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DeepSeek V3.1 Terminus vs Qwen3.5-35B-A3B

Qwen3.5-35B-A3B leads DeepSeek V3.1 Terminus on the Artificial Analysis Intelligence Index, 19.3 to 14.8, and DeepSeek V3.1 Terminus costs 1.3x less per output token ($1.0142 vs $1.30 per million). Updated October 22, 2026; 30 benchmarks have a result for both.

Replace DeepSeek V3.1 Terminus Replace Qwen3.5-35B-A3B
DeepSeek V3.1 TerminusDeepSeek
Coding
No data
Overall
No data
Output $/M
$1.0142
22
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
8
vs boards won of 30 shared

DeepSeek V3.1 Terminus or Qwen3.5-35B-A3B: which to pick

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

Pick DeepSeek V3.1 Terminus for output tokens 1.3x cheaper ($1.0142 vs $1.30 per million) and work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.

Model ADeepSeek V3.1 TerminusDeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
30
DeepSeek V3.1 Terminus only
15
Qwen3.5-35B-A3B only
16
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
DeepSeek V3.1 Terminus not benchmarked, Qwen3.5-35B-A3B not benchmarked.
Widest category
Agentic work, 52.0 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: DeepSeek V3.1 Terminus 37.1% against Qwen3.5-35B-A3B 89.2%, 52.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.1 Terminus $1.0142 against Qwen3.5-35B-A3B $1.30 per million output tokens, 1.3x apart.
Context window
DeepSeek V3.1 Terminus 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
CategoryDeepSeek V3.1 TerminusBarsQwen3.5-35B-A3BTies
Coding40
Intelligence01
Agentic work01
Reasoning22
Math01
Knowledge40
General123
All shared boards228
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
AA Coding Index43.5Not measuredOnly DeepSeek V3.1 Terminus measured
LiveCodeBench (Artificial Analysis run)79.8%Not measuredOnly DeepSeek V3.1 Terminus measured
SciCode38.0%Not measuredOnly DeepSeek V3.1 Terminus measured
Terminal-Bench Hard (Artificial Analysis run)31.8%26.5%DeepSeek V3.1 Terminus
ALE-Bench745.2221.8DeepSeek V3.1 Terminus
LMArena Text: coding14251410DeepSeek V3.1 Terminus
LMArena Text: software and IT14261415DeepSeek V3.1 Terminus
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 DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
AA Intelligence Index14.819.3Qwen3.5-35B-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 DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
AA Agentic Index6.8Not measuredOnly DeepSeek V3.1 Terminus measured
τ²-Bench Telecom37.1%89.2%Qwen3.5-35B-A3B
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index22
Reasoning benchmarks for DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
GPQA Diamond (Artificial Analysis run)79.2%84.5%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)16.4%21.0%Qwen3.5-35B-A3B
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts14261400DeepSeek V3.1 Terminus
LMArena Text: expertNot measured1408Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts in English14321411DeepSeek V3.1 Terminus
Kagi LLM Benchmark57.4%Not measuredOnly DeepSeek V3.1 Terminus measured
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
AA Math Index89.7Not measuredOnly DeepSeek V3.1 Terminus measured
AIME 2025 (Artificial Analysis run)89.7%Not measuredOnly DeepSeek V3.1 Terminus measured
OTIS Mock AIMENot measured70.0%Only Qwen3.5-35B-A3B measured
LMArena Text: math14021404Qwen3.5-35B-A3B
LMArena Text: mathematical workNot measured1410Only Qwen3.5-35B-A3B measured
MathArenaNot measured14.7%Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
MMLU Pro (Artificial Analysis run)85.1%Not measuredOnly DeepSeek V3.1 Terminus measured
LMArena Text: science14511413DeepSeek V3.1 Terminus
LMArena Text: medicine and healthcare14681421DeepSeek V3.1 Terminus
LMArena Text: legal and government14571399DeepSeek V3.1 Terminus
LMArena Text: business and finance14141394DeepSeek V3.1 Terminus
Neither model has a result on the other 15 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
Design Arena: websites1187Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: UI components1180Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: game dev1131Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: data viz1168Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: 3D1141Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: all code categories1175Not measuredOnly DeepSeek V3.1 Terminus measured
Design Arena: SVG1065Not measuredOnly DeepSeek V3.1 Terminus measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index123
General benchmarks for DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-A3BLeader
IFBench57.0%72.5%Qwen3.5-35B-A3B
Long context reasoning (AA-LCR)69.3%72.0%Qwen3.5-35B-A3B
DTBench81.3%80.0%DeepSeek V3.1 Terminus
LMCA28.6%29.5%Qwen3.5-35B-A3B
LMArena Text14191395DeepSeek V3.1 Terminus
LMArena Text: instruction following14041379DeepSeek V3.1 Terminus
LMArena Text: creative writing14031347DeepSeek V3.1 Terminus
LMArena Text: English14291407DeepSeek V3.1 Terminus
LMArena Text: non-English14081378DeepSeek V3.1 Terminus
LMArena Text: ChineseNot measured1457Only Qwen3.5-35B-A3B measured
LMArena Text: GermanNot measured1367Only Qwen3.5-35B-A3B measured
LMArena Text: JapaneseNot measured1326Only Qwen3.5-35B-A3B measured
LMArena Text: KoreanNot measured1355Only Qwen3.5-35B-A3B measured
LMArena Text: FrenchNot measured1412Only Qwen3.5-35B-A3B measured
LMArena Text: SpanishNot measured1390Only Qwen3.5-35B-A3B measured
LMArena Text: Russian14351376DeepSeek V3.1 Terminus
LMArena Text: Polish14271385DeepSeek V3.1 Terminus
LMArena Text: multi-turn14111390DeepSeek V3.1 Terminus
LMArena Text: longer queries14221389DeepSeek V3.1 Terminus
LMArena Text: writing and language14091365DeepSeek V3.1 Terminus
LMArena Text: entertainment and media13911347DeepSeek V3.1 Terminus
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
BenchmarkDeepSeek V3.1 TerminusQwen3.5-35B-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

DeepSeek V3.1 Terminus$0.0008Fits 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

DeepSeek V3.1 Terminus$0.018Fits 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

DeepSeek V3.1 Terminus$0.071Exceeds 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 DeepSeek V3.1 Terminus and Qwen3.5-35B-A3B
SpecificationDeepSeek V3.1 TerminusQwen3.5-35B-A3B
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedSeptember 22, 2025February 25, 2026
Context window164K262K
Input $/Mtok$0.3063$0.1625
Output $/Mtok$1.0142$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.1 Terminus better than Qwen3.5-35B-A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.1 Terminus for output tokens 1.3x cheaper ($1.0142 vs $1.30 per million) and work measured by AA Intelligence Index or τ²-Bench Telecom, where it leads.

Which is cheaper, DeepSeek V3.1 Terminus or Qwen3.5-35B-A3B?

DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 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, DeepSeek V3.1 Terminus or Qwen3.5-35B-A3B?

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

How many benchmarks is the DeepSeek V3.1 Terminus vs Qwen3.5-35B-A3B comparison based on?

30 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.1 Terminus'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.

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