DeepSeek V4 Flash Vision Exp vs GPT-5 Mini
Updated October 21, 2026. 5 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5 Mini for coding: it scores 59.8 on the Vibe Coding Index against 37.6 for DeepSeek V4 Flash Vision Exp.
Pick DeepSeek V4 Flash Vision Exp when output tokens cost 3.1x less, or when the context window is larger, 1.05M against 400K tokens.
- Shared results
- 5
- DeepSeek V4 Flash Vision Exp only
- 9
- GPT-5 Mini only
- 93
- Like-for-like categories
- 4 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, four public coding benchmarks
GPT-5 Mini
GPT-5 Mini scores 59.8 against 37.6.
One benchmark behind each score
Intelligence
AA Intelligence Index
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp leads, 34.8 against 20.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash Vision Exp has a AA Agentic Index result, 47.5.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5 Mini has a GPQA Diamond result, 80.3%.
Directional only
Math
AIME
No call
Only GPT-5 Mini has a AIME result, 91.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Mini has a MMLU Pro result, 82.2%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5 Mini has a Design Arena: websites result, 1125.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp $0.0005, GPT-5 Mini $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Mini has the number, $0.08.
Directional only
At a glance
- Coding index
- DeepSeek V4 Flash Vision Exp 37.6 from 1 benchmark, GPT-5 Mini 59.8 from 1 benchmark.
- Widest category
- Intelligence, 14.2 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: DeepSeek V4 Flash Vision Exp 34.8 against GPT-5 Mini 20.6, 14.2 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash Vision Exp $0.6468 against GPT-5 Mini $2.00 per million output tokens, 3.1x apart.
- Context window
- DeepSeek V4 Flash Vision Exp takes 1.05M tokens, GPT-5 Mini 400K.
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 Flash Vision Exp | Bars | GPT-5 Mini | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 5 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 59.8% | Only GPT-5 Mini measured |
| SWE-bench Multilingual | Not measured | 39.7% | Only GPT-5 Mini measured |
| LiveBench coding | 37.6% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| AA Coding Index | 65.0 | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveCodeBench (Vals AI) | Not measured | 86.6% | Only GPT-5 Mini measured |
| SWE-bench Verified (Vals AI) | Not measured | 60.8% | Only GPT-5 Mini measured |
| Vibe Code Bench (Vals AI) | Not measured | 14.2% | Only GPT-5 Mini measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 83.8% | Only GPT-5 Mini measured |
| SciCode | 49.7% | 39.0% | DeepSeek V4 Flash Vision Exp |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 33.3% | Only GPT-5 Mini measured |
| Terminal-Bench | Not measured | 34.8% | Only GPT-5 Mini measured |
| WeirdML | Not measured | 52.7% | Only GPT-5 Mini measured |
| LMArena Text: coding | Not measured | 1406 | Only GPT-5 Mini measured |
| LMArena Text: software and IT | Not measured | 1394 | Only GPT-5 Mini measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.8 | 20.6 | DeepSeek V4 Flash Vision Exp |
| Epoch Capabilities Index | Not measured | 145.3 | Only GPT-5 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| AA Agentic Index | 47.5 | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench research | 69.2% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench browser | 64.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench long agentic | 39.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| τ²-Bench Telecom | Not measured | 71.1% | Only GPT-5 Mini measured |
| Vending-Bench 2 | Not measured | -$31 | Only GPT-5 Mini measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 80.3% | Only GPT-5 Mini measured |
| LiveBench reasoning | 85.4% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| MMMU Pro (Vals AI) | Not measured | 78.9% | Only GPT-5 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 91.3% | 82.8% | DeepSeek V4 Flash Vision Exp |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 21.5% | DeepSeek V4 Flash Vision Exp |
| GPQA Diamond (Epoch AI run) | Not measured | 75.0% | Only GPT-5 Mini measured |
| ARC-AGI | Not measured | 54.3% | Only GPT-5 Mini measured |
| ARC-AGI-2 | Not measured | 4.4% | Only GPT-5 Mini measured |
| Chess puzzles | Not measured | 24.0% | Only GPT-5 Mini measured |
| Mystery game puzzles | Not measured | 10.0% | Only GPT-5 Mini measured |
| VPCT | Not measured | 40.2% | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | Not measured | 1380 | Only GPT-5 Mini measured |
| LMArena Text: expert | Not measured | 1379 | Only GPT-5 Mini measured |
| LMArena Text: hard prompts in English | Not measured | 1383 | Only GPT-5 Mini measured |
| LMArena Vision: diagrams | Not measured | 1202 | Only GPT-5 Mini measured |
| LMArena Vision: homework | Not measured | 1210 | Only GPT-5 Mini measured |
| Neither model has a result on the other 5 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 91.5% | Only GPT-5 Mini measured |
| MATH 500 (Vals AI) | Not measured | 94.8% | Only GPT-5 Mini measured |
| MGSM (Vals AI) | Not measured | 92.6% | Only GPT-5 Mini measured |
| AA Math Index | Not measured | 90.7 | Only GPT-5 Mini measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 90.7% | Only GPT-5 Mini measured |
| OTIS Mock AIME | Not measured | 86.7% | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 46.7% | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | Not measured | 12.2% | Only GPT-5 Mini measured |
| ProofBench | Not measured | 9.0% | Only GPT-5 Mini measured |
| MATH level 5 | Not measured | 97.8% | Only GPT-5 Mini measured |
| LMArena Text: math | Not measured | 1378 | Only GPT-5 Mini measured |
| LMArena Text: mathematical work | Not measured | 1380 | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.2% | Only GPT-5 Mini measured |
| LegalBench (Vals AI) | Not measured | 81.8% | Only GPT-5 Mini measured |
| CaseLaw (Vals AI) | Not measured | 68.5% | Only GPT-5 Mini measured |
| CorpFin (Vals AI) | Not measured | 60.2% | Only GPT-5 Mini measured |
| TaxEval (Vals AI) | Not measured | 75.2% | Only GPT-5 Mini measured |
| MortgageTax (Vals AI) | Not measured | 66.9% | Only GPT-5 Mini measured |
| MedQA (Vals AI) | Not measured | 96.1% | Only GPT-5 Mini measured |
| MedCode (Vals AI) | Not measured | 43.0% | Only GPT-5 Mini measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 83.7% | Only GPT-5 Mini measured |
| SimpleQA Verified | Not measured | 21.6% | Only GPT-5 Mini measured |
| LMArena Text: science | Not measured | 1371 | Only GPT-5 Mini measured |
| LMArena Text: medicine and healthcare | Not measured | 1380 | Only GPT-5 Mini measured |
| LMArena Text: legal and government | Not measured | 1375 | Only GPT-5 Mini measured |
| LMArena Text: business and finance | Not measured | 1358 | Only GPT-5 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1125 | Only GPT-5 Mini measured |
| Design Arena: UI components | Not measured | 1106 | Only GPT-5 Mini measured |
| Design Arena: game dev | Not measured | 1130 | Only GPT-5 Mini measured |
| Design Arena: data viz | Not measured | 1131 | Only GPT-5 Mini measured |
| Design Arena: 3D | Not measured | 1037 | Only GPT-5 Mini measured |
| Design Arena: all code categories | Not measured | 1115 | Only GPT-5 Mini measured |
| Design Arena: SVG | Not measured | 1091 | Only GPT-5 Mini measured |
| Design Arena: ASCII art | Not measured | 1124 | Only GPT-5 Mini measured |
| LiveBench design | 70.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | GPT-5 Mini | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.5% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| SAGE (Vals AI) | Not measured | 43.0% | Only GPT-5 Mini measured |
| MedScribe (Vals AI) | Not measured | 80.6% | Only GPT-5 Mini measured |
| IFBench | Not measured | 75.4% | Only GPT-5 Mini measured |
| Long context reasoning (AA-LCR) | 81.3% | 72.3% | DeepSeek V4 Flash Vision Exp |
| DTBench | Not measured | 80.5% | Only GPT-5 Mini measured |
| LMCA | Not measured | 34.2% | Only GPT-5 Mini measured |
| Fiction.LiveBench | Not measured | 69.4% | Only GPT-5 Mini measured |
| Creative writing (Lech Mazur) | Not measured | 83.1% | Only GPT-5 Mini measured |
| LMArena Text | Not measured | 1373 | Only GPT-5 Mini measured |
| LMArena Text: instruction following | Not measured | 1357 | Only GPT-5 Mini measured |
| LMArena Text: creative writing | Not measured | 1325 | Only GPT-5 Mini measured |
| LMArena Vision | Not measured | 1202 | Only GPT-5 Mini measured |
| LMArena Text: English | Not measured | 1379 | Only GPT-5 Mini measured |
| LMArena Text: non-English | Not measured | 1363 | Only GPT-5 Mini measured |
| LMArena Text: Chinese | Not measured | 1386 | Only GPT-5 Mini measured |
| LMArena Text: German | Not measured | 1366 | Only GPT-5 Mini measured |
| LMArena Text: Japanese | Not measured | 1341 | Only GPT-5 Mini measured |
| LMArena Text: Korean | Not measured | 1308 | Only GPT-5 Mini measured |
| LMArena Text: French | Not measured | 1386 | Only GPT-5 Mini measured |
| LMArena Text: Spanish | Not measured | 1354 | Only GPT-5 Mini measured |
| LMArena Text: Russian | Not measured | 1362 | Only GPT-5 Mini measured |
| LMArena Text: Polish | Not measured | 1378 | Only GPT-5 Mini measured |
| LMArena Text: multi-turn | Not measured | 1363 | Only GPT-5 Mini measured |
| LMArena Text: longer queries | Not measured | 1355 | Only GPT-5 Mini measured |
| LMArena Text: writing and language | Not measured | 1344 | Only GPT-5 Mini measured |
| LMArena Text: entertainment and media | Not measured | 1340 | Only GPT-5 Mini measured |
| LMArena Vision: English | Not measured | 1216 | Only GPT-5 Mini measured |
| LMArena Vision: Chinese | Not measured | 1214 | Only GPT-5 Mini measured |
| LMArena Vision: reading text | Not measured | 1199 | Only GPT-5 Mini measured |
| LMArena Vision: humor | Not measured | 1205 | Only GPT-5 Mini measured |
| LMArena Vision: captioning | Not measured | 1217 | Only GPT-5 Mini measured |
| LMArena Vision: recognizing things | Not measured | 1226 | Only GPT-5 Mini measured |
| LMArena Vision: creative writing | Not measured | 1181 | Only GPT-5 Mini 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 V4 Flash Vision Exp | GPT-5 Mini | 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 V4 Flash Vision Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash Vision Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash Vision Exp 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 Flash Vision Exp | OpenAI GPT-5 Mini |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2026 | August 7, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.2156 | $0.25 |
| Output $/Mtok | $0.6468 | $2.00 |
| Coding index | 37.6 | 59.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | $0.08 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash Vision Exp better than GPT-5 Mini for coding?
Pick GPT-5 Mini for coding: it scores 59.8 on the Vibe Coding Index against 37.6 for DeepSeek V4 Flash Vision Exp. Pick DeepSeek V4 Flash Vision Exp when output tokens cost 3.1x less, or when the context window is larger, 1.05M against 400K tokens.
Which is cheaper, DeepSeek V4 Flash Vision Exp or GPT-5 Mini?
DeepSeek V4 Flash Vision Exp costs $0.2156 per million input tokens and $0.6468 per million output tokens; GPT-5 Mini costs $0.25 and $2.00. Cost per solved task is known for GPT-5 Mini only.
Which has the bigger context window, DeepSeek V4 Flash Vision Exp or GPT-5 Mini?
DeepSeek V4 Flash Vision Exp, with 1.05M tokens against 400K.
How many benchmarks is the DeepSeek V4 Flash Vision Exp vs GPT-5 Mini comparison based on?
5 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash Vision Exp's coding index rests on 1 independent benchmark and GPT-5 Mini's on 1. Where only one model has a result, the page says so instead of naming a winner.