---
title: "GLM-5.3 vs. GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing"
description: "GLM-5.3 and GPT-5.6 Sol were evaluated on 113 DeepSWE tasks with 904 rollouts, comparing accuracy, cost, and failure patterns. Sol edges ahead at pass@1 (72.7% vs 69.0%), but GLM-5.3 leads at pass@4 (87.6% vs 85.8%) at $3.99 per rollout, half Sol’s $8.37 cost and yielding 17 solves per $100 versus Sol’s 9. Their low per-task correlation of 0.43 makes a cascade effective: GLM-5.3 first, then Sol on test failure, achieving 85.9% solved at $6.61 per task. Sol runs faster (19 minutes, 61 steps vs 35 minutes, 124 steps) and achieves higher reliability (61 tasks solved all four tries vs 48), but it breaks passing tests in 20% of failures versus GLM-5.3’s 11%."
---

# GLM-5.3 vs. GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing

[Together AI](https://yomu.fyi/company/together-ai) · Aug 21, 2026

**Type:** Benchmark

## Summary

GLM-5.3 and GPT-5.6 Sol were evaluated on 113 DeepSWE tasks with 904 rollouts, comparing accuracy, cost, and failure patterns. Sol edges ahead at pass@1 (72.7% vs 69.0%), but GLM-5.3 leads at pass@4 (87.6% vs 85.8%) at $3.99 per rollout, half Sol’s $8.37 cost and yielding 17 solves per $100 versus Sol’s 9. Their low per-task correlation of 0.43 makes a cascade effective: GLM-5.3 first, then Sol on test failure, achieving 85.9% solved at $6.61 per task. Sol runs faster (19 minutes, 61 steps vs 35 minutes, 124 steps) and achieves higher reliability (61 tasks solved all four tries vs 48), but it breaks passing tests in 20% of failures versus GLM-5.3’s 11%.

## Approach / What changed

Run GLM-5.3 first and escalate to GPT-5.6 Sol only when the test suite rejects the answer. This cascade achieves 85.9% solved at $6.61 per task, which is cheaper than a single Sol rollout and beats a perfect one-shot oracle router.

## Takeaways

- GPT-5.6 Sol holds a narrow single-shot lead on DeepSWE (72.7% vs 69.0%), but GLM-5.3 performs better with multiple attempts, reaching 87.6% at four attempts (pass@4) at half the cost.
- A cascade strategy that uses GLM-5.3 first and escalates to Sol only on test failure solves 85.9% of tasks for $6.61 per task, outperforming both the individual models and a perfect one-shot oracle router.
- GLM-5.3 has a cleaner failure profile (11% regression rate vs Sol’s 20%) and excels at JavaScript and Rust, while Sol is faster, more reliable per attempt, and dominates protocol conformance and data modeling.

## FAQ

### What is the cascade strategy and what does it achieve?

The cascade runs GLM-5.3 first and escalates to GPT-5.6 Sol only when the test suite rejects the answer. It achieves 85.9% solved tasks at $6.61 per task, cheaper than a single Sol rollout and beating a perfect one-shot oracle router.

### How do the models compare in failure modes?

Sol breaks the existing test suite in 20% of its failures, compared to 11% for GLM-5.3. GLM-5.3's failures are mostly near misses (61%) that leave the baseline intact, making it safer to accept without heavy regression gating.

### In which domains does each model excel?

Sol dominates protocol conformance (59%), data modeling and serialization (92%), build and ops tooling (73%), and concurrency (72%). GLM-5.3 excels at query and config languages (88%), language and runtime internals (83%), stateful reactivity (73%), program analysis, JavaScript (90%), and Rust (70%).

**Tags:** [Benchmark](https://yomu.fyi/topic/benchmark), [Cost Optimization](https://yomu.fyi/topic/cost-optimization), [LLMs](https://yomu.fyi/topic/llm), [Routing](https://yomu.fyi/topic/routing)

- Source: [Together AI](https://www.together.ai/blog/glm-5-3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing)
- Source URL: https://www.together.ai/blog/glm-5-3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing
- Ingested by Yomu: 2026-09-19T10:13:46.701Z

[Read original post](https://www.together.ai/blog/glm-5-3-vs-gpt-5-6-sol-on-deepswe-cost-coding-and-routing)