UI-TARS 7B vs Relace Apply 3
UI-TARS 7B costs 6.3x less per output token than Relace Apply 3 ($0.20 vs $1.25 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
- $1.25
UI-TARS 7B or Relace Apply 3: 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 6.3x cheaper ($0.20 vs $1.25 per million).
No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; Relace Apply 3 has none yet. 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
Long documents
Listed context window
Relace Apply 3
Relace Apply 3 takes 256K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
UI-TARS 7B
UI-TARS 7B $0.0002, Relace Apply 3 $0.0015 per turn.
List prices
At a glance
- Coding index
- UI-TARS 7B not benchmarked, Relace Apply 3 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 Relace Apply 3 $1.25 per million output tokens, 6.3x apart.
- Context window
- UI-TARS 7B takes 128K tokens, Relace Apply 3 256K.
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.
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | UI-TARS 7B | Relace Apply 3 | Leader |
|---|---|---|---|
| Kagi LLM Benchmark | 20.7% | Not measured | Only UI-TARS 7B measured |
| Neither model has a result on the other 21 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 | Relace Apply 3 |
|---|---|---|
| Maker | ByteDance | Relace |
| Weights | Open weights | No public weights listed |
| Released | July 22, 2025 | September 26, 2025 |
| Context window | 128K | 256K |
| Input $/Mtok | $0.10 | $0.85 |
| Output $/Mtok | $0.20 | $1.25 |
| 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 Relace Apply 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick UI-TARS 7B for output tokens 6.3x cheaper ($0.20 vs $1.25 per million).
Which is cheaper, UI-TARS 7B or Relace Apply 3?
UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; Relace Apply 3 costs $0.85 and $1.25. Cost per solved task is known for neither of them.
Which has the bigger context window, UI-TARS 7B or Relace Apply 3?
Relace Apply 3, with 256K tokens against 128K.
Has any benchmark tested both UI-TARS 7B and Relace Apply 3?
No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; Relace Apply 3 has none yet. Compare them on price and context instead. Data as of October 22, 2026.