DeepSeek V4 Pro 0423 vs Gemini 2.5 Flash Lite
Updated October 21, 2026. 12 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding.
Gemini 2.5 Flash Lite has the edge where output tokens cost 6.8x less, and where what matters is LegalBench (Vals AI) or MedScribe (Vals AI), where it leads.
- Shared results
- 12
- DeepSeek V4 Pro 0423 only
- 71
- Gemini 2.5 Flash Lite only
- 16
- Like-for-like categories
- 5 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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 DeepSeek V4 Pro 0423 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 30.4 against 10.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Pro 0423 has a AA Agentic Index result, 26.3.
Directional only
Reasoning
GPQA Diamond
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 89.4% against 70.2%.
Same board, both measured
Math
AIME
No call
Only Gemini 2.5 Flash Lite has a AIME result, 42.1%.
Directional only
Knowledge
MMLU Pro
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 87.3% against 79.1%.
Same board, both measured
Web design
Design Arena: websites
No call
Only DeepSeek V4 Pro 0423 has a Design Arena: websites result, 1235.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 2.5 Flash Lite
DeepSeek V4 Pro 0423 $0.0026, Gemini 2.5 Flash Lite $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Pro 0423 has the number, $0.57.
Directional only
At a glance
- Coding index
- DeepSeek V4 Pro 0423 38.7 from 5 benchmarks, Gemini 2.5 Flash Lite not benchmarked.
- Widest category
- Intelligence, 19.6 points apart on average over 2 shared benchmarks.
- Widest single gap
- DTBench: DeepSeek V4 Pro 0423 90.7% against Gemini 2.5 Flash Lite 62.8%, 27.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0423 $2.716 against Gemini 2.5 Flash Lite $0.40 per million output tokens, 6.8x apart.
- Context window
- Both take 1.05M tokens.
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 V4 Pro 0423 | Bars | Gemini 2.5 Flash Lite | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 1 | 0 | ||
| Knowledge | 4 | 1 | ||
| General | 2 | 1 | ||
| All shared boards | 10 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| LMArena WebDev | 1447 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| AA Coding Index | 59.4 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LiveCodeBench (Vals AI) | 87.5% | 71.4% | DeepSeek V4 Pro 0423 |
| SWE-bench Verified (Vals AI) | 77.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 4 (Vals AI) | 11.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Vibe Code Bench (Vals AI) | 49.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Code migration (Vals AI) | 26.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| SkillsBench (Vals AI) | 51.3% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 59.3% | Only Gemini 2.5 Flash Lite measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 4.5% | Only Gemini 2.5 Flash Lite measured |
| FrontierCode | 17.6% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| WeirdML | 48.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| ALE-Bench | 1006.1 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: coding | 1470 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: software and IT | 1469 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena WebDev: React | 1441 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena WebDev: HTML | 1435 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| AA Intelligence Index | 30.4 | 10.4 | DeepSeek V4 Pro 0423 |
| Epoch Capabilities Index | 149.1 | 133.8 | DeepSeek V4 Pro 0423 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| AA Agentic Index | 26.3 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building web apps | 1000 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building full-stack apps | 948 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building Godot games | 1059 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Finance Agent (Vals AI) | 44.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Tax Agent Bench (Vals AI) | 25.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Legal Research Bench (Vals AI) | 23.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Excel Modeling Benchmark (Vals AI) | 51.6% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| τ²-Bench Telecom | Not measured | 19.0% | Only Gemini 2.5 Flash Lite measured |
| Vending-Bench 2 | $3,285 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| GPQA Diamond | 89.4% | 70.2% | DeepSeek V4 Pro 0423 |
| MMMU Pro (Vals AI) | Not measured | 75.4% | Only Gemini 2.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 62.5% | Only Gemini 2.5 Flash Lite measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 6.8% | Only Gemini 2.5 Flash Lite measured |
| GPQA Diamond (Epoch AI run) | 90.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Chess puzzles | 19.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Mystery game puzzles | 17.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts | 1461 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: expert | 1463 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts in English | 1466 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| AIME | Not measured | 42.1% | Only Gemini 2.5 Flash Lite measured |
| MGSM (Vals AI) | Not measured | 89.5% | Only Gemini 2.5 Flash Lite measured |
| AA Math Index | Not measured | 53.3 | Only Gemini 2.5 Flash Lite measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 53.3% | Only Gemini 2.5 Flash Lite measured |
| OTIS Mock AIME | 96.7% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tiers 1 to 3 | 45.3% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tier 4 | 2.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| ProofBench | 16.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: math | 1443 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: mathematical work | 1455 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| MMLU Pro | 87.3% | 79.1% | DeepSeek V4 Pro 0423 |
| LegalBench (Vals AI) | 80.3% | 82.0% | Gemini 2.5 Flash Lite |
| CaseLaw (Vals AI) | 59.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| CorpFin (Vals AI) | 61.4% | 57.6% | DeepSeek V4 Pro 0423 |
| TaxEval (Vals AI) | 72.1% | 66.2% | DeepSeek V4 Pro 0423 |
| MortgageTax (Vals AI) | Not measured | 57.6% | Only Gemini 2.5 Flash Lite measured |
| MedQA (Vals AI) | Not measured | 88.9% | Only Gemini 2.5 Flash Lite measured |
| MedCode (Vals AI) | 40.5% | 34.2% | DeepSeek V4 Pro 0423 |
| MMLU Pro (Artificial Analysis run) | Not measured | 75.9% | Only Gemini 2.5 Flash Lite measured |
| SimpleQA Verified | 47.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: science | 1470 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: medicine and healthcare | 1466 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: legal and government | 1464 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: business and finance | 1443 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| Design Arena: websites | 1235 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: UI components | 1222 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: game dev | 1229 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: data viz | 1202 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: 3D | 1254 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: all code categories | 1240 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: SVG | 1140 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: ASCII art | 1148 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 62.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| SAGE (Vals AI) | Not measured | 30.8% | Only Gemini 2.5 Flash Lite measured |
| MedScribe (Vals AI) | 75.1% | 75.8% | Gemini 2.5 Flash Lite |
| IFBench | Not measured | 49.9% | Only Gemini 2.5 Flash Lite measured |
| Long context reasoning (AA-LCR) | Not measured | 55.7% | Only Gemini 2.5 Flash Lite measured |
| DTBench | 90.7% | 62.8% | DeepSeek V4 Pro 0423 |
| LMCA | 41.2% | 18.1% | DeepSeek V4 Pro 0423 |
| Surface Evolver Bench | 40.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| CL-bench Life | 13.5% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text | 1451 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: instruction following | 1445 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: creative writing | 1446 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: English | 1459 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: non-English | 1439 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Chinese | 1481 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: German | 1458 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Japanese | 1446 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Korean | 1409 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: French | 1473 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Spanish | 1457 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Russian | 1453 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Polish | 1461 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: multi-turn | 1468 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: longer queries | 1458 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: writing and language | 1447 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: entertainment and media | 1431 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Gemini 2.5 Flash Lite | 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
Gemini 2.5 Flash Lite costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Flash Lite costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Flash Lite 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 V4 Pro 0423 | Google Gemini 2.5 Flash Lite |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | April 24, 2026 | July 22, 2025 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.225 | $0.10 |
| Output $/Mtok | $2.716 | $0.40 |
| Coding index | 38.7 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | $0.57 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0423 better than Gemini 2.5 Flash Lite for coding?
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding. Gemini 2.5 Flash Lite has the edge where output tokens cost 6.8x less, and where what matters is LegalBench (Vals AI) or MedScribe (Vals AI), where it leads.
Which is cheaper, DeepSeek V4 Pro 0423 or Gemini 2.5 Flash Lite?
DeepSeek V4 Pro 0423 costs $1.225 per million input tokens and $2.716 per million output tokens; Gemini 2.5 Flash Lite costs $0.10 and $0.40. Cost per solved task is known for DeepSeek V4 Pro 0423 only.
Which has the bigger context window, DeepSeek V4 Pro 0423 or Gemini 2.5 Flash Lite?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4 Pro 0423 vs Gemini 2.5 Flash Lite comparison based on?
12 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0423's coding index rests on 5 independent benchmarks and Gemini 2.5 Flash Lite's on 0. Where only one model has a result, the page says so instead of naming a winner.