Pairwise benchmark snapshot · Aug 16, 2026

DeepSeek R1 vs Gemini 2.0 Flash Thinking benchmark

Name: DeepSeek R1 vs Gemini 2.0 Flash Thinking AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares DeepSeek R1 (DeepSeek) and Gemini 2.0 Flash Thinking (Google) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, Gemini 2.0 Flash Thinking is ahead by 132 points (1,490 vs 1,358; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Gemini 2.0 Flash Thinking resolves 66.8% versus 65.2% (seed-bootstrap (Aug 1, 2026)). Gemini 2.0 Flash Thinking streams faster (115 tok/s) while Gemini 2.0 Flash Thinking is the cheaper output token ($0.4/1M). Gemini 2.0 Flash Thinking has the larger context window (1M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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DeepSeek

DeepSeek R1

Open-weights reasoning model trained with large-scale RL.

Elo 1,358$2.5/1M out

Google

Gemini 2.0 Flash Thinking

Google experimental reasoning model that visualizes thoughts in real-time.

Elo 1,490$0.4/1M out

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek R1 (0)vsGemini 2.0 Flash Thinking (10)

DeepSeek R1: 0W (0%)Overall: Gemini 2.0 Flash ThinkingGemini 2.0 Flash Thinking: 10W (100%)

← DeepSeek R1Gemini 2.0 Flash Thinking →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,358vs1,490

Coding Elo

—vs1,515

SWE-bench

65.2%vs66.8%

LiveBench

59%vs67%

GPQA Diamond

79.8%vs81%

DeepSeek R1: 0WGemini 2.0 Flash Thinking: 5W

Gemini 2.0 Flash Thinking (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs115 tok/s

Time to first token

420 msvs220 ms

DeepSeek R1: 0WGemini 2.0 Flash Thinking: 2W

Gemini 2.0 Flash Thinking (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$0.4/1M

Input price

$0.7/1Mvs$0.1/1M

Context window

64kvs1M

DeepSeek R1: 0WGemini 2.0 Flash Thinking: 3W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGemini 2.0 Flash Thinking 6/6

Preference Elo

Gemini 2.0 Flash Thinking

132 pts advantage

Throughput Speed

Gemini 2.0 Flash Thinking

53 tok/s faster

Price Efficiency

Gemini 2.0 Flash Thinking

$2.10/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,358

EloHigh is better

1,490+10%

Code Elo

High is better

—

Code EloHigh is better

1,515

LiveBench

High is better

59%

LiveBenchHigh is better

67%+14%

SWE-bench

High is better

65.2%

SWE-benchHigh is better

66.8%+2%

GPQA

High is better

79.8%

GPQAHigh is better

81%+2%

TTFT

Low is better

420 ms

TTFTLow is better

220 ms+91%

Speed

High is better

62 tok/s

SpeedHigh is better

115 tok/s+85%

In $

Low is better

$0.7/1M

In $Low is better

$0.1/1M+600%

Out $

Low is better

$2.5/1M

Out $Low is better

$0.4/1M+525%

Context

High is better

64k

ContextHigh is better

1M+1538%

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 85% with Gemini 2.0 Flash Thinking

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

DeepSeek R1$62.00 / mo

In: $24.50Out: $37.50

Gemini 2.0 Flash Thinking$9.50 / mo

In: $3.50Out: $6.00

Estimated Cost Delta

Gemini 2.0 Flash Thinking is estimated to save $52.50/month ($630/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Gemini 2.0 Flash Thinking:Pick Gemini 2.0 Flash Thinking when repo-level coding accuracy is the constraint.
2
Gemini 2.0 Flash Thinking:Pick Gemini 2.0 Flash Thinking when time-to-first-token matters more than peak Elo.
3
Gemini 2.0 Flash Thinking:Pick Gemini 2.0 Flash Thinking for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatGemini 2.0 Flash Thinking

Lower output list price ($0.4/1M).

Voice / low-latency UIGemini 2.0 Flash Thinking

Lower TTFT (220 ms).

Long-document RAGGemini 2.0 Flash Thinking

Larger window (1M).

Screenshots / visionGemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 2.0 Flash Thinking	Higher SWE-bench (66.8%).
High-volume chat	Gemini 2.0 Flash Thinking	Lower output list price ($0.4/1M).
Voice / low-latency UI	Gemini 2.0 Flash Thinking	Lower TTFT (220 ms).
Long-document RAG	Gemini 2.0 Flash Thinking	Larger window (1M).
Screenshots / vision	Gemini 2.0 Flash Thinking	Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

launchJan 20, 2025

DeepSeek R1 stays as the open-weights RL baseline

Jan 2025 reasoning model. Still searched. V4 Pro is the newer DeepSeek buy.

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LIVE

DeepSeek

DeepSeek R1

Elo 1,358

LiveBench59%

SWE-bench65.2%

Speed62 tok/s

Output cost$2.5/1M

Google

Gemini 2.0 Flash Thinking

Elo 1,490

LiveBench67%

SWE-bench66.8%

Speed115 tok/s

Output cost$0.4/1M

Frequently Asked Questions

Which is better overall, DeepSeek R1 or Gemini 2.0 Flash Thinking?: Gemini 2.0 Flash Thinking has the higher preference Elo in our latest snapshot (1,490). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, DeepSeek R1 or Gemini 2.0 Flash Thinking?: Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 65.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Gemini 2.0 Flash Thinking output tokens are $0.4/1M versus $2.5/1M. Input prices and retry rates still move the real bill.
Which is faster, DeepSeek R1 or Gemini 2.0 Flash Thinking?: Gemini 2.0 Flash Thinking has the lower time-to-first-token (220 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Gemini 2.0 Flash Thinking accepts 1M tokens versus 64k.
Can I self-host either model?: DeepSeek R1 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. DeepSeek R1 and Gemini 2.0 Flash Thinking Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All DeepSeek R1 matchups →|All Gemini 2.0 Flash Thinking matchups →

DeepSeek R1 vs DeepSeek V3 (previous deepseek)DeepSeek R1 vs DeepSeek V4 Pro (next deepseek)Gemini 2.0 Flash Thinking vs Gemini 2.5 Flash (next gemini-flash)DeepSeek V4 Flash vs Gemini 2.0 Flash Thinking Gemini 3 Flash vs Gemini 2.0 Flash Thinking Gemini 3.6 Flash vs Gemini 2.0 Flash Thinking

DeepSeek R1 vs Gemini 2.0 Flash Thinking benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

DeepSeek R1 (0)vsGemini 2.0 Flash Thinking (10)

DeepSeek R1: 0W (0%)Overall: Gemini 2.0 Flash ThinkingGemini 2.0 Flash Thinking: 10W (100%)

← DeepSeek R1Gemini 2.0 Flash Thinking →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,358vs1,490

Coding Elo

—vs1,515

SWE-bench

65.2%vs66.8%

LiveBench

59%vs67%

GPQA Diamond

79.8%vs81%

DeepSeek R1: 0WGemini 2.0 Flash Thinking: 5W

Gemini 2.0 Flash Thinking (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

62 tok/svs115 tok/s

Time to first token

420 msvs220 ms

DeepSeek R1: 0WGemini 2.0 Flash Thinking: 2W

Gemini 2.0 Flash Thinking (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$2.5/1Mvs$0.4/1M

Input price

$0.7/1Mvs$0.1/1M

Context window

64kvs1M

DeepSeek R1: 0WGemini 2.0 Flash Thinking: 3W

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatGemini 2.0 Flash Thinking

Lower output list price ($0.4/1M).

Voice / low-latency UIGemini 2.0 Flash Thinking

Lower TTFT (220 ms).

Long-document RAGGemini 2.0 Flash Thinking

Larger window (1M).

Screenshots / visionGemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 2.0 Flash Thinking	Higher SWE-bench (66.8%).
High-volume chat	Gemini 2.0 Flash Thinking	Lower output list price ($0.4/1M).
Voice / low-latency UI	Gemini 2.0 Flash Thinking	Lower TTFT (220 ms).
Long-document RAG	Gemini 2.0 Flash Thinking	Larger window (1M).
Screenshots / vision	Gemini 2.0 Flash Thinking	Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, DeepSeek R1 or Gemini 2.0 Flash Thinking?

Gemini 2.0 Flash Thinking has the higher preference Elo in our latest snapshot (1,490). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, DeepSeek R1 or Gemini 2.0 Flash Thinking?

Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 65.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Gemini 2.0 Flash Thinking output tokens are $0.4/1M versus $2.5/1M. Input prices and retry rates still move the real bill.

Which is faster, DeepSeek R1 or Gemini 2.0 Flash Thinking?

Gemini 2.0 Flash Thinking has the lower time-to-first-token (220 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Gemini 2.0 Flash Thinking accepts 1M tokens versus 64k.

Can I self-host either model?

DeepSeek R1 is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. DeepSeek R1 and Gemini 2.0 Flash Thinking Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Gemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

DeepSeek R1

Gemini 2.0 Flash Thinking

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Gemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

DeepSeek R1

Gemini 2.0 Flash Thinking

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons