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UI-TARS 7B vs Sakana Namazu

UI-TARS 7B costs 20.0x less per output token than Sakana Namazu ($0.20 vs $4.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.

UI-TARS 7BByteDance
Coding
No data
Overall
No data
Output $/M
$0.20
Sakana NamazuSakana
Coding
No data
Overall
No data
Output $/M
$4.00
vs $0.20 vs $4.00 per 1M output tokens. UI-TARS 7B is 20.0x cheaper.

UI-TARS 7B or Sakana Namazu: 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 20.0x cheaper ($0.20 vs $4.00 per million).

No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; Sakana Namazu 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.

At a glance

Coding index
UI-TARS 7B not benchmarked, Sakana Namazu 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 Sakana Namazu $4.00 per million output tokens, 20.0x apart.
Context window
UI-TARS 7B takes 128K tokens, Sakana Namazu 262K.

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
Reasoning benchmarks for UI-TARS 7B and Sakana Namazu
BenchmarkUI-TARS 7BSakana NamazuLeader
Kagi LLM Benchmark20.7%Not measuredOnly UI-TARS 7B measured
Neither model has a result on the other 22 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$0.0002Fits in one request
Sakana Namazu$0.0029Fits in one request

UI-TARS 7B costs less

Repository review

50K input + 3K output tokens

UI-TARS 7B$0.0056Fits in one request
Sakana Namazu$0.059Fits in one request

UI-TARS 7B costs less

Agent loop

200K input + 10K output tokens

UI-TARS 7B$0.022Exceeds the context window
Sakana Namazu$0.230Fits in one request

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.

Specifications of UI-TARS 7B and Sakana Namazu
SpecificationByteDance UI-TARS 7BSakana Namazu
MakerByteDanceSakana
WeightsOpen weightsNo public weights listed
ReleasedJuly 22, 2025August 11, 2026
Context window128K262K
Input $/Mtok$0.10$0.95
Output $/Mtok$0.20$4.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is UI-TARS 7B better than Sakana Namazu for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick UI-TARS 7B for output tokens 20.0x cheaper ($0.20 vs $4.00 per million).

Which is cheaper, UI-TARS 7B or Sakana Namazu?

UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; Sakana Namazu costs $0.95 and $4.00. Cost per solved task is known for neither of them.

Which has the bigger context window, UI-TARS 7B or Sakana Namazu?

Sakana Namazu, with 262K tokens against 128K.

Has any benchmark tested both UI-TARS 7B and Sakana Namazu?

No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; Sakana Namazu has none yet. Compare them on price and context instead. Data as of October 23, 2026.

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