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GLM 5 Turbo vs Fugu Ultra

GLM 5 Turbo costs 7.5x less per output token than Fugu Ultra ($4.00 vs $30.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.

GLM 5 TurboZ.ai
Coding
No data
Overall
No data
Output $/M
$4.00
Fugu UltraSakana
Coding
No data
Overall
No data
Output $/M
$30.00
vs $4.00 vs $30.00 per 1M output tokens. GLM 5 Turbo is 7.5x cheaper.

GLM 5 Turbo or Fugu Ultra: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GLM 5 Turbo for output tokens 7.5x cheaper ($4.00 vs $30.00 per million).

No benchmark has tested both yet. GLM 5 Turbo has results on Terminal-Bench Hard (Artificial Analysis run), ALE-Bench and AA Intelligence Index; Fugu Ultra 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
GLM 5 Turbo not benchmarked, Fugu Ultra 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
GLM 5 Turbo $4.00 against Fugu Ultra $30.00 per million output tokens, 7.5x apart.
Context window
GLM 5 Turbo takes 203K tokens, Fugu Ultra 1M.

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
Coding benchmarks for GLM 5 Turbo and Fugu Ultra
BenchmarkGLM 5 TurboFugu UltraLeader
Terminal-Bench Hard (Artificial Analysis run)33.3%Not measuredOnly GLM 5 Turbo measured
ALE-Bench634.0Not measuredOnly GLM 5 Turbo 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
Intelligence benchmarks for GLM 5 Turbo and Fugu Ultra
BenchmarkGLM 5 TurboFugu UltraLeader
AA Intelligence Index26.6Not measuredOnly GLM 5 Turbo 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
Agentic work benchmarks for GLM 5 Turbo and Fugu Ultra
BenchmarkGLM 5 TurboFugu UltraLeader
τ²-Bench Telecom98.5%Not measuredOnly GLM 5 Turbo measured
Neither model has a result on the other 41 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Reasoning benchmarks for GLM 5 Turbo and Fugu Ultra
BenchmarkGLM 5 TurboFugu UltraLeader
GPQA Diamond (Artificial Analysis run)84.7%Not measuredOnly GLM 5 Turbo measured
Humanity's Last Exam (Artificial Analysis run)27.8%Not measuredOnly GLM 5 Turbo measured
Neither model has a result on the other 21 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
Web design benchmarks for GLM 5 Turbo and Fugu Ultra
BenchmarkGLM 5 TurboFugu UltraLeader
Design Arena: websites1262Not measuredOnly GLM 5 Turbo measured
Design Arena: UI components1261Not measuredOnly GLM 5 Turbo measured
Design Arena: game dev1247Not measuredOnly GLM 5 Turbo measured
Design Arena: data viz1264Not measuredOnly GLM 5 Turbo measured
Design Arena: 3D1248Not measuredOnly GLM 5 Turbo measured
Design Arena: all code categories1261Not measuredOnly GLM 5 Turbo measured
Design Arena: SVG1205Not measuredOnly GLM 5 Turbo measured
Design Arena: ASCII art1160Not measuredOnly GLM 5 Turbo measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
General benchmarks for GLM 5 Turbo and Fugu Ultra
BenchmarkGLM 5 TurboFugu UltraLeader
IFBench73.2%Not measuredOnly GLM 5 Turbo measured
Long context reasoning (AA-LCR)71.7%Not measuredOnly GLM 5 Turbo 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

GLM 5 Turbo$0.0032Fits in one request
Fugu Ultra$0.020Fits in one request

GLM 5 Turbo costs less

Repository review

50K input + 3K output tokens

GLM 5 Turbo$0.072Fits in one request
Fugu Ultra$0.340Fits in one request

GLM 5 Turbo costs less

Agent loop

200K input + 10K output tokens

GLM 5 Turbo$0.280Exceeds the context window
Fugu Ultra$1.30Fits in one request

GLM 5 Turbo 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 GLM 5 Turbo and Fugu Ultra
SpecificationZ.ai GLM 5 TurboSakana Fugu Ultra
MakerZ.aiSakana
WeightsNo public weights listedNo public weights listed
ReleasedMarch 15, 2026June 24, 2026
Context window203K1M
Input $/Mtok$1.20$5.00
Output $/Mtok$4.00$30.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5 Turbo better than Fugu Ultra for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5 Turbo for output tokens 7.5x cheaper ($4.00 vs $30.00 per million).

Which is cheaper, GLM 5 Turbo or Fugu Ultra?

GLM 5 Turbo costs $1.20 per million input tokens and $4.00 per million output tokens; Fugu Ultra costs $5.00 and $30.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 5 Turbo or Fugu Ultra?

Fugu Ultra, with 1M tokens against 203K.

Has any benchmark tested both GLM 5 Turbo and Fugu Ultra?

No benchmark has tested both yet. GLM 5 Turbo has results on Terminal-Bench Hard (Artificial Analysis run), ALE-Bench and AA Intelligence Index; Fugu Ultra has none yet. Compare them on price and context instead. Data as of October 23, 2026.

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