Model Cards / Anthropic

Claude Fable 5 & Mythos 5 System Card

model card66,240 words·288 min read·Jun 28, 2026·Source
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Summary
66,240-word document condensed to 287 words. Anthropic · Jun 28, 2026
TL;DR

throughout the system card. We preserved model welfare context about the initial safeguards, noting where the prior version is described.

Top benchmarks
BenchmarkVariantScore
GDPval-AAeconomically valuable knowledge work1932.00
SWE-bench Verifiedmax effort95.5%
SWE-bench Verifiedproduction safeguards95.0%
SWE-bench Multilingual9 languages92.2%
GraphWalks BFS 256Klong context91.1%
CharXiv Reasoningno tools88.9%
Terminal-bench 2.1mini-SWE harness88.0%
BrowseCompsingle-agent88.0%

Showing top 8 of 27. See full list below.

Capability claim
  • we are releasing it in these two forms: Fable 5, which is for general use but comes with additional safeguards that block its ability to perform tasks in high-risk domains such as biology and cybersecurity; and Mythos 5, which has relevant safeguards lifted but is only made available to a small number of trusted partners (beginning with those in Project Glasswing).
Safety findings
  • We believe these mitigations make catastrophic risk in this category low but still not negligible, for reasons discussed in our most recent Risk Report.
  • We believe that Mythos 5 falls short of the specific threshold in version 3.3 of our RSP and in our FCF. But we are nonetheless concerned about the risks it poses in this category, and we think that world-class human expert substitution may now be possible in a few areas.
  • we believe to be grader-incentivized. Rates of three behaviors in response to steering against grader awareness with three different vectors, on training environments with high-risk of grader exploitation.
Mitigations
  • we have deployed Mythos 5 to the general public with additional safeguards as Claude Fable 5.
Deployment scope
  • available to a small number of trusted partners (beginning with those in Project Glasswing).
Limitations the lab flags
  • We do not yet measure this thoroughly, and signals of affect may be more directly tied to, and conditional on, experiential states.
What’s new
  • Noted CAIS’s contribution to the VCT CB-1 evaluation in Section 2.2.4.1.
  • Corrected a minor error in our description of the

Every italicized passage is a verbatim substring of the source document (checked deterministically after extraction). Field selection is heuristic — some quotes may lack surrounding context and some claims may be absent if no matching pattern appeared. For citation, open the source: original model card · source SHA ac781cf43bf7 · version dated Jun 28, 2026.

Extracted Evaluations(27 results)

Sort by:0/27 rows fully reproducible (0%)
BenchmarkCategoryStateScoreSetupSource
agentscored
88.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
agentscored
85.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
agentscored
85.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
codingscored
95.5
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
codingscored
95.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
medicalscored
62.7
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
1932.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
92.2
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
GraphWalks BFS 256K
otherscored
91.1
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
88.9
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
Terminal-bench 2.1
otherscored
88.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
Terminal-bench 2.1
otherscored
84.3
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
BioMysteryBench
otherscored
83.9
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
80.3
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
80.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
ArxivMath
otherscored
78.5
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
66.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
59.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
57.9
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
RiemannBench
otherscored
55.0
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
otherscored
54.9
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
Blueprint-Bench 2
otherscored
38.6
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
GDP.pdf
otherscored
29.8
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
FrontierCode
otherscored
29.3
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
CritPt
otherscored
28.6
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
Automation Bench
otherscored
17.4
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported
Legal Agent Benchmark
otherscored
13.3
missing: shot countmissing: methodmissing: languagemissing: training state
self-reported