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DeepSeek V3.2 vs Gemini 4 Argon

Gemini 4 Argon leads DeepSeek V3.2 on coding, 81.0 to 30.0 on the Vibe Coding Index, and DeepSeek V3.2 costs 11.4x less per output token ($0.88 vs $10.00 per million). Updated October 22, 2026; 44 benchmarks have a result for both.

DeepSeek V3.2DeepSeek
Coding
30.0
Overall
37.9
Output $/M
$0.88
0
Gemini 4 ArgonGoogle
Coding
81.0
Overall
84.0
Output $/M
$10.00
44
vs boards won of 44 shared

DeepSeek V3.2 or Gemini 4 Argon: which to pick

Pick Gemini 4 Argon for coding: it scores 81.0 on the Vibe Coding Index against 30.0 for DeepSeek V3.2.

Pick DeepSeek V3.2 for output tokens 11.4x cheaper ($0.88 vs $10.00 per million).

Shared results
44
DeepSeek V3.2 only
31
Gemini 4 Argon only
50
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
DeepSeek V3.2 30.0 from 3 benchmarks, Gemini 4 Argon 81.0 from 5 benchmarks.
Widest category
Agentic work, 70.2 points apart on average over 2 shared benchmarks.
Widest single gap
ARC-AGI-2: DeepSeek V3.2 4.0% against Gemini 4 Argon 91.3%, 87.2 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 $0.88 against Gemini 4 Argon $10.00 per million output tokens, 11.4x apart.
Context window
DeepSeek V3.2 takes 164K tokens, Gemini 4 Argon 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
CategoryDeepSeek V3.2BarsGemini 4 ArgonTies
Coding06
Intelligence02
Agentic work02
Reasoning06
Math02
Knowledge05
Web design06
General015
All shared boards044
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
Coding benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
SWE-bench Verified70.0%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Multilingual59.0%Not measuredOnly DeepSeek V3.2 measured
LiveBench codingNot measured89.7%Only Gemini 4 Argon measured
LMArena WebDev13621678Gemini 4 Argon
AA Coding Index44.2Not measuredOnly DeepSeek V3.2 measured
LiveCodeBench (Vals AI)80.7%Not measuredOnly DeepSeek V3.2 measured
SWE-bench Verified (Vals AI)67.6%Not measuredOnly DeepSeek V3.2 measured
Terminal-Bench 4 (Vals AI)Not measured57.6%Only Gemini 4 Argon measured
Vibe Code Bench (Vals AI)5.1%91.9%Gemini 4 Argon
Code migration (Vals AI)Not measured68.2%Only Gemini 4 Argon measured
ProgramBench (Vals AI)Not measured2.5%Only Gemini 4 Argon measured
IOI (Vals AI)Not measured100.0%Only Gemini 4 Argon measured
Terminal-Bench 2.1 (Vals AI)Not measured57.7%Only Gemini 4 Argon measured
SWE-bench Multimodal (Vals AI)Not measured56.0%Only Gemini 4 Argon measured
Vibe Code Bench 1-100 (Vals AI)Not measured21.2%Only Gemini 4 Argon measured
CyberBench (Vals AI)Not measured77.9%Only Gemini 4 Argon measured
LiveCodeBench (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
SciCodeNot measured61.8%Only Gemini 4 Argon measured
Terminal-Bench Hard (Artificial Analysis run)35.6%Not measuredOnly DeepSeek V3.2 measured
Terminal-Bench39.6%Not measuredOnly DeepSeek V3.2 measured
FrontierCodeNot measured47.5%Only Gemini 4 Argon measured
FrontierSWENot measured55.0%Only Gemini 4 Argon measured
MirrorCodeNot measured58.9%Only Gemini 4 Argon measured
ALE-BenchNot measured2100.1Only Gemini 4 Argon measured
LMArena Text: coding14531546Gemini 4 Argon
LMArena Text: software and IT14491556Gemini 4 Argon
LMArena WebDev: React13501692Gemini 4 Argon
LMArena WebDev: HTML13711643Gemini 4 Argon
SciCodeNot measured12.3%Only Gemini 4 Argon measured
Neither model has a result on the other 10 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
AA Intelligence Index21.552.6Gemini 4 Argon
Epoch Capabilities Index146.1166.4Gemini 4 Argon
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
Design Arena: spreadsheetsNot measured1157Only Gemini 4 Argon measured
LiveBench researchNot measured83.1%Only Gemini 4 Argon measured
LiveBench browserNot measured92.0%Only Gemini 4 Argon measured
LiveBench long agenticNot measured69.9%Only Gemini 4 Argon measured
SREBench (Vals AI)Not measured44.3%Only Gemini 4 Argon measured
Finance Agent (Vals AI)Not measured65.4%Only Gemini 4 Argon measured
Tax Agent Bench (Vals AI)Not measured44.6%Only Gemini 4 Argon measured
Legal Research Bench (Vals AI)Not measured54.8%Only Gemini 4 Argon measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured27.1%Only Gemini 4 Argon measured
Excel Modeling Benchmark (Vals AI)Not measured75.2%Only Gemini 4 Argon measured
BioMysteryBench (Vals AI)Not measured76.3%Only Gemini 4 Argon measured
Terminal-Bench-Science (Vals AI)Not measured44.3%Only Gemini 4 Argon measured
Vals Science IndexNot measured55.4%Only Gemini 4 Argon measured
Time Horizon Index (Vals AI)Not measured52.5%Only Gemini 4 Argon measured
CUA-bench (Vals AI)Not measured4.8%Only Gemini 4 Argon measured
Robo-bench (Vals AI)Not measured0.8%Only Gemini 4 Argon measured
τ²-Bench Telecom90.6%Not measuredOnly DeepSeek V3.2 measured
APEX-Agents21.3%82.4%Gemini 4 Argon
Vending-Bench 2$1,034$13,718Gemini 4 Argon
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
GPQA Diamond80.3%Not measuredOnly DeepSeek V3.2 measured
LiveBench reasoningNot measured95.1%Only Gemini 4 Argon measured
MysteryMechanism (Vals AI)Not measured45.5%Only Gemini 4 Argon measured
GPQA Diamond (Artificial Analysis run)84.0%Not measuredOnly DeepSeek V3.2 measured
Humanity's Last Exam (Artificial Analysis run)24.6%57.1%Gemini 4 Argon
GPQA Diamond (Epoch AI run)Not measured96.4%Only Gemini 4 Argon measured
ARC-AGI57.0%98.5%Gemini 4 Argon
ARC-AGI-24.0%91.3%Gemini 4 Argon
Chess puzzlesNot measured59.0%Only Gemini 4 Argon measured
Mystery game puzzlesNot measured64.0%Only Gemini 4 Argon measured
EBR-benchNot measured64.8%Only Gemini 4 Argon measured
LMArena Text: hard prompts14341546Gemini 4 Argon
LMArena Text: expert14361550Gemini 4 Argon
LMArena Text: hard prompts in English14461548Gemini 4 Argon
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
AIME84.6%Not measuredOnly DeepSeek V3.2 measured
MGSM (Vals AI)86.0%Not measuredOnly DeepSeek V3.2 measured
AA Math Index92.0Not measuredOnly DeepSeek V3.2 measured
AIME 2025 (Artificial Analysis run)92.0%Not measuredOnly DeepSeek V3.2 measured
OTIS Mock AIMENot measured100.0%Only Gemini 4 Argon measured
FrontierMath, tiers 1 to 3Not measured86.0%Only Gemini 4 Argon measured
FrontierMath, tier 4Not measured78.0%Only Gemini 4 Argon measured
ProofBenchNot measured99.0%Only Gemini 4 Argon measured
LMArena Text: math14351536Gemini 4 Argon
LMArena Text: mathematical work14401557Gemini 4 Argon
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
MMLU Pro84.9%Not measuredOnly DeepSeek V3.2 measured
LegalBench (Vals AI)76.1%88.3%Gemini 4 Argon
CaseLaw (Vals AI)55.4%Not measuredOnly DeepSeek V3.2 measured
CorpFin (Vals AI)51.0%Not measuredOnly DeepSeek V3.2 measured
TaxEval (Vals AI)68.2%Not measuredOnly DeepSeek V3.2 measured
MedQA (Vals AI)93.9%Not measuredOnly DeepSeek V3.2 measured
MedCode (Vals AI)Not measured58.8%Only Gemini 4 Argon measured
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly DeepSeek V3.2 measured
SimpleQA VerifiedNot measured76.0%Only Gemini 4 Argon measured
LMArena Text: science14461548Gemini 4 Argon
LMArena Text: medicine and healthcare14401555Gemini 4 Argon
LMArena Text: legal and government14251548Gemini 4 Argon
LMArena Text: business and finance14101525Gemini 4 Argon
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
Design Arena: websites11751315Gemini 4 Argon
Design Arena: UI components11461333Gemini 4 Argon
Design Arena: game dev11311377Gemini 4 Argon
Design Arena: data viz11581332Gemini 4 Argon
Design Arena: 3D11321388Gemini 4 Argon
Design Arena: all code categories11631329Gemini 4 Argon
Design Arena: SVG1032Not measuredOnly DeepSeek V3.2 measured
Design Arena: ASCII art1083Not measuredOnly DeepSeek V3.2 measured
LiveBench designNot measured73.7%Only Gemini 4 Argon measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
General benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
Vals IndexNot measured69.2%Only Gemini 4 Argon measured
LiveBench data analysisNot measured85.2%Only Gemini 4 Argon measured
Public Benefits Bench (Vals AI)Not measured69.8%Only Gemini 4 Argon measured
SAGE (Vals AI)Not measured53.6%Only Gemini 4 Argon measured
MedScribe (Vals AI)Not measured87.4%Only Gemini 4 Argon measured
IFBench60.7%Not measuredOnly DeepSeek V3.2 measured
Long context reasoning (AA-LCR)73.3%79.7%Gemini 4 Argon
DTBench85.6%97.6%Gemini 4 Argon
LMCA28.8%63.7%Gemini 4 Argon
CL-bench12.4%Not measuredOnly DeepSeek V3.2 measured
Furniture assemblyNot measured72.5%Only Gemini 4 Argon measured
CL-bench Life7.4%Not measuredOnly DeepSeek V3.2 measured
LMArena Text14251532Gemini 4 Argon
LMArena Text: instruction following14131534Gemini 4 Argon
LMArena Text: creative writing14001527Gemini 4 Argon
LMArena Text: English14391538Gemini 4 Argon
LMArena Text: non-English14091522Gemini 4 Argon
LMArena Text: Chinese14551611Gemini 4 Argon
LMArena Text: German1413Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Japanese1374Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Korean1370Not measuredOnly DeepSeek V3.2 measured
LMArena Text: French1429Not measuredOnly DeepSeek V3.2 measured
LMArena Text: Spanish14241503Gemini 4 Argon
LMArena Text: Russian14241534Gemini 4 Argon
LMArena Text: Polish1419Not measuredOnly DeepSeek V3.2 measured
LMArena Text: multi-turn14271556Gemini 4 Argon
LMArena Text: longer queries14281547Gemini 4 Argon
LMArena Text: writing and language14071529Gemini 4 Argon
LMArena Text: entertainment and media13951527Gemini 4 Argon
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 and Gemini 4 Argon
BenchmarkDeepSeek V3.2Gemini 4 ArgonLeader
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 V3.2$0.0007Fits in one request
Gemini 4 Argon$0.0070Fits in one request

DeepSeek V3.2 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2$0.017Fits in one request
Gemini 4 Argon$0.130Fits in one request

DeepSeek V3.2 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2$0.067Exceeds the context window
Gemini 4 Argon$0.500Fits in one request

DeepSeek V3.2 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 V3.2 and Gemini 4 Argon
SpecificationDeepSeek V3.2Google Gemini 4 Argon
MakerDeepSeekGoogle
WeightsOpen weightsNo public weights listed
ReleasedDecember 1, 2025October 13, 2026
Context window164K1.05M
Input $/Mtok$0.29$2.00
Output $/Mtok$0.88$10.00
Coding index30.081.0
Independent measurements behind it35
Cost per solved task$0.99Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 better than Gemini 4 Argon for coding?

Pick Gemini 4 Argon for coding: it scores 81.0 on the Vibe Coding Index against 30.0 for DeepSeek V3.2. Pick DeepSeek V3.2 for output tokens 11.4x cheaper ($0.88 vs $10.00 per million).

Which is cheaper, DeepSeek V3.2 or Gemini 4 Argon?

DeepSeek V3.2 costs $0.29 per million input tokens and $0.88 per million output tokens; Gemini 4 Argon costs $2.00 and $10.00. Cost per solved task is known for DeepSeek V3.2 only.

Which has the bigger context window, DeepSeek V3.2 or Gemini 4 Argon?

Gemini 4 Argon, with 1.05M tokens against 164K.

How many benchmarks is the DeepSeek V3.2 vs Gemini 4 Argon comparison based on?

44 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2's coding index rests on 3 independent benchmarks and Gemini 4 Argon's on 5. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/deepseek-v3-2-vs-gemini-4-argon">LLMBenchmark.ai, DeepSeek V3.2 vs Gemini 4 Argon</a></p>