UI-TARS 7B vs Granite 4.0 Micro
Granite 4.0 Micro costs 1.8x less per output token than UI-TARS 7B ($0.112 vs $0.20 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
- $0.112
UI-TARS 7B or Granite 4.0 Micro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; Granite 4.0 Micro on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and AA Intelligence Index. 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 Granite 4.0 Micro has a AA Intelligence Index result, 5.1.
Directional only
Long documents
Listed context window
Granite 4.0 Micro
Granite 4.0 Micro takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.0 Micro
UI-TARS 7B $0.0002, Granite 4.0 Micro $0.0001 per turn.
List prices
At a glance
- Coding index
- UI-TARS 7B not benchmarked, Granite 4.0 Micro 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 Granite 4.0 Micro $0.112 per million output tokens, 1.8x apart.
- Context window
- UI-TARS 7B takes 128K tokens, Granite 4.0 Micro 131K.
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 Index2 boards measured
| Benchmark | UI-TARS 7B | Granite 4.0 Micro | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 18.0% | Only Granite 4.0 Micro measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 1.5% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 41 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | UI-TARS 7B | Granite 4.0 Micro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 5.1 | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | UI-TARS 7B | Granite 4.0 Micro | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 12.6% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | UI-TARS 7B | Granite 4.0 Micro | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 33.6% | Only Granite 4.0 Micro measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 5.0% | Only Granite 4.0 Micro measured |
| GPQA Diamond (Epoch AI run) | Not measured | 28.3% | Only Granite 4.0 Micro measured |
| Kagi LLM Benchmark | 20.7% | Not measured | Only UI-TARS 7B measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | UI-TARS 7B | Granite 4.0 Micro | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 6.0 | Only Granite 4.0 Micro measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 6.0% | Only Granite 4.0 Micro measured |
| OTIS Mock AIME | Not measured | 2.8% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | UI-TARS 7B | Granite 4.0 Micro | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 44.7% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 19 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | UI-TARS 7B | Granite 4.0 Micro | Leader |
|---|---|---|---|
| IFBench | Not measured | 24.8% | Only Granite 4.0 Micro measured |
| Long context reasoning (AA-LCR) | Not measured | 7.0% | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 46 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
Granite 4.0 Micro costs less
Repository review
50K input + 3K output tokens
Granite 4.0 Micro costs less
Agent loop
200K input + 10K output tokens
Granite 4.0 Micro 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 | IBM Granite 4.0 Micro |
|---|---|---|
| Maker | ByteDance | IBM Granite |
| Weights | Open weights | Open weights |
| Released | July 22, 2025 | October 20, 2025 |
| Context window | 128K | 131K |
| Input $/Mtok | $0.10 | $0.017 |
| Output $/Mtok | $0.20 | $0.112 |
| 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 Granite 4.0 Micro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, UI-TARS 7B or Granite 4.0 Micro?
UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; Granite 4.0 Micro costs $0.017 and $0.112. Cost per solved task is known for neither of them.
Which has the bigger context window, UI-TARS 7B or Granite 4.0 Micro?
Granite 4.0 Micro, with 131K tokens against 128K.
Has any benchmark tested both UI-TARS 7B and Granite 4.0 Micro?
No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; Granite 4.0 Micro on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.