UI-TARS 7B vs DeepSeek V4 Flash 0423
UI-TARS 7B costs 1.4x less per output token than DeepSeek V4 Flash 0423 ($0.20 vs $0.28 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
UI-TARS 7B or DeepSeek V4 Flash 0423: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick UI-TARS 7B for output tokens 1.4x cheaper ($0.20 vs $0.28 per million) and work measured by Kagi LLM Benchmark, where it leads.
- Shared results
- 1
- UI-TARS 7B only
- 0
- DeepSeek V4 Flash 0423 only
- 48
- Like-for-like categories
- 1 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only DeepSeek V4 Flash 0423 has a AA Intelligence Index result, 24.4.
Directional only
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash 0423 has a AA Agentic Index result, 26.3.
Directional only
Web design
Design Arena: websites
No call
Only DeepSeek V4 Flash 0423 has a Design Arena: websites result, 1207.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash 0423
DeepSeek V4 Flash 0423 takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
UI-TARS 7B
UI-TARS 7B $0.0002, DeepSeek V4 Flash 0423 $0.0003 per turn.
List prices
At a glance
- Coding index
- UI-TARS 7B not benchmarked, DeepSeek V4 Flash 0423 not benchmarked.
- Widest category
- Reasoning, 31.5 points apart on average over 1 shared benchmark.
- Widest single gap
- Kagi LLM Benchmark: UI-TARS 7B 20.7% against DeepSeek V4 Flash 0423 52.2%, 31.5 points apart on a 0 to 100 scale.
- Output price
- UI-TARS 7B $0.20 against DeepSeek V4 Flash 0423 $0.28 per million output tokens, 1.4x apart.
- Context window
- UI-TARS 7B takes 128K tokens, DeepSeek V4 Flash 0423 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 | UI-TARS 7B | Bars | DeepSeek V4 Flash 0423 | Ties |
|---|---|---|---|---|
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1582 | Only DeepSeek V4 Flash 0423 measured |
| AA Coding Index | Not measured | 52.0 | Only DeepSeek V4 Flash 0423 measured |
| WeirdML | Not measured | 45.6% | Only DeepSeek V4 Flash 0423 measured |
| ALE-Bench | Not measured | 678.2 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: coding | Not measured | 1457 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: software and IT | Not measured | 1453 | Only DeepSeek V4 Flash 0423 measured |
| LMArena WebDev: React | Not measured | 1585 | Only DeepSeek V4 Flash 0423 measured |
| LMArena WebDev: HTML | Not measured | 1558 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 24.4 | Only DeepSeek V4 Flash 0423 measured |
| Epoch Capabilities Index | Not measured | 146.1 | Only DeepSeek V4 Flash 0423 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 26.3 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| SimpleBench | Not measured | 46.3% | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: hard prompts | Not measured | 1444 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: expert | Not measured | 1441 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: hard prompts in English | Not measured | 1449 | Only DeepSeek V4 Flash 0423 measured |
| Kagi LLM Benchmark | 20.7% | 52.2% | DeepSeek V4 Flash 0423 |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1426 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: mathematical work | Not measured | 1432 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1446 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: medicine and healthcare | Not measured | 1448 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: legal and government | Not measured | 1439 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: business and finance | Not measured | 1425 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1207 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: UI components | Not measured | 1162 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: game dev | Not measured | 1196 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: data viz | Not measured | 1127 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: 3D | Not measured | 1188 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: all code categories | Not measured | 1205 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: SVG | Not measured | 1155 | Only DeepSeek V4 Flash 0423 measured |
| Design Arena: ASCII art | Not measured | 1109 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | Leader |
|---|---|---|---|
| DTBench | Not measured | 86.4% | Only DeepSeek V4 Flash 0423 measured |
| LMCA | Not measured | 35.9% | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text | Not measured | 1432 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: instruction following | Not measured | 1421 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: creative writing | Not measured | 1403 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: English | Not measured | 1441 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: non-English | Not measured | 1419 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Chinese | Not measured | 1463 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: German | Not measured | 1419 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Japanese | Not measured | 1389 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Korean | Not measured | 1383 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: French | Not measured | 1439 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Spanish | Not measured | 1436 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Russian | Not measured | 1427 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: Polish | Not measured | 1436 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: multi-turn | Not measured | 1449 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: longer queries | Not measured | 1434 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: writing and language | Not measured | 1410 | Only DeepSeek V4 Flash 0423 measured |
| LMArena Text: entertainment and media | Not measured | 1400 | Only DeepSeek V4 Flash 0423 measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | UI-TARS 7B | DeepSeek V4 Flash 0423 | 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
UI-TARS 7B costs less
Repository review
50K input + 3K output tokens
UI-TARS 7B costs less
Agent loop
200K input + 10K output tokens
UI-TARS 7B 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 | ByteDance UI-TARS 7B | DeepSeek V4 Flash 0423 |
|---|---|---|
| Maker | ByteDance | DeepSeek |
| Weights | Open weights | Open weights |
| Released | July 22, 2025 | April 24, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.10 | $0.14 |
| Output $/Mtok | $0.20 | $0.28 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is UI-TARS 7B better than DeepSeek V4 Flash 0423 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick UI-TARS 7B for output tokens 1.4x cheaper ($0.20 vs $0.28 per million) and work measured by Kagi LLM Benchmark, where it leads.
Which is cheaper, UI-TARS 7B or DeepSeek V4 Flash 0423?
UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; DeepSeek V4 Flash 0423 costs $0.14 and $0.28. Cost per solved task is known for neither of them.
Which has the bigger context window, UI-TARS 7B or DeepSeek V4 Flash 0423?
DeepSeek V4 Flash 0423, with 1.05M tokens against 128K.
How many benchmarks is the UI-TARS 7B vs DeepSeek V4 Flash 0423 comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. UI-TARS 7B's coding index rests on 0 independent benchmarks and DeepSeek V4 Flash 0423's on 1. Where only one model has a result, the page says so instead of naming a winner.