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Deep Seek-R1 vs Gemini 2.0 Flash-Lite: Benchmarks, Pricing, and Context Window Comparison

Deep Seek-R1 vs Gemini 2.0 Flash-Lite compares provider, context window, token pricing, benchmark performance, and release timeline in one side-by-side view. Use this page to quickly identify which model is a better fit for your production constraints, quality targets, and estimated cost per request.

Verdict

Gemini 2.0 Flash-Lite has lower listed token pricing, while Deep Seek-R1 can still be preferable if benchmark results better match your workload.

Author: Mirai Minds Research Team

Last updated:

Compare
Deep Seek-R1
to
Gemini 2.0 Flash-Lite
Overview
Deep Seek-R1 was released 2 months after Gemini 2.0 Flash-Lite.
Deep Seek-R1
Gemini 2.0 Flash-Lite
Provider
The entity that provides this model.
DeepSeek
Google
Input Context Window
The number of tokens supported by the input context window.
128K
tokens
1M
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
32K
tokens
8,192
tokens
Release Date
When the model was first released.
2025-01-21
2024-12-11
Leaderboard
Deep Seek-R1
Gemini 2.0 Flash-Lite
Rank
Unknown
Unknown
Arena Elo
Not specified.
Not specified.
95% CI
Not specified.
Not specified.
Votes
Not specified.
Not specified.
License
Not specified.
Not specified.
Knowledge Cutoff
Unknown
Unknown
Pricing
Deep Seek-R1
Gemini 2.0 Flash-Lite
Input
Cost of input data provided to the model.
$0.55
per million tokens
$0.075
per million tokens
Output
Cost of output tokens generated by the model.
$2.19
per million tokens
$0.30
per million tokens
Benchmarks
Compare relevant benchmarks between Deep Seek-R1 and Gemini 2.0 Flash-Lite Instruct.
Deep Seek-R1
Gemini 2.0 Flash-Lite
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
90.8
(5-shot)
Benchmark not available.
MMMU
A wide ranging multi-discipline and multimodal benchmark.
Benchmark not available.
HellaSwag
A challenging sentence completion benchmark.
Benchmark not available.
Benchmark not available.