UI-TARS 7B vs Granite 4.2 8B
UI-TARS 7B and Granite 4.2 8B cost about the same per output token ($0.20 vs $0.20 per million). Updated October 23, 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
- $0.20
UI-TARS 7B or Granite 4.2 8B: 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 4.2 8B on AA Coding Index, SciCode and LMArena Text: coding. 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 4.2 8B has a AA Intelligence Index result, 11.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Granite 4.2 8B has a AA Agentic Index result, 1.3.
Directional only
Long documents
Listed context window
Granite 4.2 8B
Granite 4.2 8B takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.2 8B
UI-TARS 7B $0.0002, Granite 4.2 8B $0.0002 per turn.
List prices
At a glance
- Coding index
- UI-TARS 7B not benchmarked, Granite 4.2 8B 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
- Both cost $0.20 per million output tokens.
- Context window
- UI-TARS 7B takes 128K tokens, Granite 4.2 8B 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 Index4 boards measured
| Benchmark | UI-TARS 7B | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 22.4 | Only Granite 4.2 8B measured |
| SciCode | Not measured | 31.5% | Only Granite 4.2 8B measured |
| LMArena Text: coding | Not measured | 1378 | Only Granite 4.2 8B measured |
| LMArena Text: software and IT | Not measured | 1366 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | UI-TARS 7B | Granite 4.2 8B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.1 | Only Granite 4.2 8B 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 4.2 8B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.3 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | UI-TARS 7B | Granite 4.2 8B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 63.1% | Only Granite 4.2 8B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 9.7% | Only Granite 4.2 8B measured |
| LMArena Text: hard prompts | Not measured | 1327 | Only Granite 4.2 8B measured |
| LMArena Text: expert | Not measured | 1386 | Only Granite 4.2 8B measured |
| LMArena Text: hard prompts in English | Not measured | 1344 | Only Granite 4.2 8B measured |
| Kagi LLM Benchmark | 20.7% | Not measured | Only UI-TARS 7B measured |
| Neither model has a result on the other 17 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | UI-TARS 7B | Granite 4.2 8B | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1335 | Only Granite 4.2 8B measured |
| LMArena Text: medicine and healthcare | Not measured | 1332 | Only Granite 4.2 8B measured |
| LMArena Text: legal and government | Not measured | 1327 | Only Granite 4.2 8B measured |
| LMArena Text: business and finance | Not measured | 1322 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 16 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | UI-TARS 7B | Granite 4.2 8B | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 45.0% | Only Granite 4.2 8B measured |
| LMArena Text | Not measured | 1319 | Only Granite 4.2 8B measured |
| LMArena Text: instruction following | Not measured | 1301 | Only Granite 4.2 8B measured |
| LMArena Text: creative writing | Not measured | 1235 | Only Granite 4.2 8B measured |
| LMArena Text: English | Not measured | 1337 | Only Granite 4.2 8B measured |
| LMArena Text: non-English | Not measured | 1300 | Only Granite 4.2 8B measured |
| LMArena Text: Chinese | Not measured | 1365 | Only Granite 4.2 8B measured |
| LMArena Text: Russian | Not measured | 1280 | Only Granite 4.2 8B measured |
| LMArena Text: multi-turn | Not measured | 1300 | Only Granite 4.2 8B measured |
| LMArena Text: longer queries | Not measured | 1324 | Only Granite 4.2 8B measured |
| LMArena Text: writing and language | Not measured | 1269 | Only Granite 4.2 8B measured |
| LMArena Text: entertainment and media | Not measured | 1271 | Only Granite 4.2 8B measured |
| Neither model has a result on the other 36 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 4.2 8B costs less
Repository review
50K input + 3K output tokens
Granite 4.2 8B costs less
Agent loop
200K input + 10K output tokens
Granite 4.2 8B 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 4.2 8B |
|---|---|---|
| Maker | ByteDance | IBM Granite |
| Weights | Open weights | Open weights |
| Released | July 22, 2025 | August 31, 2026 |
| Context window | 128K | 131K |
| Input $/Mtok | $0.10 | $0.08 |
| Output $/Mtok | $0.20 | $0.20 |
| 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 4.2 8B 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 4.2 8B?
UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; Granite 4.2 8B costs $0.08 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, UI-TARS 7B or Granite 4.2 8B?
Granite 4.2 8B, with 131K tokens against 128K.
Has any benchmark tested both UI-TARS 7B and Granite 4.2 8B?
No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; Granite 4.2 8B on AA Coding Index, SciCode and LMArena Text: coding. Compare them on price and context instead. Data as of October 23, 2026.