Agentic
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- Not ranked
- Basis
- BenchAlign lane · 1 vs 1 public rows
- Reading
- Not comparable
Laguna XS 2.1 vs Sakana Fugu-Ultra
Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Long documents
Prompts that approach the documented context limit
Sakana Fugu-Ultra
Sakana Fugu-Ultra has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Laguna XS 2.1 and Sakana Fugu-Ultra are not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Laguna XS 2.1 and Sakana Fugu-Ultra are not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 Laguna XS 2.1 only
3 Shared
8 Sakana Fugu-Ultra only
- Shared results
- 3
- Laguna XS 2.1 only
- 2
- Sakana Fugu-Ultra only
- 8
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Coding
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- Not ranked
- Basis
- BenchAlign lane · 4 vs 5 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- 77.9
- Unranked · 1 rankable row
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- Not ranked
- Basis
- BenchAlign lane · 0 vs 3 public rows
- Reading
- Not comparable
Math
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- 72.8
- Unranked · 1 rankable row
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Laguna XS 2.1
- Not ranked
- Sakana Fugu-Ultra
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Laguna XS 2.1 | Sakana Fugu-Ultra | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | Not ranked | Not comparableBenchAlign lane · 1 vs 1 public rows | Not comparable |
| Coding | Not ranked | Not ranked | Not comparableBenchAlign lane · 4 vs 5 public rows | Not comparable |
| Reasoning | Not ranked | 77.9Unranked · 1 rankable row | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Knowledge | Not ranked | Not ranked | Not comparableBenchAlign lane · 0 vs 3 public rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 72.8Unranked · 1 rankable row | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
Terminal-Bench 2.0
Agentic
Laguna XS 2.1: 37.5%Sakana Fugu-Ultra: 82.1%Normalized gap 44.6Laguna XS 2.1 source Sakana Fugu-Ultra sourceSWE-bench Pro
Coding
Laguna XS 2.1: 47.6%Sakana Fugu-Ultra: 73.7%Normalized gap 26.1Laguna XS 2.1 source Sakana Fugu-Ultra source
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
- Laguna XS 2.1
- $0.0002
- Fits in one request
- Sakana Fugu-Ultra
- API rate not published
- Fits in one request
Sakana Fugu-Ultra has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Laguna XS 2.1
- $0.0056
- Fits in one request
- Sakana Fugu-Ultra
- API rate not published
- Fits in one request
Sakana Fugu-Ultra has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Laguna XS 2.1
- $0.014
- Fits in one request
- Sakana Fugu-Ultra
- API rate not published
- Fits in one request
- Cached-input rate unavailable
Sakana Fugu-Ultra has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationLaguna XS 2.1Sakana Fugu-Ultra
Context window
Maximum documented context; output-token limits may be lower.
Laguna XS 2.1
Sakana Fugu-Ultra
1M
API model ID
Laguna XS 2.1
poolside/Laguna-XS-2.1
Poolside Laguna XS 2.1 launch postSakana Fugu-Ultra
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Laguna XS 2.1
$0.05 per 1M cached input tokens
Poolside Laguna XS 2.1 launch postSakana Fugu-Ultra
No comparable hosted API rate
Documented inputs
Laguna XS 2.1
Not sourced
Sakana Fugu-Ultra
Not sourced
Documented outputs
Laguna XS 2.1
Not sourced
Sakana Fugu-Ultra
Not sourced
Provider availability
Laguna XS 2.1
Not sourced
Sakana Fugu-Ultra
Not sourced
Reasoning profile
Laguna XS 2.1
Reasoning
Sakana Fugu-Ultra
Reasoning
Weight access
Laguna XS 2.1
Open Weight
Sakana Fugu-Ultra
Proprietary
License
Laguna XS 2.1
Open Weight
Sakana Fugu-Ultra
Proprietary
Release date
Laguna XS 2.1
2026-07-02
Sakana Fugu-Ultra
2026-06-22
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Sakana Fugu-Ultra has the larger documented window (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.
Browse raw public benchmark evidence13 rows
Agentic
Coding
SWE-bench Verified
Laguna XS 2.170.9%SourceSakana Fugu-Ultra—Not directly comparable
SWE Multilingual
Laguna XS 2.163.1%SourceSakana Fugu-Ultra—Not directly comparable
SWE-bench Pro
Laguna XS 2.147.6%SourceSakana Fugu-Ultra73.7%SourceSakana Fugu-Ultra leads this result
Terminal-Bench 2.0
Laguna XS 2.137.5%SourceSakana Fugu-Ultra82.1%SourceSakana Fugu-Ultra leads this result
LiveCodeBench v6
Laguna XS 2.1—Sakana Fugu-Ultra93.2%SourceNot directly comparable
LiveCodeBench Pro
Laguna XS 2.1—Sakana Fugu-Ultra90.8%SourceNot directly comparable
SciCode
Laguna XS 2.1—Sakana Fugu-Ultra58.7%SourceNot directly comparable
Reasoning
MRCRv2
Laguna XS 2.1—Sakana Fugu-Ultra93.6%SourceNot directly comparable
Knowledge
Multimodal
CharXiv
Laguna XS 2.1—Sakana Fugu-Ultra86.6%SourceNot directly comparable
Frequently asked questions
Which is better, Laguna XS 2.1 or Sakana Fugu-Ultra?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Laguna XS 2.1 or Sakana Fugu-Ultra?
Laguna XS 2.1 and Sakana Fugu-Ultra are not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Laguna XS 2.1 or Sakana Fugu-Ultra?
Laguna XS 2.1 and Sakana Fugu-Ultra are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Laguna XS 2.1 or Sakana Fugu-Ultra?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Laguna XS 2.1 or Sakana Fugu-Ultra?
Sakana Fugu-Ultra has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 10, 2026
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