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gemini-2.5-pro vs GLM-5.1

Side-by-side comparison of gemini-2.5-pro and GLM-5.1: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. GLM-5.1 outperforms gemini-2.5-pro on 7 of 7 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
gemini-2.5-pro34.6%
GLM-5.151.4%
Coding Indexcoding
gemini-2.5-pro32.0%
GLM-5.143.4%
Math Indexmath
gemini-2.5-pro87.7%
GLM-5.1N/A
GPQA Diamondreasoning
gemini-2.5-pro84.4%
GLM-5.186.8%
AIME 2025math
gemini-2.5-pro87.7%
GLM-5.1N/A
LiveCodeBenchcoding
gemini-2.5-pro80.1%
GLM-5.1N/A
Terminal-Bench Hardagentic
gemini-2.5-pro26.5%
GLM-5.143.2%
τ²-Benchagentic
gemini-2.5-pro54.1%
GLM-5.197.7%
SciCodecoding
gemini-2.5-pro42.8%
GLM-5.143.8%
MMLU Proknowledge
gemini-2.5-pro86.2%
GLM-5.1N/A
Humanity's Last Examreasoning
gemini-2.5-pro21.1%
GLM-5.128.0%

Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.

Pricing & specifications

gemini-2.5-proGLM-5.1
Input price / 1M$1.25$1.40
Output price / 1M$10.00$4.40
Context window1.0M tokens200K tokens
Max output66K tokens128K tokens
Vision inputYesYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer useN/AN/A
ProviderGoogle LLC (Gemini API)Z.ai

Questions people ask

Is gemini-2.5-pro better than GLM-5.1?
GLM-5.1 outperforms gemini-2.5-pro on 7 of 7 shared benchmarks. See the benchmark comparison above for specifics: gemini-2.5-pro and GLM-5.1 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, gemini-2.5-pro or GLM-5.1?
GLM-5.1 is cheaper. gemini-2.5-pro costs $1.25/$10.00 per 1M input/output tokens, while GLM-5.1 costs $1.40/$4.40.
Can I use gemini-2.5-pro and GLM-5.1 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "google/gemini-2.5-pro" and "zai/GLM-5.1", no other code changes needed.
What are the context windows?
gemini-2.5-pro supports up to 1.0M tokens of context. GLM-5.1 supports up to 200K tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.

Switch between gemini-2.5-pro and GLM-5.1 with one line of code

Requesty provides a single OpenAI-compatible API for 400+ models. Change the model parameter, not your code.

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