DeepSeek V4 Pro vs. GLM-5.1: A Comparative Analysis

What the Benchmarks Show

DeepSeek V4 Pro and GLM-5.1 represent the latest generation of reasoning-focused AI, with both models demonstrating competitive performance across a range of standardized tests. DeepSeek V4 Pro holds a slight advantage in general intelligence, with an index of 51.5 compared to GLM-5.1’s 51.4. This marginal lead is mirrored in coding tasks, where DeepSeek V4 Pro scores 47.5 against GLM-5.1’s 43.4.

Looking at specific benchmarks, DeepSeek V4 Pro consistently outperforms its counterpart in GPQA (0.888 vs 0.868), HLE (0.359 vs 0.28), and SciCode (0.5 vs 0.438). It also demonstrates stronger performance in TerminalBench Hard and LCR. However, GLM-5.1 is not without its strengths; it actually edges out DeepSeek V4 Pro in the TAU2 benchmark, scoring 0.976 compared to 0.962. While both models show similar capabilities in IFBench, the data suggests that DeepSeek V4 Pro is better optimized for complex, multi-step reasoning and technical coding challenges, while GLM-5.1 remains highly competitive in specific task-oriented benchmarks.

Speed and Cost

The operational profiles of these two models reveal a clear trade-off between performance depth and speed. GLM-5.1 is significantly faster, delivering an output speed of 54.406 tokens per second, nearly double the 29.718 tokens per second offered by DeepSeek V4 Pro. Additionally, GLM-5.1 provides a faster time to first token at 0.929 seconds compared to 1.248 seconds for DeepSeek V4 Pro. For applications requiring near-instantaneous responses, GLM-5.1 is the more efficient engine.

Cost structures also differ slightly. DeepSeek V4 Pro has a blended cost of $2.17 per million tokens, while GLM-5.1 is marginally cheaper at $2.15 per million tokens. While the blended costs are nearly identical, the pricing models are structured differently: DeepSeek V4 Pro charges $1.74 for input and $3.48 for output, whereas GLM-5.1 charges $1.40 for input and $4.40 for output. Users with input-heavy workloads may find GLM-5.1 more economical, while those with output-heavy requirements might prefer the pricing structure of DeepSeek V4 Pro.

Which model fits which workflow

Choosing the right model requires an assessment of your specific operational constraints. DeepSeek V4 Pro is engineered for tasks where the quality of the reasoning process is the primary bottleneck. Its higher coding index and superior performance on benchmarks like HLE and SciCode make it the preferred tool for software development, scientific research, and complex data analysis where accuracy is non-negotiable.

GLM-5.1 is optimized for speed and responsiveness. Its superior output speed and lower latency make it ideal for real-time chat interfaces, customer support automation, or any application where the user experience is tied to the immediacy of the response. While it sacrifices a small margin of raw intelligence compared to DeepSeek V4 Pro, the gains in throughput allow for a more fluid interaction in high-traffic environments.

Decision takeaway

Ultimately, the decision rests on whether your project demands maximum reasoning depth or maximum operational velocity. DeepSeek V4 Pro is the more capable model for deep-thought tasks, while GLM-5.1 is the more responsive tool for high-speed, interactive deployments. Both models are highly capable, and their near-identical blended pricing ensures that the decision can be made purely on the basis of performance characteristics rather than cost.