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Paul Gauthier
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4 changed files with 177 additions and 37 deletions
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@ -2184,7 +2184,7 @@
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- dirname: 2024-12-18-01-50-08--o1
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test_cases: 133
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model: openrouter/openai/o1
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model: o1
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edit_format: diff
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commit_hash: 074c636-dirty
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pass_rate_1: 65.4
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155
aider/website/_data/polyglot_leaderboard.yml
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155
aider/website/_data/polyglot_leaderboard.yml
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@ -0,0 +1,155 @@
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- dirname: 2024-12-21-18-41-18--polyglot-gpt-4o-mini
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test_cases: 225
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model: gpt-4o-mini-2024-07-18
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edit_format: whole
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commit_hash: a755079-dirty
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pass_rate_1: 0.9
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pass_rate_2: 3.6
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pass_num_1: 2
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pass_num_2: 8
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percent_cases_well_formed: 100.0
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error_outputs: 0
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num_malformed_responses: 0
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num_with_malformed_responses: 0
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user_asks: 36
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lazy_comments: 0
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syntax_errors: 0
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indentation_errors: 0
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exhausted_context_windows: 0
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test_timeouts: 3
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total_tests: 225
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command: aider --model gpt-4o-mini-2024-07-18
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date: 2024-12-21
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versions: 0.69.2.dev
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seconds_per_case: 17.3
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total_cost: 0.3236
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- dirname: 2024-12-21-18-44-28--polyglot-sonnet
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test_cases: 225
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model: claude-3-5-sonnet-20241022
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edit_format: diff
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commit_hash: a755079-dirty
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pass_rate_1: 18.7
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pass_rate_2: 45.3
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pass_num_1: 42
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pass_num_2: 102
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percent_cases_well_formed: 100.0
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error_outputs: 1
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num_malformed_responses: 0
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num_with_malformed_responses: 0
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user_asks: 14
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lazy_comments: 0
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syntax_errors: 0
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indentation_errors: 0
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exhausted_context_windows: 1
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test_timeouts: 12
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total_tests: 225
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command: aider --model claude-3-5-sonnet-20241022
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date: 2024-12-21
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versions: 0.69.2.dev
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seconds_per_case: 30.8
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total_cost: 13.4847
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- dirname: 2024-12-21-18-52-34--polyglot-gpt-4o-diff
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test_cases: 225
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model: gpt-4o-2024-11-20
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edit_format: diff
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commit_hash: a755079-dirty
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pass_rate_1: 4.9
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pass_rate_2: 15.1
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pass_num_1: 11
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pass_num_2: 34
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percent_cases_well_formed: 96.0
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error_outputs: 12
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num_malformed_responses: 11
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num_with_malformed_responses: 9
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user_asks: 34
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lazy_comments: 0
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syntax_errors: 0
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indentation_errors: 0
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exhausted_context_windows: 1
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test_timeouts: 19
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total_tests: 225
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command: aider --model gpt-4o-2024-11-20
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date: 2024-12-21
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versions: 0.69.2.dev
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seconds_per_case: 22.2
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total_cost: 7.1835
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- dirname: 2024-12-21-19-23-03--polyglot-o1-hard-diff
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test_cases: 224
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model: o1-2024-12-17
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edit_format: diff
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commit_hash: a755079-dirty
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pass_rate_1: 23.7
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pass_rate_2: 61.7
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pass_num_1: 53
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pass_num_2: 139
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percent_cases_well_formed: 91.5
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error_outputs: 25
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num_malformed_responses: 24
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num_with_malformed_responses: 19
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user_asks: 16
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lazy_comments: 0
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syntax_errors: 0
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indentation_errors: 0
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exhausted_context_windows: 0
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test_timeouts: 2
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total_tests: 225
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command: aider --model openrouter/openai/o1
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date: 2024-12-21
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versions: 0.69.2.dev
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seconds_per_case: 133.2
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total_cost: 0.0000
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- dirname: 2024-12-21-20-56-21--polyglot-deepseek-diff
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test_cases: 225
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model: deepseek-chat
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edit_format: diff
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commit_hash: a755079-dirty
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pass_rate_1: 5.3
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pass_rate_2: 17.8
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pass_num_1: 12
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pass_num_2: 40
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percent_cases_well_formed: 92.9
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error_outputs: 42
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num_malformed_responses: 37
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num_with_malformed_responses: 16
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user_asks: 23
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lazy_comments: 0
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syntax_errors: 0
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indentation_errors: 0
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exhausted_context_windows: 5
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test_timeouts: 5
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total_tests: 225
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command: aider --model deepseek/deepseek-chat
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date: 2024-12-21
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versions: 0.69.2.dev
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seconds_per_case: 184.0
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total_cost: 0.5101
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- dirname: 2024-12-21-21-46-27--polyglot-haiku-diff
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test_cases: 225
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model: claude-3-5-haiku-20241022
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edit_format: diff
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commit_hash: a755079-dirty
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pass_rate_1: 7.1
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pass_rate_2: 28.0
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pass_num_1: 16
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pass_num_2: 63
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percent_cases_well_formed: 91.1
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error_outputs: 31
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num_malformed_responses: 30
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num_with_malformed_responses: 20
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user_asks: 13
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lazy_comments: 0
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syntax_errors: 0
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indentation_errors: 0
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exhausted_context_windows: 1
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test_timeouts: 9
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total_tests: 225
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command: aider --model claude-3-5-haiku-20241022
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date: 2024-12-21
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versions: 0.69.2.dev
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seconds_per_case: 31.8
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total_cost: 6.0583
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@ -18,11 +18,27 @@ The leaderboards report the results from a number of popular LLMs.
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While [aider can connect to almost any LLM](/docs/llms.html),
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it works best with models that score well on the benchmarks.
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## Code editing leaderboard
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[Aider's code editing benchmark](/docs/benchmarks.html#the-benchmark) asks the LLM to edit python source files to complete 133 small coding exercises
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{: .note :}
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The old
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[aider code editing leaderboard](edit.html)
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has been replaced by this
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new, much more challenging
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[polyglot leaderboard]().
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## Polyglot leaderboard
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[Aider's polyglot benchmark](/docs/benchmarks.html#the-benchmark)
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asks the LLM to edit source files to complete 225 coding exercises
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from Exercism.
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This measures the LLM's coding ability, and whether it can
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It contains exercises in many popular programming languages:
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C++, Go, Java, JavaScript, Python and Rust.
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The 225 exercises were purposely selected to be the *hardest*
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that Exercism offered in those languages, to provide
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a strong coding challenge to LLMs.
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This benchmark measures the LLM's coding ability in popular languages,
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and whether it can
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write new code that integrates into existing code.
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The model also has to successfully apply all its changes to the source file without human intervention.
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@ -39,7 +55,7 @@ The model also has to successfully apply all its changes to the source file with
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</tr>
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</thead>
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<tbody>
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{% assign edit_sorted = site.data.edit_leaderboard | sort: 'pass_rate_2' | reverse %}
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{% assign edit_sorted = site.data.polyglot_leaderboard | sort: 'pass_rate_2' | reverse %}
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{% for row in edit_sorted %}
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<tr style="border-bottom: 1px solid #ddd;">
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<td style="padding: 8px;">{{ row.model }}</td>
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</style>
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## Notes on benchmarking results
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The key benchmarking results are:
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- **Percent completed correctly** - Measures what percentage of the coding tasks that the LLM completed successfully. To complete a task, the LLM must solve the programming assignment *and* edit the code to implement that solution.
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- **Percent using correct edit format** - Measures the percent of coding tasks where the LLM complied with the edit format specified in the system prompt. If the LLM makes edit mistakes, aider will give it feedback and ask for a fixed copy of the edit. The best models can reliably conform to the edit format, without making errors.
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## Notes on the edit format
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Aider uses different "edit formats" to collect code edits from different LLMs.
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The "whole" format is the easiest for an LLM to use, but it uses a lot of tokens
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and may limit how large a file can be edited.
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Models which can use one of the diff formats are much more efficient,
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using far fewer tokens.
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Models that use a diff-like format are able to
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edit larger files with less cost and without hitting token limits.
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Aider is configured to use the best edit format for the popular OpenAI and Anthropic models
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and the [other models recommended on the LLM page](/docs/llms.html).
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For lesser known models aider will default to using the "whole" editing format
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since it is the easiest format for an LLM to use.
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## Contributing benchmark results
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Contributions of benchmark results are welcome!
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See the
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[benchmark README](https://github.com/Aider-AI/aider/blob/main/benchmark/README.md)
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for information on running aider's code editing benchmarks.
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Submit results by opening a PR with edits to the
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[benchmark results data files](https://github.com/Aider-AI/aider/blob/main/aider/website/_data/).
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<p class="post-date">
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@ -6,7 +6,7 @@ description: Quantitative benchmark of LLM code refactoring skill.
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---
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## Aider refactoring leaderboard
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## Refactoring leaderboard
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[Aider's refactoring benchmark](https://github.com/Aider-AI/refactor-benchmark) asks the LLM to refactor 89 large methods from large python classes. This is a more challenging benchmark, which tests the model's ability to output long chunks of code without skipping sections or making mistakes. It was developed to provoke and measure [GPT-4 Turbo's "lazy coding" habit](/2023/12/21/unified-diffs.html).
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