UI-TARS 7B vs DeepSeek V3 0324
UI-TARS 7B costs 5.3x less per output token than DeepSeek V3 0324 ($0.20 vs $1.07 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.20
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.07
UI-TARS 7B or DeepSeek V3 0324: 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 5.3x cheaper ($0.20 vs $1.07 per million).
No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; DeepSeek V3 0324 on SWE-bench Verified, AA Coding Index and LiveCodeBench (Vals AI). Compare them on price and context instead.
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 V3 0324 has a AA Intelligence Index result, 9.7.
Directional only
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
Long documents
Listed context window
DeepSeek V3 0324
DeepSeek V3 0324 takes 164K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
UI-TARS 7B
UI-TARS 7B $0.0002, DeepSeek V3 0324 $0.0008 per turn.
List prices
At a glance
- Coding index
- UI-TARS 7B not benchmarked, DeepSeek V3 0324 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- UI-TARS 7B $0.20 against DeepSeek V3 0324 $1.07 per million output tokens, 5.3x apart.
- Context window
- UI-TARS 7B takes 128K tokens, DeepSeek V3 0324 164K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards measured
| Benchmark | UI-TARS 7B | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 42.0% | Only DeepSeek V3 0324 measured |
| AA Coding Index | Not measured | 21.2 | Only DeepSeek V3 0324 measured |
| LiveCodeBench (Vals AI) | Not measured | 65.5% | Only DeepSeek V3 0324 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 40.5% | Only DeepSeek V3 0324 measured |
| SciCode | Not measured | 39.0% | Only DeepSeek V3 0324 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 15.2% | Only DeepSeek V3 0324 measured |
| WeirdML | Not measured | 36.1% | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | UI-TARS 7B | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 9.7 | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | UI-TARS 7B | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.8 | Only DeepSeek V3 0324 measured |
| τ²-Bench Telecom | Not measured | 47.1% | Only DeepSeek V3 0324 measured |
| METR time horizons | Not measured | 49.6% | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | UI-TARS 7B | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 61.6% | Only DeepSeek V3 0324 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 65.5% | Only DeepSeek V3 0324 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 4.7% | Only DeepSeek V3 0324 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 67.6% | Only DeepSeek V3 0324 measured |
| SimpleBench | Not measured | 27.2% | Only DeepSeek V3 0324 measured |
| Kagi LLM Benchmark | 20.7% | Not measured | Only UI-TARS 7B measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | UI-TARS 7B | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| AIME | Not measured | 52.2% | Only DeepSeek V3 0324 measured |
| MATH 500 (Vals AI) | Not measured | 88.6% | Only DeepSeek V3 0324 measured |
| MGSM (Vals AI) | Not measured | 91.7% | Only DeepSeek V3 0324 measured |
| AA Math Index | Not measured | 41.0 | Only DeepSeek V3 0324 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 41.0% | Only DeepSeek V3 0324 measured |
| OTIS Mock AIME | Not measured | 37.8% | Only DeepSeek V3 0324 measured |
| MATH level 5 | Not measured | 75.5% | Only DeepSeek V3 0324 measured |
| MathArena | Not measured | 7.1% | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | UI-TARS 7B | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 79.5% | Only DeepSeek V3 0324 measured |
| LegalBench (Vals AI) | Not measured | 77.7% | Only DeepSeek V3 0324 measured |
| CorpFin (Vals AI) | Not measured | 54.7% | Only DeepSeek V3 0324 measured |
| TaxEval (Vals AI) | Not measured | 71.1% | Only DeepSeek V3 0324 measured |
| MedQA (Vals AI) | Not measured | 82.0% | Only DeepSeek V3 0324 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 81.9% | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 14 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | UI-TARS 7B | DeepSeek V3 0324 | Leader |
|---|---|---|---|
| IFBench | Not measured | 41.0% | Only DeepSeek V3 0324 measured |
| Long context reasoning (AA-LCR) | Not measured | 40.7% | Only DeepSeek V3 0324 measured |
| DTBench | Not measured | 64.8% | Only DeepSeek V3 0324 measured |
| LMCA | Not measured | 15.5% | Only DeepSeek V3 0324 measured |
| Fiction.LiveBench | Not measured | 50.0% | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | Not measured | 77.0% | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 42 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 V3 0324 |
|---|---|---|
| Maker | ByteDance | DeepSeek |
| Weights | Open weights | Open weights |
| Released | July 22, 2025 | March 24, 2025 |
| Context window | 128K | 164K |
| Input $/Mtok | $0.10 | $0.27 |
| Output $/Mtok | $0.20 | $1.07 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is UI-TARS 7B better than DeepSeek V3 0324 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick UI-TARS 7B for output tokens 5.3x cheaper ($0.20 vs $1.07 per million).
Which is cheaper, UI-TARS 7B or DeepSeek V3 0324?
UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; DeepSeek V3 0324 costs $0.27 and $1.07. Cost per solved task is known for neither of them.
Which has the bigger context window, UI-TARS 7B or DeepSeek V3 0324?
DeepSeek V3 0324, with 164K tokens against 128K.
Has any benchmark tested both UI-TARS 7B and DeepSeek V3 0324?
No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; DeepSeek V3 0324 on SWE-bench Verified, AA Coding Index and LiveCodeBench (Vals AI). Compare them on price and context instead. Data as of October 22, 2026.