Model comparison

DeepSeek-R1 vs Gemini 3.8 Flash

Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 42.3 on the Noometry Index. DeepSeek-R1 costs 1.6× less per token, which makes it the better buy when Gemini 3.8 Flash's lead doesn't matter for your workload.

Last verified October 10, 2026. 27 shared benchmarks.

DeepSeek-R1

DeepSeek

42.3

Rank #115 Confirmed

Gemini 3.8 Flash

Google

61.8

Rank #11 Confirmed

Summary

They share 27 benchmarks with published results for both. DeepSeek-R1 scores higher in 0 categories and Gemini 3.8 Flash in 9 categories; 8 gaps are clear of the uncertainty.
The widest gap is in reasoning, where Gemini 3.8 Flash leads 76.9 to 18.6.
The biggest single-benchmark swing is ARC-AGI-2: 1.3% for DeepSeek-R1 and 89.2% for Gemini 3.8 Flash.
DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.8 Flash.
Gemini 3.8 Flash accepts more context: 1.05M tokens versus 164K.

Side by side

DeepSeek-R1 and Gemini 3.8 Flash specifications
	DeepSeek-R1	Gemini 3.8 Flash
Provider	DeepSeek	Google
Noometry Index	42.3	61.8
Released	2025-01-20	2026-09-02
Weights	Proprietary	Proprietary
Context window	164K	1.05M
Max output	64K	66K
Input $ / M tokens	$0.50	$0.75
Output $ / M tokens	$2.15	$3.75
Results tracked	52	50

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Category by category

Coding Gemini 3.8 Flash leads

DeepSeek-R1: 46.3 (#68), Gemini 3.8 Flash: 59.2 (#15)

Coding benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
SciCode	35.7%	56.6%
WeirdML	41.6%	84.8%
LMArena Coding	1427	1510
ALE-Bench	804.12	1,270
DeepSWE	—	73.8%
FrontierCode	—	41.2%
Aider Polyglot	71.4%	—
CursorBench	—	39.6%
LMArena WebDev	—	1584
FrontierSWE	—	19.6%
LiveBench Coding	66.7%	—
AlgoTune	1.7	—

Agentic & Tool Use Gemini 3.8 Flash leads

DeepSeek-R1: 30.7 (#75), Gemini 3.8 Flash: 41.8 (#21)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
APEX-Agents	—	64.3%
Remote Labor Index	—	5.8%
DeepResearch Bench	35.1%	—
BALROG	34.9%	—
GDP.pdf	—	23.4%
METR Time Horizons	53.8%	—
Vending-Bench 2	—	5,094

Reasoning Gemini 3.8 Flash leads

DeepSeek-R1: 18.6 (#278), Gemini 3.8 Flash: 76.9 (#5)

Reasoning benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
ARC-AGI-2	1.3%	89.2%
ARC-AGI-1	21.2%	98.5%
CritPt	1.1%	18.3%
LMArena Hard Prompts	1416	1508
Epoch Capabilities Index	141.29	156.71
SimpleBench	40.8%	—
Kagi LLM Benchmark	69.4%	—
NYT Connections (extended)	—	97.4%
Chess Puzzles	—	61%
LiveBench Reasoning	83.2%	—
Mystery Game Puzzles	—	47%
DTBench	—	95.7%
LiveBench Data Analysis	69.8%	—
LMCA	—	52.9%
Surface Evolver Bench	—	76.9%
ForecastBench	60	—
LiveBench	71.6%	—

Math Gemini 3.8 Flash leads

DeepSeek-R1: 43.8 (#79), Gemini 3.8 Flash: 65.3 (#28)

Math benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
OTIS Mock AIME 2024-2025	66.4%	98.9%
LMArena Math	1400	1528
FrontierMath (Tiers 1-3)	—	68.4%
FrontierMath Tier 4	—	22%
ProofBench	—	48%
Omni-MATH	42.4%	—
LiveBench Math	80.7%	—
MATH Level 5	96.6%	—

Knowledge Gemini 3.8 Flash leads

DeepSeek-R1: 44.5 (#87), Gemini 3.8 Flash: 74.8 (#2)

Knowledge benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
GPQA Diamond	76.3%	95.4%
LMArena Expert	1394	1524
Humanity's Last Exam	—	44.5%
SimpleQA Verified	—	69.7%
MMLU-Pro	79.3%	—
Confabulations	12.7%	—
Vectara Hallucination Rate	11.3%	—
GPQA (HELM)	66.6%	—

Multimodal Not comparable

DeepSeek-R1: —, Gemini 3.8 Flash: 40.7 (#45)

Multimodal benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
LMArena Vision	—	1314
Blueprint-Bench 2	—	38.6%
Furniture Assembly	—	31.7%

Multilingual Gemini 3.8 Flash leads

DeepSeek-R1: 52.4 (#85), Gemini 3.8 Flash: 58.0 (#5)

Multilingual benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
LMArena Non-English	1412	1491
LMArena Chinese	1442	1554
LMArena French	1417	1498
LMArena German	1404	1493
LMArena Japanese	1391	1502
LMArena Korean	1360	1459
LMArena Russian	1423	1515
LMArena Spanish	1411	1485

Instruction Following Gemini 3.8 Flash leads

DeepSeek-R1: 72.0 (#143), Gemini 3.8 Flash: 78.0 (#13)

Instruction Following benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
LMArena Instruction Following	1382	1490
LiveBench Instruction Following	80.5%	—
IFEval	78.4%	—

Long Context Too close to call

DeepSeek-R1: 45.4 (#36), Gemini 3.8 Flash: 46.3 (#24)

Long Context benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
LMArena Longer Query	1391	1508
Fiction.LiveBench	75%	—

Writing & Preference Gemini 3.8 Flash leads

DeepSeek-R1: 61.4 (#88), Gemini 3.8 Flash: 72.2 (#15)

Writing & Preference benchmarks
Benchmark	DeepSeek-R1	Gemini 3.8 Flash
LMArena Text	1428	1499
LMArena Creative Writing	1405	1492
EQ-Bench Creative Writing	1500	1748
LMArena Multi-Turn	1405	1501
Short-Story Creative Writing	83%	—
WildBench	82.8%	—
LiveBench Language	48.5%	—

Frequently asked questions

Is DeepSeek-R1 better than Gemini 3.8 Flash?

Which is cheaper, DeepSeek-R1 or Gemini 3.8 Flash?

DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Gemini 3.8 Flash lists at $0.75 and $3.75.

Is DeepSeek-R1 or Gemini 3.8 Flash better for coding?

Gemini 3.8 Flash scores higher on coding benchmarks: 59.2 versus 46.3 in the Noometry coding category.

Which has the bigger context window?

Gemini 3.8 Flash does, with 1.05M tokens against 164K.

How many benchmarks do DeepSeek-R1 and Gemini 3.8 Flash share?

27 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Gemini 3.8 Flash has 50.