UI-TARS 7B vs Mistral Small 4
UI-TARS 7B costs 3.0x less per output token than Mistral Small 4 ($0.20 vs $0.60 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
UI-TARS 7B or Mistral Small 4: 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 3.0x cheaper ($0.20 vs $0.60 per million) and work measured by Kagi LLM Benchmark, where it leads.
- Shared results
- 1
- UI-TARS 7B only
- 0
- Mistral Small 4 only
- 14
- 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 Mistral Small 4 has a AA Intelligence Index result, 11.3.
Directional only
Agentic work
AA Agentic Index
No call
Only Mistral Small 4 has a AA Agentic Index result, 0.8.
Directional only
Long documents
Listed context window
Mistral Small 4
Mistral Small 4 takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
UI-TARS 7B
UI-TARS 7B $0.0002, Mistral Small 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- UI-TARS 7B not benchmarked, Mistral Small 4 not benchmarked.
- Widest category
- Reasoning, 19.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Kagi LLM Benchmark: UI-TARS 7B 20.7% against Mistral Small 4 40.5%, 19.8 points apart on a 0 to 100 scale.
- Output price
- UI-TARS 7B $0.20 against Mistral Small 4 $0.60 per million output tokens, 3.0x apart.
- Context window
- UI-TARS 7B takes 128K tokens, Mistral Small 4 262K.
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 | Mistral Small 4 | Ties |
|---|---|---|---|---|
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 26.6 | Only Mistral Small 4 measured |
| Vibe Code Bench (Vals AI) | Not measured | 0.0% | Only Mistral Small 4 measured |
| SciCode | Not measured | 38.8% | Only Mistral Small 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 17.4% | Only Mistral Small 4 measured |
| ALE-Bench | Not measured | 497.6 | Only Mistral Small 4 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.3 | Only Mistral Small 4 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.8 | Only Mistral Small 4 measured |
| τ²-Bench Telecom | Not measured | 41.2% | Only Mistral Small 4 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 76.9% | Only Mistral Small 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 9.9% | Only Mistral Small 4 measured |
| Kagi LLM Benchmark | 20.7% | 40.5% | Mistral Small 4 |
| Neither model has a result on the other 19 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | Leader |
|---|---|---|---|
| IFBench | Not measured | 48.2% | Only Mistral Small 4 measured |
| Long context reasoning (AA-LCR) | Not measured | 49.7% | Only Mistral Small 4 measured |
| DTBench | Not measured | 70.9% | Only Mistral Small 4 measured |
| LMCA | Not measured | 20.6% | Only Mistral Small 4 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | UI-TARS 7B | Mistral Small 4 | 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 | Mistral Small 4 |
|---|---|---|
| Maker | ByteDance | Mistral AI |
| Weights | Open weights | Open weights |
| Released | July 22, 2025 | March 16, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.10 | $0.15 |
| Output $/Mtok | $0.20 | $0.60 |
| 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 Mistral Small 4 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick UI-TARS 7B for output tokens 3.0x cheaper ($0.20 vs $0.60 per million) and work measured by Kagi LLM Benchmark, where it leads.
Which is cheaper, UI-TARS 7B or Mistral Small 4?
UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; Mistral Small 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, UI-TARS 7B or Mistral Small 4?
Mistral Small 4, with 262K tokens against 128K.
How many benchmarks is the UI-TARS 7B vs Mistral Small 4 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 Mistral Small 4's on 1. Where only one model has a result, the page says so instead of naming a winner.