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deepseek-ai/DeepSeek-R1 vs gemini-2.5-pro

Side-by-side comparison of deepseek-ai/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-ai/DeepSeek-R1 on 7 of 8 shared benchmarks.

Benchmark comparison

MMLU Proknowledge
deepseek-ai/DeepSeek-R185.0%
gemini-2.5-pro86.2%
GPQA Diamondreasoning
deepseek-ai/DeepSeek-R171.5%
gemini-2.5-pro84.0%
HumanEvalcoding
deepseek-ai/DeepSeek-R192.0%
gemini-2.5-pro93.2%
SWE-Bench Verifiedcoding
deepseek-ai/DeepSeek-R149.2%
gemini-2.5-pro63.8%
MATHmath
deepseek-ai/DeepSeek-R192.2%
gemini-2.5-pro91.4%
AIME 2024math
deepseek-ai/DeepSeek-R179.8%
gemini-2.5-pro88.0%
MMMUmultimodal
deepseek-ai/DeepSeek-R174.8%
gemini-2.5-pro81.7%
LiveBenchreasoning
deepseek-ai/DeepSeek-R171.5%
gemini-2.5-pro73.6%
τ-bench Retailagentic
deepseek-ai/DeepSeek-R1
gemini-2.5-pro69.8%

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-ai/DeepSeek-R1gemini-2.5-pro
Input price / 1M$3.00$1.25
Output price / 1M$7.00$10.00
Context window64K tokens1.0M tokens
Max output8K tokens66K tokens
Vision inputYes
Tool callingYes
ReasoningYes
Prompt cachingYes
Computer use
ProviderTogether AI Inc.Google LLC (Gemini API)

Questions people ask

Is deepseek-ai/DeepSeek-R1 better than gemini-2.5-pro?
gemini-2.5-pro outperforms deepseek-ai/DeepSeek-R1 on 7 of 8 shared benchmarks. See the benchmark comparison above for specifics — deepseek-ai/DeepSeek-R1 and gemini-2.5-pro have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — deepseek-ai/DeepSeek-R1 or gemini-2.5-pro?
deepseek-ai/DeepSeek-R1 is cheaper. deepseek-ai/DeepSeek-R1 costs $3.00/$7.00 per 1M input/output tokens, while gemini-2.5-pro costs $1.25/$10.00.
Can I use deepseek-ai/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 — "together/deepseek-ai/DeepSeek-R1" or "google/gemini-2.5-pro" — no other code changes needed.
What are the context windows?
deepseek-ai/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-ai/DeepSeek-R1 and gemini-2.5-pro with one line of code

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