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Model A
Claude Mythos 5

Anthropic

Evidence status unavailable

90% interval unavailable

Claude Mythos 5 vs Fugu Cyber

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Sakana AI logo
Model B
Fugu Cyber

Sakana AI

Evidence status unavailable

90% interval unavailable

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.

1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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

    Fugu Cyber

    Fugu Cyber 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

    Fugu Cyber

    Fugu Cyber 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

    Fugu Cyber

    Fugu Cyber 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

    Claude Mythos 5 and Fugu Cyber 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

    Claude Mythos 5 and Fugu Cyber are not ranked on the public lane for agentic, so no winner is named for agentic.

    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.

Shared results
1
Claude Mythos 5 only
14
Fugu Cyber only
1
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.

Agentic

Not comparable
Claude Mythos 5
Not ranked
Fugu Cyber
Not ranked
Basis
BenchAlign lane · 4 vs 2 public rows
Reading
Not comparable

Coding

Not comparable
Claude Mythos 5
Not ranked
Fugu Cyber
Not ranked
Basis
BenchAlign lane · 3 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Mythos 5
Not ranked
Fugu Cyber
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Mythos 5
Not ranked
Fugu Cyber
Not ranked
Basis
BenchAlign lane · 3 vs 0 public rows
Reading
Not comparable

Math

Not comparable
Claude Mythos 5
Not ranked
Fugu Cyber
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Mythos 5
Not ranked
Fugu Cyber
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Mythos 5
84.9
Unranked · 3 rankable rows
Fugu Cyber
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Mythos 5
Not ranked
Fugu Cyber
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
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.

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

Claude Mythos 5
$0.035
Fits in one request
Fugu Cyber
$0.024
Fits in one request

Fugu Cyber has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Mythos 5
$0.65
Fits in one request
Fugu Cyber
$0.408
Fits in one request

Fugu Cyber has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Mythos 5
$0.9
Fits in one request
Fugu Cyber
$0.6
Fits in one request

Fugu Cyber 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.

Context window

Maximum documented context; output-token limits may be lower.

Claude Mythos 5

Fugu Cyber

1M

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Mythos 5

$1 per 1M cached input tokens

Claude API pricing

Fugu Cyber

$0.6 per 1M cached input tokens

Reasoning profile

Claude Mythos 5

Reasoning

Fugu Cyber

Reasoning

Weight access

Claude Mythos 5

Proprietary

Fugu Cyber

Proprietary

License

Claude Mythos 5

Proprietary

Fugu Cyber

Proprietary

Release date

Claude Mythos 5

2026-06-09

Fugu Cyber

2026-07-21

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
Repository review: $0.65 vs $0.408. Cache-heavy agent loop: $0.9 vs $0.6.
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.

Browse raw public benchmark evidence16 rows

Agentic

  • Terminal-Bench 2.0

    Claude Mythos 588%
    Source
    Fugu Cyber

    Not directly comparable

  • OSWorld-Verified

    Claude Mythos 585%
    Source
    Fugu Cyber

    Not directly comparable

  • BrowseComp

    Claude Mythos 588%
    Source
    Fugu Cyber

    Not directly comparable

  • CyberGym

    Claude Mythos 583.8%
    Source
    Fugu Cyber86.9%
    Source

    Fugu Cyber leads this result

  • CTI-REALM

    Claude Mythos 5
    Fugu Cyber72.1%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Mythos 595.5%
    Source
    Fugu Cyber

    Not directly comparable

  • SWE-bench Pro

    Claude Mythos 580.3%
    Source
    Fugu Cyber

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Mythos 588.0%
    Source
    Fugu Cyber

    Not directly comparable

Knowledge

  • GPQA

    Claude Mythos 594.1%
    Source
    Fugu Cyber

    Not directly comparable

  • HLE

    Claude Mythos 564.5%
    Source
    Fugu Cyber

    Not directly comparable

  • HLE w/o tools

    Claude Mythos 559%
    Source
    Fugu Cyber

    Not directly comparable

Math

  • USAMO 2026

    Claude Mythos 597.6%
    Source
    Fugu Cyber

    Not directly comparable

Multilingual

  • SWE Multilingual

    Claude Mythos 592.2%
    Source
    Fugu Cyber

    Not directly comparable

Multimodal

  • SWE-bench Multimodal

    Claude Mythos 554.9%
    Source
    Fugu Cyber

    Not directly comparable

  • CharXiv

    Claude Mythos 593.5%
    Source
    Fugu Cyber

    Not directly comparable

  • CharXiv w/o tools

    Claude Mythos 588.9%
    Source
    Fugu Cyber

    Not directly comparable

Frequently asked questions

Which is better, Claude Mythos 5 or Fugu Cyber?

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, Claude Mythos 5 or Fugu Cyber?

Claude Mythos 5 and Fugu Cyber are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Claude Mythos 5 or Fugu Cyber?

Claude Mythos 5 and Fugu Cyber are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Mythos 5 or Fugu Cyber?

For the stated presets, chat costs $0.035 on Claude Mythos 5 and $0.024 on Fugu Cyber; repository review costs $0.65 and $0.408; the cache-heavy agent loop costs $0.9 and $0.6. Costs use the listed standard API rates.

Which has the larger context window, Claude Mythos 5 or Fugu Cyber?

Both models list the same context window, 1M.

Related comparisons

Last updated September 4, 2026

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