Contamination MapText / LLM / Model
Claude 3.7 Sonnet
- Organisation
- Anthropic
- Family
- Claude · version 3.7
- Released
- 2025-02-24 (anthropic.com/news/claude-3-7-sonnet announcement dated Feb 24, 2025)
- Training cutoff
- 2024-11-01
Evidence
“While trained on publicly available information on the internet through November 2024, Claude 3.7 Sonnet's knowledge cut-off date is the end of October 2024.”
assets.anthropic.com · model card · Section 1.1 · retrieved 2026-10-15 - Checkpoints
- claude-3-7-sonnet-20250219
- Weights
- Closed · proprietary
- Links
- Model card
Training data disclosure: Vague
Level determined for 4% of benchmark cells.
- TestTest data seen0
- SeenSeen, split unclear0
- TrainTraining data seen0
- Related data seen0
- NoNot seen1
- ?Unknown21
“Claude 3.7 Sonnet is trained on a proprietary mix of publicly available information on the Internet, as well as non-public data from third parties, data provided by data labeling services and paid contractors, and data we generate internally.”
Other declared training data
-
publicly available information on the Internet (through November 2024) (broad web data: may contain benchmark test sets) · split: unknown
Evidence
“Claude 3.7 Sonnet is trained on a proprietary mix of publicly available information on the Internet, as well as non-public data from third parties, data provided by data labeling services and paid contractors, and data we generate internally.”
assets.anthropic.com · model card · Section 1.1 (Training Data & Process) · retrieved 2026-10-15 -
non-public data from third parties (not yet matched to a dataset) · split: unknown
Evidence
“Claude 3.7 Sonnet is trained on a proprietary mix of publicly available information on the Internet, as well as non-public data from third parties, data provided by data labeling services and paid contractors, and data we generate internally.”
assets.anthropic.com · model card · Section 1.1 (Training Data & Process) · retrieved 2026-10-15 -
data provided by data labeling services and paid contractors (not yet matched to a dataset) · split: unknown
Evidence
“Claude 3.7 Sonnet is trained on a proprietary mix of publicly available information on the Internet, as well as non-public data from third parties, data provided by data labeling services and paid contractors, and data we generate internally.”
assets.anthropic.com · model card · Section 1.1 (Training Data & Process) · retrieved 2026-10-15 -
data we generate internally (not yet matched to a dataset) · split: unknown
Evidence
“Claude 3.7 Sonnet is trained on a proprietary mix of publicly available information on the Internet, as well as non-public data from third parties, data provided by data labeling services and paid contractors, and data we generate internally.”
assets.anthropic.com · model card · Section 1.1 (Training Data & Process) · retrieved 2026-10-15
Benchmark cells
Classic LLM benchmarks
Unknown MMLU (Measuring Massive Multitask Language Understanding) · training data not disclosed in enough detail
Unknown GSM8K (Grade School Math 8K) · training data not disclosed in enough detail
Unknown MATH (Mathematics Aptitude Test of Heuristics) · training data not disclosed in enough detail
Unknown HumanEval · training data not disclosed in enough detail
Unknown ARC-Challenge (AI2 Reasoning Challenge, Challenge Set) · training data not disclosed in enough detail
Unknown HellaSwag · training data not disclosed in enough detail
Unknown TruthfulQA · training data not disclosed in enough detail
Unknown WinoGrande · training data not disclosed in enough detail
Multimodal LLM benchmarks
Unknown MMMU (Massive Multi-discipline Multimodal Understanding and Reasoning) · training data not disclosed in enough detail
Unknown MMMU-Pro · training data not disclosed in enough detail
Unknown MathVista · training data not disclosed in enough detail
Unknown ChartQA · training data not disclosed in enough detail
Unknown DocVQA · training data not disclosed in enough detail
Unknown AI2D (AI2 Diagrams) · training data not disclosed in enough detail
Unknown CharXiv · training data not disclosed in enough detail
Recent LLM benchmarks
Unknown GPQA Diamond · training data not disclosed in enough detail
Unknown MMLU-Pro · training data not disclosed in enough detail
Unknown LiveCodeBench (code generation, release_v6) · training data not disclosed in enough detail
Unknown SWE-bench Verified · training data not disclosed in enough detail
Unknown AIME 2024 · training data not disclosed in enough detail
Not seen AIME 2025 · its test items were published from 2025-02-06, after the model's stated training-data cutoff (2024-11-01)
Evidence (3)
“While trained on publicly available information on the internet through November 2024, Claude 3.7 Sonnet's knowledge cut-off date is the end of October 2024.”
“2025 AIME I problems and solutions. The test was held on Thursday, February 6, 2025.”
“This year the AIME I will take place on February 6, 2025, while the alternate AIME II will take place on February 12, 2025.”
Unknown MATH-500 · training data not disclosed in enough detail
Notes
No benchmark contamination or decontamination statement found in the system card. Accepts image input: “Claude 3.7 Sonnet can understand both text (including voice dictation) and image inputs, engaging in conversation, analysis, coding, and creative tasks.”
Sources
- Claude 3.7 Sonnet System Card · model card · retrieved 2026-10-15
- Anthropic Transparency Hub: Model Report · website · retrieved 2026-10-15
- Claude 3.7 Sonnet announcement · website · retrieved 2026-10-15