---
title: "DeepSeek V4 Pro 0813 vs Claude Fable 5 on DeepSWE: Cost, Coding, and Routing"
description: "The DeepSWE benchmark comparison between DeepSeek V4 Pro 0813 and Claude Fable 5 reveals a trade-off between cost and accuracy. Claude Fable 5 leads on the first attempt with 69.7% pass@1 versus DeepSeek V4 Pro’s 62.8%, but costs 90 times more per rollout ($21.63 vs $0.24). Under repeated attempts, DeepSeek V4 Pro surpasses Fable, achieving 88.5% pass@4 compared to Fable’s 84.1%. The two models show unusually low per-task correlation (0.39), meaning they fail on different tasks. A cascade strategy that runs DeepSeek V4 Pro first and escalates to Claude Fable 5 only on failures solves 82.7% of tasks at $8.28 per task, outperforming either model used alone."
---

# DeepSeek V4 Pro 0813 vs Claude Fable 5 on DeepSWE: Cost, Coding, and Routing

[Together AI](https://yomu.fyi/company/together-ai) · Aug 17, 2026

**Type:** Benchmark

## Summary

The DeepSWE benchmark comparison between DeepSeek V4 Pro 0813 and Claude Fable 5 reveals a trade-off between cost and accuracy. Claude Fable 5 leads on the first attempt with 69.7% pass@1 versus DeepSeek V4 Pro’s 62.8%, but costs 90 times more per rollout ($21.63 vs $0.24). Under repeated attempts, DeepSeek V4 Pro surpasses Fable, achieving 88.5% pass@4 compared to Fable’s 84.1%. The two models show unusually low per-task correlation (0.39), meaning they fail on different tasks. A cascade strategy that runs DeepSeek V4 Pro first and escalates to Claude Fable 5 only on failures solves 82.7% of tasks at $8.28 per task, outperforming either model used alone.

## Context

Comparing DeepSeek V4 Pro 0813 and Claude Fable 5 on the DeepSWE benchmark to evaluate cost, coding accuracy, and routing strategy.

## Approach / What changed

Run DeepSeek V4 Pro 0813 first and escalate to Claude Fable 5 only when the test suite rejects the answer. This cascade solves 82.7% of DeepSWE tasks at $8.28 per task, beating both models used individually.

## Takeaways

- Claude Fable 5 achieves 69.7% pass@1 on DeepSWE, but costs $21.63 per rollout – 90 times more than DeepSeek V4 Pro’s $0.24 per rollout.
- DeepSeek V4 Pro 0813 matches Claude Fable 5 at pass@2 and exceeds it at pass@4, reaching 88.5% compared to Fable’s 84.1%.
- The optimal routing strategy is a cascade: run DeepSeek V4 Pro first, escalate to Claude Fable 5 on failure, solving 82.7% of tasks at $8.28 per task – better and cheaper than using either model alone.

## FAQ

### Which model is more cost-effective per task on DeepSWE?

DeepSeek V4 Pro 0813 is far more cost-effective, solving 260 tasks per $100 compared to Claude Fable 5's 3 tasks. At $0.24 per rollout, Pro is 90x cheaper than Fable's $21.63.

### What routing strategy yields the best accuracy at lowest cost?

A cascade that runs DeepSeek V4 Pro first and escalates to Claude Fable 5 only when the test suite rejects achieves 82.7% accuracy at $8.28 per task, more accurate than either model alone and cheaper than using Fable exclusively.

### How do the models compare on Rust tasks?

Claude Fable 5 achieves 85% on Rust, a 20-point margin over DeepSeek V4 Pro's 65%, making it the clear choice for Rust-heavy workloads despite its high cost.

**Tags:** [Claude](https://yomu.fyi/topic/claude), [Cost Optimization](https://yomu.fyi/topic/cost-optimization), [DeepSeek](https://yomu.fyi/topic/deepseek), [Model Routing](https://yomu.fyi/topic/model-routing)

- Source: [Together AI](https://www.together.ai/blog/deepseek-v4-pro-0813-vs-claude-fable-5-on-deepswe-cost-coding-and-routing)
- Source URL: https://www.together.ai/blog/deepseek-v4-pro-0813-vs-claude-fable-5-on-deepswe-cost-coding-and-routing
- Ingested by Yomu: 2026-09-19T10:13:45.807Z

[Read original post](https://www.together.ai/blog/deepseek-v4-pro-0813-vs-claude-fable-5-on-deepswe-cost-coding-and-routing)