DeepSeek V3 0324 vs Gemini 4 Argon
Gemini 4 Argon leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 52.6 to 9.7, and DeepSeek V3 0324 costs 9.3x less per output token ($1.07 vs $10.00 per million). Updated October 21, 2026; 9 benchmarks have a result for both.
DeepSeek V3 0324 or Gemini 4 Argon: which to pick
Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; DeepSeek V3 0324 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3 0324 for output tokens 9.3x cheaper ($1.07 vs $10.00 per million).
- Shared results
- 9
- DeepSeek V3 0324 only
- 26
- Gemini 4 Argon only
- 84
- Like-for-like categories
- 6 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Gemini 4 Argon has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 4 Argon
Gemini 4 Argon leads, 52.6 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V3 0324 has a AA Agentic Index result, 0.8.
Directional only
Reasoning
GPQA Diamond
No call
Only DeepSeek V3 0324 has a GPQA Diamond result, 61.6%.
Directional only
Math
AIME
No call
Only DeepSeek V3 0324 has a AIME result, 52.2%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V3 0324 has a MMLU Pro result, 79.5%.
Directional only
Web design
Design Arena: websites
No call
Only Gemini 4 Argon has a Design Arena: websites result, 1315.
Directional only
General
Vals Index
No call
Only Gemini 4 Argon has a Vals Index result, 69.2%.
Directional only
Long documents
Listed context window
Gemini 4 Argon
Gemini 4 Argon takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3 0324
DeepSeek V3 0324 $0.0008, Gemini 4 Argon $0.0070 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, Gemini 4 Argon 81.0 from 5 benchmarks.
- Widest category
- Math, 62.2 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: DeepSeek V3 0324 37.8% against Gemini 4 Argon 100.0%, 62.2 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against Gemini 4 Argon $10.00 per million output tokens, 9.3x apart.
- Context window
- DeepSeek V3 0324 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.
| Category | DeepSeek V3 0324 | Bars | Gemini 4 Argon | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 1 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 3 | ||
| All shared boards | 0 | 9 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | Not measured | Only DeepSeek V3 0324 measured |
| LiveBench coding | Not measured | 89.7% | Only Gemini 4 Argon measured |
| LMArena WebDev | Not measured | 1678 | Only Gemini 4 Argon measured |
| AA Coding Index | 21.2 | Not measured | Only DeepSeek V3 0324 measured |
| LiveCodeBench (Vals AI) | 65.5% | Not measured | Only DeepSeek V3 0324 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 57.6% | Only Gemini 4 Argon measured |
| Vibe Code Bench (Vals AI) | Not measured | 91.9% | Only Gemini 4 Argon measured |
| Code migration (Vals AI) | Not measured | 68.2% | Only Gemini 4 Argon measured |
| ProgramBench (Vals AI) | Not measured | 2.5% | Only Gemini 4 Argon measured |
| IOI (Vals AI) | Not measured | 100.0% | Only Gemini 4 Argon measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 57.7% | Only Gemini 4 Argon measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 56.0% | Only Gemini 4 Argon measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 21.2% | Only Gemini 4 Argon measured |
| CyberBench (Vals AI) | Not measured | 77.9% | Only Gemini 4 Argon measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | Not measured | Only DeepSeek V3 0324 measured |
| SciCode | 39.0% | 61.8% | Gemini 4 Argon |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | Not measured | Only DeepSeek V3 0324 measured |
| FrontierCode | Not measured | 47.5% | Only Gemini 4 Argon measured |
| FrontierSWE | Not measured | 55.0% | Only Gemini 4 Argon measured |
| WeirdML | 36.1% | Not measured | Only DeepSeek V3 0324 measured |
| ALE-Bench | Not measured | 2100.1 | Only Gemini 4 Argon measured |
| LMArena Text: coding | Not measured | 1546 | Only Gemini 4 Argon measured |
| LMArena Text: software and IT | Not measured | 1556 | Only Gemini 4 Argon measured |
| LMArena WebDev: React | Not measured | 1692 | Only Gemini 4 Argon measured |
| LMArena WebDev: HTML | Not measured | 1643 | Only Gemini 4 Argon measured |
| SciCode | Not measured | 12.3% | Only Gemini 4 Argon measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 52.6 | Gemini 4 Argon |
| Epoch Capabilities Index | Not measured | 166.4 | Only Gemini 4 Argon measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | Not measured | Only DeepSeek V3 0324 measured |
| Design Arena: spreadsheets | Not measured | 1142 | Only Gemini 4 Argon measured |
| LiveBench research | Not measured | 83.1% | Only Gemini 4 Argon measured |
| LiveBench browser | Not measured | 92.0% | Only Gemini 4 Argon measured |
| LiveBench long agentic | Not measured | 69.9% | Only Gemini 4 Argon measured |
| SREBench (Vals AI) | Not measured | 44.3% | Only Gemini 4 Argon measured |
| Finance Agent (Vals AI) | Not measured | 65.4% | Only Gemini 4 Argon measured |
| Tax Agent Bench (Vals AI) | Not measured | 44.6% | Only Gemini 4 Argon measured |
| Legal Research Bench (Vals AI) | Not measured | 54.8% | Only Gemini 4 Argon measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 27.1% | Only Gemini 4 Argon measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 75.2% | Only Gemini 4 Argon measured |
| BioMysteryBench (Vals AI) | Not measured | 76.3% | Only Gemini 4 Argon measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 44.3% | Only Gemini 4 Argon measured |
| Vals Science Index | Not measured | 55.4% | Only Gemini 4 Argon measured |
| Time Horizon Index (Vals AI) | Not measured | 52.5% | Only Gemini 4 Argon measured |
| CUA-bench (Vals AI) | Not measured | 4.8% | Only Gemini 4 Argon measured |
| Robo-bench (Vals AI) | Not measured | 0.8% | Only Gemini 4 Argon measured |
| τ²-Bench Telecom | 47.1% | Not measured | Only DeepSeek V3 0324 measured |
| APEX-Agents | Not measured | 82.4% | Only Gemini 4 Argon measured |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| Vending-Bench 2 | Not measured | $13,718 | Only Gemini 4 Argon measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | Not measured | Only DeepSeek V3 0324 measured |
| LiveBench reasoning | Not measured | 95.1% | Only Gemini 4 Argon measured |
| MysteryMechanism (Vals AI) | Not measured | 45.5% | Only Gemini 4 Argon measured |
| GPQA Diamond (Artificial Analysis run) | 65.5% | Not measured | Only DeepSeek V3 0324 measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 57.1% | Gemini 4 Argon |
| GPQA Diamond (Epoch AI run) | 67.6% | 96.4% | Gemini 4 Argon |
| ARC-AGI | Not measured | 98.5% | Only Gemini 4 Argon measured |
| ARC-AGI-2 | Not measured | 91.3% | Only Gemini 4 Argon measured |
| SimpleBench | 27.2% | Not measured | Only DeepSeek V3 0324 measured |
| Chess puzzles | Not measured | 59.0% | Only Gemini 4 Argon measured |
| Mystery game puzzles | Not measured | 64.0% | Only Gemini 4 Argon measured |
| EBR-bench | Not measured | 64.8% | Only Gemini 4 Argon measured |
| LMArena Text: hard prompts | Not measured | 1546 | Only Gemini 4 Argon measured |
| LMArena Text: expert | Not measured | 1550 | Only Gemini 4 Argon measured |
| LMArena Text: hard prompts in English | Not measured | 1548 | Only Gemini 4 Argon measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| AIME | 52.2% | Not measured | Only DeepSeek V3 0324 measured |
| MATH 500 (Vals AI) | 88.6% | Not measured | Only DeepSeek V3 0324 measured |
| MGSM (Vals AI) | 91.7% | Not measured | Only DeepSeek V3 0324 measured |
| AA Math Index | 41.0 | Not measured | Only DeepSeek V3 0324 measured |
| AIME 2025 (Artificial Analysis run) | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| OTIS Mock AIME | 37.8% | 100.0% | Gemini 4 Argon |
| FrontierMath, tiers 1 to 3 | Not measured | 86.0% | Only Gemini 4 Argon measured |
| FrontierMath, tier 4 | Not measured | 78.0% | Only Gemini 4 Argon measured |
| ProofBench | Not measured | 99.0% | Only Gemini 4 Argon measured |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: math | Not measured | 1536 | Only Gemini 4 Argon measured |
| LMArena Text: mathematical work | Not measured | 1557 | Only Gemini 4 Argon measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | Not measured | Only DeepSeek V3 0324 measured |
| LegalBench (Vals AI) | 77.7% | 88.3% | Gemini 4 Argon |
| CorpFin (Vals AI) | 54.7% | Not measured | Only DeepSeek V3 0324 measured |
| TaxEval (Vals AI) | 71.1% | Not measured | Only DeepSeek V3 0324 measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only DeepSeek V3 0324 measured |
| MedCode (Vals AI) | Not measured | 58.8% | Only Gemini 4 Argon measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only DeepSeek V3 0324 measured |
| SimpleQA Verified | Not measured | 76.0% | Only Gemini 4 Argon measured |
| LMArena Text: science | Not measured | 1548 | Only Gemini 4 Argon measured |
| LMArena Text: medicine and healthcare | Not measured | 1555 | Only Gemini 4 Argon measured |
| LMArena Text: legal and government | Not measured | 1548 | Only Gemini 4 Argon measured |
| LMArena Text: business and finance | Not measured | 1525 | Only Gemini 4 Argon measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1315 | Only Gemini 4 Argon measured |
| Design Arena: UI components | Not measured | 1331 | Only Gemini 4 Argon measured |
| Design Arena: game dev | Not measured | 1375 | Only Gemini 4 Argon measured |
| Design Arena: data viz | Not measured | 1336 | Only Gemini 4 Argon measured |
| Design Arena: 3D | Not measured | 1389 | Only Gemini 4 Argon measured |
| Design Arena: all code categories | Not measured | 1329 | Only Gemini 4 Argon measured |
| LiveBench design | Not measured | 73.7% | Only Gemini 4 Argon measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| Vals Index | Not measured | 69.2% | Only Gemini 4 Argon measured |
| LiveBench data analysis | Not measured | 85.2% | Only Gemini 4 Argon measured |
| Public Benefits Bench (Vals AI) | Not measured | 69.8% | Only Gemini 4 Argon measured |
| SAGE (Vals AI) | Not measured | 53.6% | Only Gemini 4 Argon measured |
| MedScribe (Vals AI) | Not measured | 87.4% | Only Gemini 4 Argon measured |
| IFBench | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| Long context reasoning (AA-LCR) | 40.7% | 79.7% | Gemini 4 Argon |
| DTBench | 64.8% | 97.6% | Gemini 4 Argon |
| LMCA | 15.5% | 63.7% | Gemini 4 Argon |
| Fiction.LiveBench | 50.0% | Not measured | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | 77.0% | Not measured | Only DeepSeek V3 0324 measured |
| Furniture assembly | Not measured | 72.5% | Only Gemini 4 Argon measured |
| LMArena Text | Not measured | 1532 | Only Gemini 4 Argon measured |
| LMArena Text: instruction following | Not measured | 1534 | Only Gemini 4 Argon measured |
| LMArena Text: creative writing | Not measured | 1527 | Only Gemini 4 Argon measured |
| LMArena Text: English | Not measured | 1538 | Only Gemini 4 Argon measured |
| LMArena Text: non-English | Not measured | 1522 | Only Gemini 4 Argon measured |
| LMArena Text: Chinese | Not measured | 1611 | Only Gemini 4 Argon measured |
| LMArena Text: Spanish | Not measured | 1503 | Only Gemini 4 Argon measured |
| LMArena Text: Russian | Not measured | 1534 | Only Gemini 4 Argon measured |
| LMArena Text: multi-turn | Not measured | 1556 | Only Gemini 4 Argon measured |
| LMArena Text: longer queries | Not measured | 1547 | Only Gemini 4 Argon measured |
| LMArena Text: writing and language | Not measured | 1529 | Only Gemini 4 Argon measured |
| LMArena Text: entertainment and media | Not measured | 1527 | Only Gemini 4 Argon measured |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | Gemini 4 Argon | Leader |
|---|---|---|---|
| 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 0324 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3 0324 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3 0324 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.
| Specification | DeepSeek V3 0324 | Google Gemini 4 Argon |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | March 24, 2025 | October 13, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.27 | $2.00 |
| Output $/Mtok | $1.07 | $10.00 |
| Coding index | Not benchmarked | 81.0 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than Gemini 4 Argon for coding?
Only Gemini 4 Argon has a coding score, 81.0 on the Vibe Coding Index; DeepSeek V3 0324 has none, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for output tokens 9.3x cheaper ($1.07 vs $10.00 per million).
Which is cheaper, DeepSeek V3 0324 or Gemini 4 Argon?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; Gemini 4 Argon costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 0324 or Gemini 4 Argon?
Gemini 4 Argon, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3 0324 vs Gemini 4 Argon comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3 0324's coding index rests on 0 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.