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deepseek-r1 vs gemini-2.5-pro

Side-by-side comparison of deepseek-r1 and gemini-2.5-pro— benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gemini-2.5-pro outperforms deepseek-r1 on 11 of 11 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
deepseek-r127.1%
gemini-2.5-pro34.6%
Coding Indexcoding
deepseek-r124.0%
gemini-2.5-pro32.0%
Math Indexmath
deepseek-r176.0%
gemini-2.5-pro87.7%
GPQA Diamondreasoning
deepseek-r181.3%
gemini-2.5-pro84.4%
AIME 2025math
deepseek-r176.0%
gemini-2.5-pro87.7%
LiveCodeBenchcoding
deepseek-r177.0%
gemini-2.5-pro80.1%
Terminal-Bench Hardagentic
deepseek-r115.9%
gemini-2.5-pro26.5%
τ²-Benchagentic
deepseek-r136.5%
gemini-2.5-pro54.1%
SciCodecoding
deepseek-r140.3%
gemini-2.5-pro42.8%
MMLU Proknowledge
deepseek-r184.9%
gemini-2.5-pro86.2%
Humanity's Last Examreasoning
deepseek-r114.9%
gemini-2.5-pro21.1%

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

deepseek-r1gemini-2.5-pro
Input price / 1M$4.00$1.25
Output price / 1M$4.00$10.00
Context window64K tokens1.0M tokens
Max output66K tokens
Vision inputYes
Tool callingYesYes
ReasoningYes
Prompt cachingYes
Computer use
ProviderNovita AIGoogle LLC (Gemini API)

Questions people ask

Is deepseek-r1 better than gemini-2.5-pro?
gemini-2.5-pro outperforms deepseek-r1 on 11 of 11 shared benchmarks. See the benchmark comparison above for specifics — deepseek-r1 and gemini-2.5-pro have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — deepseek-r1 or gemini-2.5-pro?
deepseek-r1 is cheaper. deepseek-r1 costs $4.00/$4.00 per 1M input/output tokens, while gemini-2.5-pro costs $1.25/$10.00.
Can I use deepseek-r1 and gemini-2.5-pro through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch — "novita/deepseek/deepseek-r1" or "google/gemini-2.5-pro" — no other code changes needed.
What are the context windows?
deepseek-r1 supports up to 64K tokens of context. gemini-2.5-pro supports up to 1.0M 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 deepseek-r1 and gemini-2.5-pro with one line of code

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