Enter opens the highlighted result. Esc closes.

R1 0528 vs Gemini 3.5 Flash

Gemini 3.5 Flash leads R1 0528 on the Artificial Analysis Intelligence Index, 33.6 to 13.1, and R1 0528 costs 4.1x less per output token ($2.18 vs $9.00 per million). Updated October 22, 2026; 49 benchmarks have a result for both.

R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
0
Gemini 3.5 FlashGoogle
Coding
39.8
Overall
63.8
Output $/M
$9.00
49
vs boards won of 49 shared

R1 0528 or Gemini 3.5 Flash: which to pick

Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding.

Pick R1 0528 for output tokens 4.1x cheaper ($2.18 vs $9.00 per million).

Shared results
49
R1 0528 only
11
Gemini 3.5 Flash only
63
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
R1 0528 not benchmarked, Gemini 3.5 Flash 39.8 from 4 benchmarks.
Widest category
Agentic work, 59.1 points apart on average over 1 shared benchmark.
Widest single gap
ARC-AGI: R1 0528 21.2% against Gemini 3.5 Flash 92.5%, 71.3 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against Gemini 3.5 Flash $9.00 per million output tokens, 4.1x apart.
Context window
R1 0528 takes 164K tokens, Gemini 3.5 Flash 1.05M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryR1 0528BarsGemini 3.5 FlashTies
Coding05
Intelligence01
Agentic work01
Reasoning09
Math03
Knowledge04
Web design07
General019
All shared boards049
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1499Only Gemini 3.5 Flash measured
LiveCodeBench (Vals AI)Not measured87.6%Only Gemini 3.5 Flash measured
SWE-bench Verified (Vals AI)Not measured78.8%Only Gemini 3.5 Flash measured
Terminal-Bench 4 (Vals AI)Not measured6.1%Only Gemini 3.5 Flash measured
Vibe Code Bench (Vals AI)Not measured48.7%Only Gemini 3.5 Flash measured
Code migration (Vals AI)Not measured26.8%Only Gemini 3.5 Flash measured
ProgramBench (Vals AI)Not measured0.0%Only Gemini 3.5 Flash measured
Terminal-Bench 2.1 (Vals AI)Not measured74.2%Only Gemini 3.5 Flash measured
SkillsBench (Vals AI)Not measured52.7%Only Gemini 3.5 Flash measured
LiveCodeBench (Artificial Analysis run)77.0%Not measuredOnly R1 0528 measured
SciCodeNot measured53.9%Only Gemini 3.5 Flash measured
Terminal-Bench Hard (Artificial Analysis run)15.9%46.2%Gemini 3.5 Flash
WeirdML41.6%62.6%Gemini 3.5 Flash
ALE-Bench804.1911.0Gemini 3.5 Flash
LMArena Text: coding14271493Gemini 3.5 Flash
LMArena Text: software and IT14351494Gemini 3.5 Flash
LMArena WebDev: ReactNot measured1495Only Gemini 3.5 Flash measured
LMArena WebDev: HTMLNot measured1522Only Gemini 3.5 Flash measured
LMArena WebDev: from an imageNot measured1504Only Gemini 3.5 Flash measured
SciCodeNot measured12.3%Only Gemini 3.5 Flash measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
AA Intelligence Index13.133.6Gemini 3.5 Flash
Epoch Capabilities IndexNot measured154.9Only Gemini 3.5 Flash measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
Design Arena: agents building web appsNot measured1202Only Gemini 3.5 Flash measured
Design Arena: agents building full-stack appsNot measured1197Only Gemini 3.5 Flash measured
Design Arena: agents building mobile appsNot measured1174Only Gemini 3.5 Flash measured
Design Arena: agents building Android appsNot measured1185Only Gemini 3.5 Flash measured
Design Arena: agents building Godot gamesNot measured1098Only Gemini 3.5 Flash measured
Design Arena: agents building gamesNot measured1180Only Gemini 3.5 Flash measured
Design Arena: HTML slidesNot measured1093Only Gemini 3.5 Flash measured
Design Arena: PowerPoint slidesNot measured1154Only Gemini 3.5 Flash measured
Finance Agent (Vals AI)Not measured57.9%Only Gemini 3.5 Flash measured
Tax Agent Bench (Vals AI)Not measured21.6%Only Gemini 3.5 Flash measured
Legal Research Bench (Vals AI)Not measured30.8%Only Gemini 3.5 Flash measured
Excel Modeling Benchmark (Vals AI)Not measured63.5%Only Gemini 3.5 Flash measured
Terminal-Bench-Science (Vals AI)Not measured5.7%Only Gemini 3.5 Flash measured
τ²-Bench Telecom36.5%95.6%Gemini 3.5 Flash
APEX-AgentsNot measured27.5%Only Gemini 3.5 Flash measured
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
Vending-Bench 2Not measured$5,396Only Gemini 3.5 Flash measured
BrowseComp-Plus16.4%Not measuredOnly R1 0528 measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
GPQA DiamondNot measured92.7%Only Gemini 3.5 Flash measured
MMMU Pro (Vals AI)Not measured88.3%Only Gemini 3.5 Flash measured
GPQA Diamond (Artificial Analysis run)81.3%92.2%Gemini 3.5 Flash
Humanity's Last Exam (Artificial Analysis run)15.8%42.7%Gemini 3.5 Flash
GPQA Diamond (Epoch AI run)76.3%92.8%Gemini 3.5 Flash
ARC-AGI21.2%92.5%Gemini 3.5 Flash
ARC-AGI-21.1%72.1%Gemini 3.5 Flash
SimpleBench40.8%76.7%Gemini 3.5 Flash
Chess puzzlesNot measured45.0%Only Gemini 3.5 Flash measured
Mystery game puzzlesNot measured32.0%Only Gemini 3.5 Flash measured
EBR-benchNot measured4.8%Only Gemini 3.5 Flash measured
LMArena Text: hard prompts14151488Gemini 3.5 Flash
LMArena Text: expert13941495Gemini 3.5 Flash
LMArena Text: hard prompts in English14221483Gemini 3.5 Flash
LMArena Vision: diagramsNot measured1323Only Gemini 3.5 Flash measured
LMArena Vision: homeworkNot measured1330Only Gemini 3.5 Flash measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
AA Math Index76.0Not measuredOnly R1 0528 measured
AIME 2025 (Artificial Analysis run)76.0%Not measuredOnly R1 0528 measured
OTIS Mock AIME66.4%95.6%Gemini 3.5 Flash
FrontierMath, tiers 1 to 3Not measured62.8%Only Gemini 3.5 Flash measured
FrontierMath, tier 4Not measured26.8%Only Gemini 3.5 Flash measured
ProofBenchNot measured31.0%Only Gemini 3.5 Flash measured
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001504Gemini 3.5 Flash
LMArena Text: mathematical work14151495Gemini 3.5 Flash
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
MMLU ProNot measured89.5%Only Gemini 3.5 Flash measured
LegalBench (Vals AI)Not measured83.6%Only Gemini 3.5 Flash measured
CorpFin (Vals AI)Not measured64.7%Only Gemini 3.5 Flash measured
TaxEval (Vals AI)Not measured74.4%Only Gemini 3.5 Flash measured
MortgageTax (Vals AI)Not measured68.1%Only Gemini 3.5 Flash measured
MedCode (Vals AI)Not measured55.8%Only Gemini 3.5 Flash measured
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
SimpleQA VerifiedNot measured66.2%Only Gemini 3.5 Flash measured
LMArena Text: science14301495Gemini 3.5 Flash
LMArena Text: medicine and healthcare14451483Gemini 3.5 Flash
LMArena Text: legal and government14191488Gemini 3.5 Flash
LMArena Text: business and finance14021467Gemini 3.5 Flash
FACTS Benchmark SuiteNot measured63.1%Only Gemini 3.5 Flash measured
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
Design Arena: websites11491267Gemini 3.5 Flash
Design Arena: UI components11001269Gemini 3.5 Flash
Design Arena: game dev10971263Gemini 3.5 Flash
Design Arena: data viz11821236Gemini 3.5 Flash
Design Arena: 3D11101243Gemini 3.5 Flash
Design Arena: all code categories11381266Gemini 3.5 Flash
Design Arena: SVG10381253Gemini 3.5 Flash
Design Arena: ASCII artNot measured1254Only Gemini 3.5 Flash measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
Public Benefits Bench (Vals AI)Not measured59.5%Only Gemini 3.5 Flash measured
SAGE (Vals AI)Not measured49.9%Only Gemini 3.5 Flash measured
MedScribe (Vals AI)Not measured76.6%Only Gemini 3.5 Flash measured
Vals Multimodal IndexNot measured62.9%Only Gemini 3.5 Flash measured
IFBench39.6%76.3%Gemini 3.5 Flash
Long context reasoning (AA-LCR)55.7%74.3%Gemini 3.5 Flash
DTBenchNot measured94.7%Only Gemini 3.5 Flash measured
LMCANot measured47.1%Only Gemini 3.5 Flash measured
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
Surface Evolver BenchNot measured58.1%Only Gemini 3.5 Flash measured
LMArena Text14281482Gemini 3.5 Flash
LMArena Text: instruction following13821467Gemini 3.5 Flash
LMArena Text: creative writing14051470Gemini 3.5 Flash
LMArena VisionNot measured1308Only Gemini 3.5 Flash measured
LMArena Text: English14371481Gemini 3.5 Flash
LMArena Text: non-English14121475Gemini 3.5 Flash
LMArena Text: Chinese14421527Gemini 3.5 Flash
LMArena Text: German14041494Gemini 3.5 Flash
LMArena Text: Japanese13911486Gemini 3.5 Flash
LMArena Text: Korean13601448Gemini 3.5 Flash
LMArena Text: French14171490Gemini 3.5 Flash
LMArena Text: Spanish14111480Gemini 3.5 Flash
LMArena Text: Russian14231493Gemini 3.5 Flash
LMArena Text: Polish14281516Gemini 3.5 Flash
LMArena Text: multi-turn14051481Gemini 3.5 Flash
LMArena Text: longer queries13911483Gemini 3.5 Flash
LMArena Text: writing and language14021478Gemini 3.5 Flash
LMArena Text: entertainment and media14001459Gemini 3.5 Flash
LMArena Vision: EnglishNot measured1305Only Gemini 3.5 Flash measured
LMArena Vision: ChineseNot measured1377Only Gemini 3.5 Flash measured
LMArena Vision: reading textNot measured1317Only Gemini 3.5 Flash measured
LMArena Vision: humorNot measured1321Only Gemini 3.5 Flash measured
LMArena Vision: creative writingNot measured1301Only Gemini 3.5 Flash measured
LMArena DocumentNot measured1463Only Gemini 3.5 Flash measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for R1 0528 and Gemini 3.5 Flash
BenchmarkR1 0528Gemini 3.5 FlashLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

R1 0528$0.0016Fits in one request
Gemini 3.5 Flash$0.0060Fits in one request

R1 0528 costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
Gemini 3.5 Flash$0.102Fits in one request

R1 0528 costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
Gemini 3.5 Flash$0.390Fits in one request

R1 0528 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of R1 0528 and Gemini 3.5 Flash
SpecificationDeepSeek R1 0528Google Gemini 3.5 Flash
MakerDeepSeekGoogle
WeightsOpen weightsNo public weights listed
ReleasedMay 28, 2025May 19, 2026
Context window164K1.05M
Input $/Mtok$0.50$1.50
Output $/Mtok$2.18$9.00
Coding indexNot benchmarked39.8
Independent measurements behind it04
Cost per solved taskNot computable$1.21
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than Gemini 3.5 Flash for coding?

Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; R1 0528 has none, so the two cannot be ranked on coding. Pick R1 0528 for output tokens 4.1x cheaper ($2.18 vs $9.00 per million).

Which is cheaper, R1 0528 or Gemini 3.5 Flash?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; Gemini 3.5 Flash costs $1.50 and $9.00. Cost per solved task is known for Gemini 3.5 Flash only.

Which has the bigger context window, R1 0528 or Gemini 3.5 Flash?

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

How many benchmarks is the R1 0528 vs Gemini 3.5 Flash comparison based on?

49 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and Gemini 3.5 Flash's on 4. Where only one model has a result, the page says so instead of naming a winner.

Compare next