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Kilo Code Model Selection Guide

Last updated: September 3, 2025.

The AI model landscape evolves rapidly, so this guide focuses on what's delivering excellent results with Kilo Code right now. We update this regularly as new models emerge and performance shifts.

Kilo Code Top Performers

ModelContext WindowSWE-Bench VerifiedHuman EvalLiveCodeBenchInput Price*Output Price*Best For
GPT-5400K tokens74.9%96.3%68.2%$1.25$10Latest capabilities, multi-modal coding
Claude Sonnet 41M tokens72.7%94.8%65.9%$3-6$15-22.50Enterprise code generation, complex systems
Grok Code Fast 1256K tokens70.8%92.1%63.4%$0.75$3.50Rapid development, cost-performance balance
Qwen3 Coder256K tokens68.4%91.7%61.8%$0.20$0.80Pure coding tasks, rapid prototyping
Gemini 2.5 Pro1M+ tokens67.2%89.9%59.3%TBDTBDMassive codebases, architectural planning

*Per million tokens

Budget-Conscious Options

ModelContext WindowSWE-Bench VerifiedHuman EvalLiveCodeBenchInput Price*Output Price*Notes
DeepSeek V3128K tokens64.1%87.3%56.7%$0.14$0.28Exceptional value for daily coding
DeepSeek R1128K tokens62.8%85.9%54.2%$0.55$2.19Advanced reasoning at budget prices
Qwen3 32B128K tokens60.3%83.4%52.1%VariesVariesOpen source flexibility
Z AI GLM 4.5128K tokens58.7%81.2%49.8%TBDTBDMIT license, hybrid reasoning system

*Per million tokens

Comprehensive Evaluation Framework

Latency Performance

Response times significantly impact development flow and productivity:

  • Ultra-Fast (< 2s): Grok Code Fast 1, Qwen3 Coder
  • Fast (2-4s): DeepSeek V3, GPT-5
  • Moderate (4-8s): Claude Sonnet 4, DeepSeek R1
  • Slower (8-15s): Gemini 2.5 Pro, Z AI GLM 4.5

Impact on Development: Ultra-fast models enable real-time coding assistance and immediate feedback loops. Models with 8+ second latency can disrupt flow state but may be acceptable for complex architectural decisions.

Throughput Analysis

Token generation rates affect large codebase processing:

  • High Throughput (150+ tokens/s): GPT-5, Grok Code Fast 1
  • Medium Throughput (100-150 tokens/s): Claude Sonnet 4, Qwen3 Coder
  • Standard Throughput (50-100 tokens/s): DeepSeek models, Gemini 2.5 Pro
  • Variable Throughput: Open source models depend on infrastructure

Scaling Factors: High throughput models excel when generating extensive documentation, refactoring large files, or batch processing multiple components.

Reliability & Availability

Enterprise considerations for production environments:

  • Enterprise Grade (99.9%+ uptime): Claude Sonnet 4, GPT-5, Gemini 2.5 Pro
  • Production Ready (99%+ uptime): Qwen3 Coder, Grok Code Fast 1
  • Developing Reliability: DeepSeek models, Z AI GLM 4.5
  • Self-Hosted: Qwen3 32B (reliability depends on your infrastructure)

Success Rates: Enterprise models maintain consistent output quality and handle edge cases more gracefully, while budget options may require additional validation steps.

Context Window Strategy

Optimizing for different project scales:

SizeWord CountTypical Use CaseRecommended ModelsStrategy
32K tokens~24,000 wordsIndividual components, scriptsDeepSeek V3, Qwen3 CoderFocus on single-file optimization
128K tokens~96,000 wordsStandard applications, most projectsAll budget models, Grok Code Fast 1Multi-file context, moderate complexity
256K tokens~192,000 wordsLarge applications, multiple servicesQwen3 Coder, Grok Code Fast 1Full feature context, service integration
400K+ tokens~300,000+ wordsEnterprise systems, full stack appsGPT-5, Claude Sonnet 4, Gemini 2.5 ProArchitectural overview, system-wide refactoring

Performance Degradation: Model effectiveness typically drops significantly beyond 400-500K tokens, regardless of advertised limits. Plan context usage accordingly.

Community Choice

The AI model landscape changes quicky to stay up to date 👉 check Kilo Code Community Favorites on OpenRouter