Agentic
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Fugu Cyber vs Sakana Fugu-Ultra v1.1
Updated August 22, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload. This is a same-family comparison, so migration details appear when the source data supports them.
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Chat turn cost
1K fresh input + 500 output tokens
Sakana Fugu-Ultra v1.1
Sakana Fugu-Ultra v1.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Sakana Fugu-Ultra v1.1
Sakana Fugu-Ultra v1.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Sakana Fugu-Ultra v1.1
Sakana Fugu-Ultra v1.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 Fugu Cyber only
- Shared results
- 0
- Fugu Cyber only
- 2
- Sakana Fugu-Ultra v1.1 only
- 0
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Fugu Cyber
- Not measured
- Sakana Fugu-Ultra v1.1
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Fugu Cyber | Sakana Fugu-Ultra v1.1 | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Coding | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Fugu Cyber
- $0.024
- Fits in one request
- Sakana Fugu-Ultra v1.1
- $0.02
- Fits in one request
Sakana Fugu-Ultra v1.1 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Fugu Cyber
- $0.408
- Fits in one request
- Sakana Fugu-Ultra v1.1
- $0.34
- Fits in one request
Sakana Fugu-Ultra v1.1 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Fugu Cyber
- $0.6
- Fits in one request
- Sakana Fugu-Ultra v1.1
- $0.5
- Fits in one request
Sakana Fugu-Ultra v1.1 has the lower modeled cost
Costs use the listed standard API rates.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationFugu CyberSakana Fugu-Ultra v1.1
Context window
Maximum documented context; output-token limits may be lower.
Fugu Cyber
1M
Sakana Fugu-Ultra v1.1
1M
API model ID
Fugu Cyber
Not sourced
Sakana Fugu-Ultra v1.1
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Fugu Cyber
$0.6 per 1M cached input tokens
Sakana Fugu-Ultra v1.1
$0.5 per 1M cached input tokens
Documented inputs
Fugu Cyber
Not sourced
Sakana Fugu-Ultra v1.1
Not sourced
Documented outputs
Fugu Cyber
Not sourced
Sakana Fugu-Ultra v1.1
Not sourced
Provider availability
Fugu Cyber
Not sourced
Sakana Fugu-Ultra v1.1
Not sourced
Reasoning profile
Fugu Cyber
Reasoning
Sakana Fugu-Ultra v1.1
Reasoning
Weight access
Fugu Cyber
Proprietary
Sakana Fugu-Ultra v1.1
Proprietary
License
Fugu Cyber
Proprietary
Sakana Fugu-Ultra v1.1
Proprietary
Release date
Fugu Cyber
2026-07-21
Sakana Fugu-Ultra v1.1
2026-07-24
If you are choosing between sibling variants
- Deployment change
- Both entries list Sakana AI as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
- Quality signal
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- Repository review: $0.408 vs $0.34. Cache-heavy agent loop: $0.6 vs $0.5.
- Context tradeoff
- Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Frequently asked questions
Which is better, Fugu Cyber or Sakana Fugu-Ultra v1.1?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Fugu Cyber or Sakana Fugu-Ultra v1.1?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Fugu Cyber or Sakana Fugu-Ultra v1.1?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Fugu Cyber or Sakana Fugu-Ultra v1.1?
For the stated presets, chat costs $0.024 on Fugu Cyber and $0.02 on Sakana Fugu-Ultra v1.1; repository review costs $0.408 and $0.34; the cache-heavy agent loop costs $0.6 and $0.5. Costs use the listed standard API rates.
Which has the larger context window, Fugu Cyber or Sakana Fugu-Ultra v1.1?
Both models list the same context window, 1M.
Related comparisons
Last updated August 22, 2026
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