Enter opens the highlighted result. Esc closes.

R1 0528 vs Qwen3.5-35B-A3B

Qwen3.5-35B-A3B leads R1 0528 on the Artificial Analysis Intelligence Index, 19.3 to 13.1, and Qwen3.5-35B-A3B costs 1.7x less per output token ($1.30 vs $2.18 per million). Updated October 22, 2026; 39 benchmarks have a result for both.

Replace R1 0528 Replace Qwen3.5-35B-A3B
R1 0528DeepSeek
Coding
No data
Overall
46.8
Output $/M
$2.18
26
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
13
vs boards won of 39 shared

R1 0528 or Qwen3.5-35B-A3B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick R1 0528 for work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Model AR1 0528DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
39
R1 0528 only
24
Qwen3.5-35B-A3B only
7
Like-for-like categories
7 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, Qwen3.5-35B-A3B not benchmarked.
Widest category
Agentic work, 52.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: R1 0528 36.5% against Qwen3.5-35B-A3B 89.2%, 52.6 points apart on a 0 to 100 scale.
Output price
R1 0528 $2.18 against Qwen3.5-35B-A3B $1.30 per million output tokens, 1.7x apart.
Context window
R1 0528 takes 164K tokens, Qwen3.5-35B-A3B 262K.

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 0528BarsQwen3.5-35B-A3BTies
Coding31
Intelligence01
Agentic work01
Reasoning24
Math13
Knowledge40
General163
All shared boards2613
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
Coding benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
Aider polyglot71.4%Not measuredOnly R1 0528 measured
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
LiveCodeBench (Artificial Analysis run)77.0%Not measuredOnly R1 0528 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%26.5%Qwen3.5-35B-A3B
WeirdML41.6%Not measuredOnly R1 0528 measured
ALE-Bench804.1221.8R1 0528
LMArena Text: coding14271410R1 0528
LMArena Text: software and IT14351415R1 0528
LMArena WebDev: ReactNot measured1238Only Qwen3.5-35B-A3B measured
LMArena WebDev: HTMLNot measured1301Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 33 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
AA Intelligence Index13.119.3Qwen3.5-35B-A3B
Epoch Capabilities IndexNot measured142.5Only Qwen3.5-35B-A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
τ²-Bench Telecom36.5%89.2%Qwen3.5-35B-A3B
METR time horizons53.8%Not measuredOnly R1 0528 measured
DeepResearch Bench35.1%Not measuredOnly R1 0528 measured
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
BrowseComp-Plus16.4%Not measuredOnly R1 0528 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index24
Reasoning benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
GPQA Diamond (Artificial Analysis run)81.3%84.5%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)15.8%21.0%Qwen3.5-35B-A3B
GPQA Diamond (Epoch AI run)76.3%83.5%Qwen3.5-35B-A3B
ARC-AGI21.2%Not measuredOnly R1 0528 measured
ARC-AGI-21.1%Not measuredOnly R1 0528 measured
SimpleBench40.8%Not measuredOnly R1 0528 measured
LMArena Text: hard prompts14151400R1 0528
LMArena Text: expert13941408Qwen3.5-35B-A3B
LMArena Text: hard prompts in English14221411R1 0528
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index13
Math benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
AA Math Index76.0Not measuredOnly R1 0528 measured
AIME 2025 (Artificial Analysis run)76.0%Not measuredOnly R1 0528 measured
OTIS Mock AIME66.4%70.0%Qwen3.5-35B-A3B
MATH level 596.6%Not measuredOnly R1 0528 measured
LMArena Text: math14001404Qwen3.5-35B-A3B
LMArena Text: mathematical work14151410R1 0528
MathArena12.9%14.7%Qwen3.5-35B-A3B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
MMLU Pro (Artificial Analysis run)84.9%Not measuredOnly R1 0528 measured
LMArena Text: science14301413R1 0528
LMArena Text: medicine and healthcare14451421R1 0528
LMArena Text: legal and government14191399R1 0528
LMArena Text: business and finance14021394R1 0528
PRBench Finance32.7%Not measuredOnly R1 0528 measured
PRBench Legal36.6%Not measuredOnly R1 0528 measured
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
Design Arena: websites1149Not measuredOnly R1 0528 measured
Design Arena: UI components1100Not measuredOnly R1 0528 measured
Design Arena: game dev1097Not measuredOnly R1 0528 measured
Design Arena: data viz1182Not measuredOnly R1 0528 measured
Design Arena: 3D1110Not measuredOnly R1 0528 measured
Design Arena: all code categories1138Not measuredOnly R1 0528 measured
Design Arena: SVG1038Not measuredOnly R1 0528 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index163
General benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
IFBench39.6%72.5%Qwen3.5-35B-A3B
Long context reasoning (AA-LCR)55.7%72.0%Qwen3.5-35B-A3B
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
Fiction.LiveBench75.0%Not measuredOnly R1 0528 measured
Creative writing (Lech Mazur)81.9%Not measuredOnly R1 0528 measured
LMArena Text14281395R1 0528
LMArena Text: instruction following13821379R1 0528
LMArena Text: creative writing14051347R1 0528
LMArena Text: English14371407R1 0528
LMArena Text: non-English14121378R1 0528
LMArena Text: Chinese14421457Qwen3.5-35B-A3B
LMArena Text: German14041367R1 0528
LMArena Text: Japanese13911326R1 0528
LMArena Text: Korean13601355R1 0528
LMArena Text: French14171412R1 0528
LMArena Text: Spanish14111390R1 0528
LMArena Text: Russian14231376R1 0528
LMArena Text: Polish14281385R1 0528
LMArena Text: multi-turn14051390R1 0528
LMArena Text: longer queries13911389R1 0528
LMArena Text: writing and language14021365R1 0528
LMArena Text: entertainment and media14001347R1 0528
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for R1 0528 and Qwen3.5-35B-A3B
BenchmarkR1 0528Qwen3.5-35B-A3BLeader
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
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

R1 0528$0.032Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

R1 0528$0.122Exceeds the context window
Qwen3.5-35B-A3B$0.045Fits in one request

Qwen3.5-35B-A3B 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 Qwen3.5-35B-A3B
SpecificationDeepSeek R1 0528Qwen3.5-35B-A3B
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedMay 28, 2025February 25, 2026
Context window164K262K
Input $/Mtok$0.50$0.1625
Output $/Mtok$2.18$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is R1 0528 better than Qwen3.5-35B-A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick R1 0528 for work measured by Terminal-Bench Hard (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, R1 0528 or Qwen3.5-35B-A3B?

R1 0528 costs $0.50 per million input tokens and $2.18 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for neither of them.

Which has the bigger context window, R1 0528 or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B, with 262K tokens against 164K.

How many benchmarks is the R1 0528 vs Qwen3.5-35B-A3B comparison based on?

39 benchmarks have a result for both models as of October 22, 2026. R1 0528's coding index rests on 0 independent benchmarks and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next