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deepseek-r1 vs gemini-3.5-flash

Side-by-side comparison of deepseek-r1 and gemini-3.5-flash: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gemini-3.5-flash outperforms deepseek-r1 on 6 of 6 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
deepseek-r120.1%
gemini-3.5-flash50.2%
Coding Indexcoding
deepseek-r1N/A
gemini-3.5-flash70.1%
Math Indexmath
deepseek-r176.0%
gemini-3.5-flashN/A
GPQA Diamondreasoning
deepseek-r181.3%
gemini-3.5-flash92.2%
AIME 2025math
deepseek-r176.0%
gemini-3.5-flashN/A
LiveCodeBenchcoding
deepseek-r177.0%
gemini-3.5-flashN/A
Terminal-Bench Hardagentic
deepseek-r115.9%
gemini-3.5-flash40.9%
τ²-Benchagentic
deepseek-r136.5%
gemini-3.5-flash95.3%
SciCodecoding
deepseek-r140.3%
gemini-3.5-flash53.1%
MMLU Proknowledge
deepseek-r184.9%
gemini-3.5-flashN/A
Humanity's Last Examreasoning
deepseek-r114.9%
gemini-3.5-flash41.0%

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

deepseek-r1gemini-3.5-flash
Input price / 1M$4.00$1.50
Output price / 1M$4.00$9.00
Context window64K tokens1.0M tokens
Max outputN/A66K tokens
Vision inputN/AYes
Tool callingYesYes
ReasoningN/AYes
Prompt cachingN/AYes
Computer useN/AN/A
ProviderNovita AIGoogle LLC (Vertex AI)

Questions people ask

Is deepseek-r1 better than gemini-3.5-flash?
gemini-3.5-flash outperforms deepseek-r1 on 6 of 6 shared benchmarks. See the benchmark comparison above for specifics: deepseek-r1 and gemini-3.5-flash have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, deepseek-r1 or gemini-3.5-flash?
deepseek-r1 is cheaper. deepseek-r1 costs $4.00/$4.00 per 1M input/output tokens, while gemini-3.5-flash costs $1.50/$9.00.
Can I use deepseek-r1 and gemini-3.5-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 "novita/deepseek/deepseek-r1" and "vertex/gemini-3.5-flash", no other code changes needed.
What are the context windows?
deepseek-r1 supports up to 64K tokens of context. gemini-3.5-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 deepseek-r1 and gemini-3.5-flash with one line of code

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