gemini-2.5-pro vs deepseek-v4-flash

Side-by-side comparison of gemini-2.5-pro and deepseek-v4-flash: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. deepseek-v4-flash outperforms gemini-2.5-pro on 5 of 5 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
gemini-2.5-pro25.9%
deepseek-v4-flash51.8%
Coding Indexcoding
gemini-2.5-pro33.3%
deepseek-v4-flash69.1%
Math Indexmath
gemini-2.5-pro87.7%
deepseek-v4-flashN/A
GPQA Diamondreasoning
gemini-2.5-pro84.4%
deepseek-v4-flash90.8%
AIME 2025math
gemini-2.5-pro87.7%
deepseek-v4-flashN/A
LiveCodeBenchcoding
gemini-2.5-pro80.1%
deepseek-v4-flashN/A
Terminal-Bench Hardagentic
gemini-2.5-pro26.5%
deepseek-v4-flashN/A
τ²-Benchagentic
gemini-2.5-pro54.1%
deepseek-v4-flashN/A
SciCodecoding
gemini-2.5-pro42.8%
deepseek-v4-flash49.9%
MMLU Proknowledge
gemini-2.5-pro86.2%
deepseek-v4-flashN/A
Humanity's Last Examreasoning
gemini-2.5-pro22.5%
deepseek-v4-flash38.6%

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-prodeepseek-v4-flash
Input price / 1M$1.25$0.14
Output price / 1M$10.00$0.28
Context window1.0M tokens1.0M tokens
Max output66K tokensN/A
Vision inputYesN/A
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesN/A
Computer useN/AN/A
ProviderGoogle LLC (Gemini API)Novita AI

Questions people ask

Is gemini-2.5-pro better than deepseek-v4-flash?
deepseek-v4-flash outperforms gemini-2.5-pro on 5 of 5 shared benchmarks. See the benchmark comparison above for specifics: gemini-2.5-pro and deepseek-v4-flash have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, gemini-2.5-pro or deepseek-v4-flash?
deepseek-v4-flash is cheaper. gemini-2.5-pro costs $1.25/$10.00 per 1M input/output tokens, while deepseek-v4-flash costs $0.14/$0.28.
Can I use gemini-2.5-pro and deepseek-v4-flash 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 "novita/deepseek/deepseek-v4-flash", no other code changes needed.
What are the context windows?
gemini-2.5-pro supports up to 1.0M tokens of context. deepseek-v4-flash 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 gemini-2.5-pro and deepseek-v4-flash with one line of code

Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.