfra is the overall recommended provider: lowest blended price ($0.80/1M tokens) and lowest latency (0.53s TTFT) among all 4 tracked providers.
  • Groq leads on throughput: 202.1 t/s — nearly 3x faster than the next competitor, with the fastest E2E time (3.73s for 500 tokens).
  • Price spread: DeepInfra at $0.80/1M vs Groq at $1.50/1M — nearly 2x more expensive for Groq’s speed advantage.
  • All 4 providers support JSON Mode and Function Calling — feature parity across the board.
  • Context window note: DeepInfra offers 131k tokens vs 262k for Groq, Fireworks, and Novita.

Kimi K2 0905 — Best APIs

ProviderWhy NotableSpeed (t/s)TTFT (s)Blended ($/1M)E2E (s)ContextJSONFunc
DeepInfraBest overall value: lowest price + lowest latency with solid throughput77.70.53s$0.806.96s131kYesYes
GroqBest for throughput-intensive workloads: fastest generation speed202.11.26s$1.503.73s262kYesYes
FireworksMid-pack performance; higher cost than DeepInfra42.51.44s$1.2013.22s262kYesYes
NovitaBudget alternative; slowest speed and highest latency27.51.99s$1.0720.18s262kYesYes

Quick Verdict: Which Kimi K2 0905 Provider is Best?

Based on benchmarks across 4 tracked providers, DeepInfra is the recommended API for production-scale Kimi K2 0905 deployment. It offers the lowest latency (0.53s TTFT), the lowest blended price ($0.80/1M tokens), and solid throughput (77.7 t/s). The only scenario where an alternative makes sense is when maximum generation speed is the primary requirement — in which case Groq’s 202.1 t/s throughput justifies its premium pricing.

Overall Winner: DeepInfra

DeepInfra delivers the optimal balance of performance and cost for Kimi K2 0905, making it the best choice for the vast majority of production deployments.

  • Output Speed: 77.7 t/s
  • Latency (TTFT): 0.53s (fastest among all providers)
  • End-to-End (500 tokens): 6.96s
  • Blended Price: $0.80 / 1M tokens (cheapest available)
  • Input Price: $0.40 / 1M tokens
  • Output Price: $1.20 / 1M tokens
  • Context Window: 131,072 tokens
  • API Features: JSON Mode + Function Calling

DeepInfra’s sub-second latency (0.53s) makes it ideal for interactive applications where responsiveness directly impacts user experience. Combined with its industry-leading pricing, it offers the best total cost of ownership for production workloads. The slightly smaller context window (131k vs 262k) may be a consideration for extremely long-context applications, but for the vast majority of use cases, DeepInfra delivers unmatched value.

Best for Throughput: Groq

Groq’s custom LPU (Language Processing Unit) architecture delivers unparalleled generation speed, making it the go-to choice for throughput-intensive applications.

  • Output Speed: 202.1 t/s (fastest — by a wide margin)
  • Latency (TTFT): 1.26s
  • End-to-End (500 tokens): 3.73s (fastest overall)
  • Blended Price: $1.50 / 1M tokens
  • Input Price: $0.40 / 1M tokens
  • Output Price: $2.00 / 1M tokens
  • Context Window: 262,144 tokens
  • API Features: JSON Mode + Function Calling

Groq’s 202.1 t/s output speed is nearly 3x faster than the next competitor, making it exceptional for batch processing, real-time streaming applications, or scenarios where generation time is the critical bottleneck. However, this performance comes at a premium — at $1.50/1M blended, it costs nearly double DeepInfra’s rate. Choose Groq when raw speed matters more than cost optimisation.

Mid-Tier Option: Fireworks

Fireworks offers a middle-ground option with reliable performance but doesn’t lead in any single metric.

  • Output Speed: 42.5 t/s
  • Latency (TTFT): 1.44s
  • End-to-End (500 tokens): 13.22s
  • Blended Price: $1.20 / 1M tokens
  • Input Price: $0.40 / 1M tokens
  • Output Price: $2.00 / 1M tokens
  • Context Window: 262,144 tokens
  • API Features: JSON Mode + Function Calling

Fireworks provides consistent, reliable service with full feature support and a larger context window than DeepInfra. It is a reasonable choice for enterprises already integrated into the Fireworks ecosystem, though DeepInfra offers better value across all performance metrics for new deployments.

Budget Alternative: Novita

Novita offers lower pricing than Groq and Fireworks, but with significant performance trade-offs that limit its practical applicability.

  • Output Speed: 27.5 t/s (slowest in the benchmark)
  • Latency (TTFT): 1.99s (highest in the benchmark)
  • End-to-End (500 tokens): 20.18s
  • Blended Price: $1.07 / 1M tokens
  • Input Price: $0.40 / 1M tokens
  • Output Price: $1.74 / 1M tokens
  • Context Window: 262,144 tokens
  • API Features: JSON Mode + Function Calling

Novita’s pricing falls between DeepInfra and Fireworks, but its performance lags significantly behind all three. A 20-second end-to-end time for 500 tokens makes it unsuitable for latency-sensitive applications. DeepInfra still offers better pricing with vastly superior performance, making Novita difficult to recommend for most use cases.

Looking Ahead: Kimi K2.5

For teams planning future projects, Moonshot AI’s newer Kimi K2.5 model — released in January 2026 — represents a significant evolution with several key upgrades:

  • Native Multimodality: Built through continual pretraining on approximately 15 trillion mixed visual and text tokens, K2.5 treats images, video, and text as first-class inputs — enabling visual-to-code workflows and image-grounded reasoning.
  • Agent Swarm Paradigm: K2.5 can self-direct up to 100 specialized AI sub-agents working in parallel, reducing execution time by up to 4.5x compared to single-agent approaches — ideal for complex, multi-step workflows.
  • Enhanced Coding Capabilities: Improved frontend code quality and design expressiveness, with the ability to generate fully functional, visually appealing interfaces directly from natural language.

If your use case involves vision-based inputs, multi-agent orchestration, or advanced UI generation, Kimi K2.5 is worth evaluating for your next project.

Conclusion

For Kimi K2 0905 deployments, DeepInfra is the recommended provider for most use cases. Its combination of the lowest latency (0.53s TTFT), the lowest blended price ($0.80/1M tokens), solid throughput (77.7 t/s), and full JSON Mode and Function Calling support makes it the optimal choice for production applications.

  • Choose DeepInfra for the best overall value — lowest cost, lowest latency, and full feature support.
  • Choose Groq when maximum generation speed (202.1 t/s) is the primary requirement and the 2x price premium is acceptable.
  • Choose Fireworks if you require a 262k context window and are already integrated into the Fireworks ecosystem.
  • Avoid Novita for latency-sensitive workloads — its 20s E2E time for 500 tokens makes it unsuitable for interactive applications.

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