DeepSeek V3 0324 vs Gemini 2.5 Pro
Gemini 2.5 Pro leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 16.1 to 9.7, and DeepSeek V3 0324 costs 9.3x less per output token ($1.07 vs $10.00 per million). Updated October 22, 2026; 22 benchmarks have a result for both.
DeepSeek V3 0324 or Gemini 2.5 Pro: which to pick
Only Gemini 2.5 Pro has a coding score, 19.1 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
- 22
- DeepSeek V3 0324 only
- 13
- Gemini 2.5 Pro only
- 68
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Gemini 2.5 Pro has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 2.5 Pro
Gemini 2.5 Pro leads, 16.1 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
Gemini 2.5 Pro
Gemini 2.5 Pro leads, 1.6 against 0.8.
Same board, both measured
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 2.5 Pro has a Design Arena: websites result, 1167.
Directional only
Long documents
Listed context window
Gemini 2.5 Pro
Gemini 2.5 Pro 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 2.5 Pro $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Pro has the number, $0.64.
Directional only
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, Gemini 2.5 Pro 19.1 from 3 benchmarks.
- Widest category
- Math, 46.8 points apart on average over 3 shared benchmarks.
- Widest single gap
- OTIS Mock AIME: DeepSeek V3 0324 37.8% against Gemini 2.5 Pro 84.7%, 46.9 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against Gemini 2.5 Pro $10.00 per million output tokens, 9.3x apart.
- Context window
- DeepSeek V3 0324 takes 164K tokens, Gemini 2.5 Pro 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 2.5 Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 2 | ||
| General | 0 | 5 | ||
| All shared boards | 0 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | 53.6% | Gemini 2.5 Pro |
| LMArena WebDev | Not measured | 1226 | Only Gemini 2.5 Pro measured |
| AA Coding Index | 21.2 | 33.3 | Gemini 2.5 Pro |
| LiveCodeBench (Vals AI) | 65.5% | Not measured | Only DeepSeek V3 0324 measured |
| SWE-bench Verified (Vals AI) | Not measured | 54.4% | Only Gemini 2.5 Pro measured |
| Vibe Code Bench (Vals AI) | Not measured | 0.4% | Only Gemini 2.5 Pro measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | 80.1% | Gemini 2.5 Pro |
| SciCode | 39.0% | 46.3% | Gemini 2.5 Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 26.5% | Gemini 2.5 Pro |
| Terminal-Bench | Not measured | 32.6% | Only Gemini 2.5 Pro measured |
| GSO-Bench | Not measured | 3.9% | Only Gemini 2.5 Pro measured |
| WeirdML | 36.1% | 54.0% | Gemini 2.5 Pro |
| LMArena Text: coding | Not measured | 1452 | Only Gemini 2.5 Pro measured |
| LMArena Text: software and IT | Not measured | 1459 | Only Gemini 2.5 Pro measured |
| LMArena WebDev: HTML | Not measured | 1235 | Only Gemini 2.5 Pro measured |
| LMArena WebDev: from an image | Not measured | 1285 | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 16.1 | Gemini 2.5 Pro |
| Epoch Capabilities Index | Not measured | 145.1 | Only Gemini 2.5 Pro measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 1.6 | Gemini 2.5 Pro |
| τ²-Bench Telecom | 47.1% | 54.1% | Gemini 2.5 Pro |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| GDPval | Not measured | 23.3% | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | Not measured | 41.5% | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | Not measured | $574 | Only Gemini 2.5 Pro measured |
| BrowseComp-Plus | Not measured | 29.5% | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | Not measured | Only DeepSeek V3 0324 measured |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 84.4% | Gemini 2.5 Pro |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 22.5% | Gemini 2.5 Pro |
| GPQA Diamond (Epoch AI run) | 67.6% | 85.3% | Gemini 2.5 Pro |
| ARC-AGI | Not measured | 41.0% | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | Not measured | 4.9% | Only Gemini 2.5 Pro measured |
| SimpleBench | 27.2% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: hard prompts | Not measured | 1455 | Only Gemini 2.5 Pro measured |
| LMArena Text: expert | Not measured | 1452 | Only Gemini 2.5 Pro measured |
| LMArena Text: hard prompts in English | Not measured | 1453 | Only Gemini 2.5 Pro measured |
| LMArena Vision: diagrams | Not measured | 1274 | Only Gemini 2.5 Pro measured |
| LMArena Vision: homework | Not measured | 1281 | Only Gemini 2.5 Pro measured |
| Kagi LLM Benchmark | Not measured | 70.3% | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | 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 | 87.7 | Gemini 2.5 Pro |
| AIME 2025 (Artificial Analysis run) | 41.0% | 87.7% | Gemini 2.5 Pro |
| OTIS Mock AIME | 37.8% | 84.7% | Gemini 2.5 Pro |
| FrontierMath, tiers 1 to 3 | Not measured | 24.6% | Only Gemini 2.5 Pro measured |
| FrontierMath, tier 4 | Not measured | 0.0% | Only Gemini 2.5 Pro measured |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: math | Not measured | 1450 | Only Gemini 2.5 Pro measured |
| LMArena Text: mathematical work | Not measured | 1454 | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | Not measured | Only DeepSeek V3 0324 measured |
| LegalBench (Vals AI) | 77.7% | Not measured | Only DeepSeek V3 0324 measured |
| CaseLaw (Vals AI) | Not measured | 63.9% | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 54.7% | 60.8% | Gemini 2.5 Pro |
| TaxEval (Vals AI) | 71.1% | Not measured | Only DeepSeek V3 0324 measured |
| MortgageTax (Vals AI) | Not measured | 68.9% | Only Gemini 2.5 Pro measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only DeepSeek V3 0324 measured |
| MedCode (Vals AI) | Not measured | 50.6% | Only Gemini 2.5 Pro measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | 86.2% | Gemini 2.5 Pro |
| LMArena Text: science | Not measured | 1480 | Only Gemini 2.5 Pro measured |
| LMArena Text: medicine and healthcare | Not measured | 1476 | Only Gemini 2.5 Pro measured |
| LMArena Text: legal and government | Not measured | 1480 | Only Gemini 2.5 Pro measured |
| LMArena Text: business and finance | Not measured | 1439 | Only Gemini 2.5 Pro measured |
| FACTS Benchmark Suite | Not measured | 61.5% | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1167 | Only Gemini 2.5 Pro measured |
| Design Arena: UI components | Not measured | 1137 | Only Gemini 2.5 Pro measured |
| Design Arena: game dev | Not measured | 1111 | Only Gemini 2.5 Pro measured |
| Design Arena: data viz | Not measured | 1222 | Only Gemini 2.5 Pro measured |
| Design Arena: 3D | Not measured | 1080 | Only Gemini 2.5 Pro measured |
| Design Arena: all code categories | Not measured | 1152 | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.9% | Only Gemini 2.5 Pro measured |
| MedScribe (Vals AI) | Not measured | 73.5% | Only Gemini 2.5 Pro measured |
| IFBench | 41.0% | 48.7% | Gemini 2.5 Pro |
| Long context reasoning (AA-LCR) | 40.7% | 69.0% | Gemini 2.5 Pro |
| DTBench | 64.8% | 82.4% | Gemini 2.5 Pro |
| LMCA | 15.5% | 34.8% | Gemini 2.5 Pro |
| Fiction.LiveBench | 50.0% | Not measured | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | 77.0% | 83.8% | Gemini 2.5 Pro |
| LMArena Text | Not measured | 1458 | Only Gemini 2.5 Pro measured |
| LMArena Text: instruction following | Not measured | 1437 | Only Gemini 2.5 Pro measured |
| LMArena Text: creative writing | Not measured | 1454 | Only Gemini 2.5 Pro measured |
| LMArena Vision | Not measured | 1263 | Only Gemini 2.5 Pro measured |
| LMArena Text: English | Not measured | 1458 | Only Gemini 2.5 Pro measured |
| LMArena Text: non-English | Not measured | 1452 | Only Gemini 2.5 Pro measured |
| LMArena Text: Chinese | Not measured | 1507 | Only Gemini 2.5 Pro measured |
| LMArena Text: German | Not measured | 1487 | Only Gemini 2.5 Pro measured |
| LMArena Text: Japanese | Not measured | 1461 | Only Gemini 2.5 Pro measured |
| LMArena Text: Korean | Not measured | 1434 | Only Gemini 2.5 Pro measured |
| LMArena Text: French | Not measured | 1473 | Only Gemini 2.5 Pro measured |
| LMArena Text: Spanish | Not measured | 1474 | Only Gemini 2.5 Pro measured |
| LMArena Text: Russian | Not measured | 1461 | Only Gemini 2.5 Pro measured |
| LMArena Text: Polish | Not measured | 1479 | Only Gemini 2.5 Pro measured |
| LMArena Text: multi-turn | Not measured | 1453 | Only Gemini 2.5 Pro measured |
| LMArena Text: longer queries | Not measured | 1449 | Only Gemini 2.5 Pro measured |
| LMArena Text: writing and language | Not measured | 1454 | Only Gemini 2.5 Pro measured |
| LMArena Text: entertainment and media | Not measured | 1441 | Only Gemini 2.5 Pro measured |
| LMArena Vision: English | Not measured | 1261 | Only Gemini 2.5 Pro measured |
| LMArena Vision: Chinese | Not measured | 1300 | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | Not measured | 1270 | Only Gemini 2.5 Pro measured |
| LMArena Vision: humor | Not measured | 1262 | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | Not measured | 1304 | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | Not measured | 1283 | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | Not measured | 1265 | Only Gemini 2.5 Pro measured |
| LMArena Document | Not measured | 1421 | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | Gemini 2.5 Pro | 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 2.5 Pro |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | March 24, 2025 | June 17, 2025 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.27 | $1.25 |
| Output $/Mtok | $1.07 | $10.00 |
| Coding index | Not benchmarked | 19.1 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $0.64 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than Gemini 2.5 Pro for coding?
Only Gemini 2.5 Pro has a coding score, 19.1 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 2.5 Pro?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; Gemini 2.5 Pro costs $1.25 and $10.00. Cost per solved task is known for Gemini 2.5 Pro only.
Which has the bigger context window, DeepSeek V3 0324 or Gemini 2.5 Pro?
Gemini 2.5 Pro, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3 0324 vs Gemini 2.5 Pro comparison based on?
22 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3 0324's coding index rests on 0 independent benchmarks and Gemini 2.5 Pro's on 3. Where only one model has a result, the page says so instead of naming a winner.