When you are building an autonomous coding agent, "vibes" don't matter. What matters is exactly two things: Can the model write the correct file without hallucinating? And How fast can it do it?
To find out, we ran a gauntlet of real-world file manipulation tasks through the Mythos Router using its built-in Strict Write Discipline (SWD) engine.
Most benchmarks (like HumanEval or SWE-bench) test logic in a vacuum. They don't test a model's ability to navigate a messy, real-world filesystem with complex dependencies.
We tested the models on three specific agentic capabilities:
1. Target Accuracy: Can it find and modify the correct file?
2. Intent Adherence: Does it obey the strict [FILE_ACTION] schema?
3. Correction Speed: When the SWD verification loop rejects an operation, how fast does the model fix its mistake?
The Benchmark Results
Here is the raw data from 500 automated refactoring tasks run through the Mythos CLI.
| Model | Zero-Shot Accuracy | SWD Correction Rate | Avg Latency | Cost / 1M Tokens |
|---|---|---|---|---|
| Claude 3.5 Sonnet | 94.2% | 99.8% | 1.2s | $15.00 |
| DeepSeek V3 | 91.5% | 98.1% | 0.8s | $1.20 |
| GPT-4.5 | 86.4% | 92.3% | 1.5s | $10.00 |
Analysis: Claude is King, DeepSeek is the Future
Claude 3.5 Sonnet remains the undisputed heavyweight champion of agentic coding. It understands the SWD protocol almost perfectly out of the box, rarely requiring a correction turn. If you have the budget, this is your primary model.
DeepSeek V3, however, is the revelation of this benchmark. At literally less than 1/10th the cost of Claude, it performed within a 3% margin of error. Because Mythos Router uses an automatic error-correction loop, that 3% difference is easily caught and fixed by the system before it ever touches your disk.
GPT-4.5 struggled in comparison. Despite costing nearly 10x more than DeepSeek, it had the highest rate of path hallucinations and intent failures (86.4% zero-shot accuracy). While it remains a powerful general-purpose model, it is currently outclassed in strict agentic execution.
Because the Mythos Router catches and forces corrections on errors automatically, you can safely use cheaper models like DeepSeek V3 for 90% of your tasks, only falling back to Claude 3.5 when the context gets overwhelmingly complex.
The Optimal Setup
Based on these results, the absolute optimal configuration for the Mythos Router Orchestration Engine is:
// DeepSeek handles the volume. Claude handles the complex fallbacks.
export ANTHROPIC_API_KEY="..."
export DEEPSEEK_API_KEY="..."If you run npx mythos-router chat with both keys in your environment, the engine will dynamically route between them, giving you Claude-level reliability at DeepSeek prices.