GPT-5.6, Claude, and Grok Coding Build-Off: Frontier vs Open-Weights Models

Frontier models continue to maintain a significant lead over open-weights alternatives in complex, novel coding tasks, though open-weights models are highly cost-effective for common problems. In a large-scale build-off involving 12 models across four distinct applications, GPT-5.6 Sol and Claude Fable 5 emerged as the top performers for high-complexity work, while Qwen 3.7 Plus and GLM-5.2 proved efficient for standard implementations.

Performance on Complex 3D and Logic Tasks

Frontier models are significantly more reliable when tasked with complex spatial reasoning and 3D rendering.

Doom-style Raycaster Maze

GPT-5.6 Sol and GPT-5.6 Luna achieved a 100% success rate (5/5 attempts), producing the most detailed and consistent results. While Muse Spark 1.1 showed high potential on successful runs, it was inconsistent, failing 3 out of 5 attempts. Open-weights models generally struggled, with GLM-5.2 failing to produce a moveable character in any attempt.

3D Rubik's Cube

Claude Fable 5 dominated this task with a perfect 5/5 success rate for clean solves. GPT-5.6 Sol and Terra also performed well (4/5), though GPT-5.6 Luna failed completely (0/5) as scrambling immediately broke the build. Claude Opus 4.8 unexpectedly failed to land a single flawless solve (0/5), highlighting a performance gap even within the same model family.

Functional Calculator

Claude models (Opus 4.8 and Fable 5) achieved perfect 5/5 success rates, with Fable 5 noted for superior styling. GPT-5.6 Sol also achieved 5/5 but was criticized for over-styling (attempting 3D renders) that hindered the user experience. Grok 4.5 and GPT-5.6 Luna also maintained 5/5 consistency.

Conway's Game of Life

Open-weights models, specifically Qwen 3.7 Plus and GLM-5.2, performed exceptionally well on this task. Because the Game of Life of the Game of Life is a well-trodden problem with extensive open-source examples, these models were able to deliver high-quality results at a fraction of the cost of frontier models.

Model Efficiency: Speed and Cost

There is a stark contrast in contrast in performance between the high-cost frontier models and the high-speed open-weights models.

Model	Time to First Token	Throughput	Cost per 1k Tokens
GPT-5.6 Luna	1.0s	97 tok/s	$0.001
Qwen 3.7 Plus	2.1s	204 tok/s	$0.001
Grok 4.5	3.0s	112 tok/s	$0.003
Claude Fable 5	6.6s	30 tok/s	$0.01
DeepSeek V4 Pro	9.3s	37 tok/s	$0.001

GPT-5.6 Luna is the fastest model for short prompts, while Qwen 3.7 Plus offers the highest throughput and lowest cost. DeepSeek V4 Pro and GLM-5.2 were noted as being significantly slower in their response times.

Creative SVG Rendering

In one-shot SVG generation tasks, Claude Fable 5 outperformed all other models in both detail and composition. In a complex scene depicting tech billionaires watching a rocket landing, Fable 5 produced a clean render with specific details like smoke and lighting effects. In contrast, GPT-5.6 models produced more cartoony and less precise results.

Summary of Model Positioning

• GPT-5.6 Sol & Claude Fable 5: The gold standard for complex, novel, or high-stakes coding projects.
• Grok 4.5: A highly competitive alternative to Claude Opus, offering a strong balance of performance and cost.
• Qwen 3.7 Plus & GLM-5.2: Ideal for ideal for standard, well-documented tasks where cost and speed are the primary drivers.
• Muse Spark 1.1: A promising a promising debut that sits between open-weights and frontier models but lacks the consistency required for primary use.