Noometry

Model comparison

DeepSeek-R1 vs Gemini 3.5 Flash

Gemini 3.5 Flash is the stronger model overall, scoring 54.2 to 42.3 on the Noometry Index. DeepSeek-R1 costs 3.7× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.

Last verified . 28 shared benchmarks.

DeepSeek-R1 DeepSeek

42.3

Rank #115 Confirmed

Gemini 3.5 Flash Google

54.2

Rank #32 Confirmed

Summary

  • They share 28 benchmarks with published results for both. DeepSeek-R1 scores higher in 2 categories and Gemini 3.5 Flash in 7 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Gemini 3.5 Flash leads 62.8 to 18.6.
  • The biggest single-benchmark swing is ARC-AGI-1: 21.2% for DeepSeek-R1 and 92.5% for Gemini 3.5 Flash.
  • DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $1.50 / $9 for Gemini 3.5 Flash.
  • Gemini 3.5 Flash accepts more context: 1.05M tokens versus 164K.

Side by side

DeepSeek-R1Gemini 3.5 Flash
ProviderDeepSeekGoogle
Noometry Index42.354.2
Released2025-01-202026-05-19
WeightsProprietaryProprietary
Context window164K1.05M
Max output64K66K
Input $ / M tokens$0.50$1.50
Output $ / M tokens$2.15$9
Results tracked5254

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Category by category

Coding Gemini 3.5 Flash leads

DeepSeek-R1: 46.3 (#68), Gemini 3.5 Flash: 49.4 (#49)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
SciCode35.7%53.1%
WeirdML41.6%62.6%
LMArena Coding14271492
ALE-Bench804.12911.02
SWE-bench Verified—79.3%
DeepSWE—37.4%
Aider Polyglot71.4%—
LMArena WebDev—1499
LiveBench Coding66.7%—
AlgoTune1.7—

Agentic & Tool Use DeepSeek-R1 leads

DeepSeek-R1: 30.7 (#75), Gemini 3.5 Flash: 24.7 (#114)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
APEX-Agents—27.5%
DeepResearch Bench35.1%—
BALROG34.9%—
GBAEval—6.7%
GDP.pdf—14%
METR Time Horizons53.8%—
Vending-Bench 2—5,396

Reasoning Gemini 3.5 Flash leads

DeepSeek-R1: 18.6 (#278), Gemini 3.5 Flash: 62.8 (#18)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
ARC-AGI-21.3%72.1%
SimpleBench40.8%76.7%
ARC-AGI-121.2%92.5%
CritPt1.1%13.1%
LMArena Hard Prompts14161488
Epoch Capabilities Index141.29154.46
ForecastBench6059
Kagi LLM Benchmark69.4%—
NYT Connections (extended)—92.6%
Chess Puzzles—50%
EnigmaEval—25.4%
EBR-Bench—4.8%
LiveBench Reasoning83.2%—
Mystery Game Puzzles—32%
DTBench—94.7%
LiveBench Data Analysis69.8%—
LMCA—47.1%
Surface Evolver Bench—58.1%
LiveBench71.6%—

Math Gemini 3.5 Flash leads

DeepSeek-R1: 43.8 (#79), Gemini 3.5 Flash: 60.7 (#36)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
OTIS Mock AIME 2024-202566.4%95.6%
LMArena Math14001504
FrontierMath (Tiers 1-3)—62.8%
FrontierMath Tier 4—26.8%
MathArena Final-Answer Competitions—76.3%
ProofBench—31%
Omni-MATH42.4%—
LiveBench Math80.7%—
MATH Level 596.6%—
FrontierMath (Feb 2025 set)—39%
FrontierMath Tier 4 (v1)—14.6%

Knowledge Gemini 3.5 Flash leads

DeepSeek-R1: 44.5 (#87), Gemini 3.5 Flash: 66.3 (#11)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
GPQA Diamond76.3%92.8%
LMArena Expert13941495
SimpleQA Verified—66.2%
MMLU-Pro79.3%—
Confabulations12.7%—
Vectara Hallucination Rate11.3%—
GPQA (HELM)66.6%—

Multimodal Not comparable

DeepSeek-R1: —, Gemini 3.5 Flash: 45.7 (#15)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
LMArena Vision—1310
Blueprint-Bench 2—33.6%
LMArena Document—1463

Multilingual Gemini 3.5 Flash leads

DeepSeek-R1: 52.4 (#85), Gemini 3.5 Flash: 57.0 (#13)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
LMArena Non-English14121476
LMArena Chinese14421526
LMArena French14171490
LMArena German14041492
LMArena Japanese13911486
LMArena Korean13601451
LMArena Russian14231493
LMArena Spanish14111480

Instruction Following Gemini 3.5 Flash leads

DeepSeek-R1: 72.0 (#143), Gemini 3.5 Flash: 77.0 (#30)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
LMArena Instruction Following13821467
LiveBench Instruction Following80.5%—
IFEval78.4%—

Long Context Too close to call

DeepSeek-R1: 45.4 (#36), Gemini 3.5 Flash: 45.4 (#38)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
LMArena Longer Query13911482
Fiction.LiveBench75%—

Writing & Preference Gemini 3.5 Flash leads

DeepSeek-R1: 61.4 (#88), Gemini 3.5 Flash: 65.5 (#47)

BenchmarkDeepSeek-R1Gemini 3.5 Flash
LMArena Text14281482
LMArena Creative Writing14051470
LMArena Multi-Turn14051481
Short-Story Creative Writing83%—
EQ-Bench Creative Writing1500—
WildBench82.8%—
EQ-Bench 4—1087
LiveBench Language48.5%—

Frequently asked questions

Is DeepSeek-R1 better than Gemini 3.5 Flash?

Gemini 3.5 Flash is the stronger model overall, scoring 54.2 to 42.3 on the Noometry Index. DeepSeek-R1 costs 3.7× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.

Which is cheaper, DeepSeek-R1 or Gemini 3.5 Flash?

DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Gemini 3.5 Flash lists at $1.50 and $9.

Is DeepSeek-R1 or Gemini 3.5 Flash better for coding?

Gemini 3.5 Flash scores higher on coding benchmarks: 49.4 versus 46.3 in the Noometry coding category.

Which has the bigger context window?

Gemini 3.5 Flash does, with 1.05M tokens against 164K.

How many benchmarks do DeepSeek-R1 and Gemini 3.5 Flash share?

28 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Gemini 3.5 Flash has 54.

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