In 2026, choosing an AI coding assistant is harder than picking a programming language. Every new model promises more context, higher speed, and lower cost. But what actually works faster, and where are you paying for the brand?

Models Comparison

All metrics are based on open benchmarks (Artificial Analysis). The Intelligence score is an aggregated index of code understanding and logic.

Claude Opus 5 63
Anthropic · 1M context
Price$2.34
Tokens/s61
Latency72.6s
Response80.9s
GPT-5.6 Sol 61
OpenAI · 1M context
Price$1.23
Tokens/s68
Latency213.5s
Response220.9s
Grok 4.6 61
SpaceXAI · 500k context
Price$0.84
Tokens/s66
Latency45.4s
Response53.1s
Kimi K3 60
Kimi · 1.05M context
Price$0.84
Tokens/s41
Latency2.69s
Response64.3s
GLM-5.3 60
Z AI · 1M context
Price$0.68
Tokens/s93
Latency1.92s
Response28.8s

Speed & Price Visualization

Claude 5
61
GPT-5.6
68
Grok 4.6
66
Kimi K3
41
GLM-5.3
93
Intelligence 60–63 Best price/speed Max tokens/s

Latency & End‑to‑End Response

Claude 5
72.6s
GPT-5.6
213.5s
Grok 4.6
45.4s
Kimi K3
2.69s
GLM-5.3
1.92s
First‑chunk latency — critical for interactive work
Data aggregated from Artificial Analysis Intelligence Index. Source: artificialanalysis.ai

My Personal Choice for Coding

If you need a balance of price and performance — GLM-5.3 delivers 93 tokens/s at $0.68, with near‑instant latency. For complex architectural tasks, Claude Opus 5 remains the king of code understanding, but the price is steep. Grok 4.6 is a solid compromise, and Kimi K3 impresses with 1.05M context — great for large codebases.

The next post will be inside the virtual lab about Three.js WebGL — how to implement this technology in your project, in full detail. Stay tuned!
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