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UI-TARS 7B vs GLM 5.3 FlashX

UI-TARS 7B costs 6.3x less per output token than GLM 5.3 FlashX ($0.20 vs $1.25 per million). Updated October 22, 2026; no benchmark has tested both models yet.

UI-TARS 7BByteDance
Coding
No data
Overall
No data
Output $/M
$0.20
GLM 5.3 FlashXZ.ai
Coding
No data
Overall
No data
Output $/M
$1.25
vs $0.20 vs $1.25 per 1M output tokens. UI-TARS 7B is 6.3x cheaper.

UI-TARS 7B or GLM 5.3 FlashX: 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; GLM 5.3 FlashX 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, GLM 5.3 FlashX 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 GLM 5.3 FlashX $1.25 per million output tokens, 6.3x apart.
Context window
UI-TARS 7B takes 128K tokens, GLM 5.3 FlashX 1.05M.

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 GLM 5.3 FlashX
BenchmarkUI-TARS 7BGLM 5.3 FlashXLeader
Kagi LLM Benchmark20.7%Not measuredOnly 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$0.0002Fits in one request
GLM 5.3 FlashX$0.0010Fits in one request

UI-TARS 7B costs less

Repository review

50K input + 3K output tokens

UI-TARS 7B$0.0056Fits in one request
GLM 5.3 FlashX$0.022Fits in one request

UI-TARS 7B costs less

Agent loop

200K input + 10K output tokens

UI-TARS 7B$0.022Exceeds the context window
GLM 5.3 FlashX$0.086Fits 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 GLM 5.3 FlashX
SpecificationByteDance UI-TARS 7BZ.ai GLM 5.3 FlashX
MakerByteDanceZ.ai
WeightsOpen weightsNo public weights listed
ReleasedJuly 22, 2025September 18, 2026
Context window128K1.05M
Input $/Mtok$0.10$0.37
Output $/Mtok$0.20$1.25
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is UI-TARS 7B better than GLM 5.3 FlashX 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 GLM 5.3 FlashX?

UI-TARS 7B costs $0.10 per million input tokens and $0.20 per million output tokens; GLM 5.3 FlashX costs $0.37 and $1.25. Cost per solved task is known for neither of them.

Which has the bigger context window, UI-TARS 7B or GLM 5.3 FlashX?

GLM 5.3 FlashX, with 1.05M tokens against 128K.

Has any benchmark tested both UI-TARS 7B and GLM 5.3 FlashX?

No benchmark has tested both yet. UI-TARS 7B has results on Kagi LLM Benchmark; GLM 5.3 FlashX has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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