[whatmodel.sh](../../README.md) / Claude Opus 5
# Claude Opus 5
Anthropic · released 2026-07 · closed weights
**score 80.5** ±0.5 · #10 of 732 · from 52 benchmark results across 17 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Claude Opus 5 among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄▅▅▄▄●▁ #10 of 313 36% 18
coding ▁▁▁▃▅▇█▇▅▄▃● #8 of 469 18% 8
chat & writing ▁▁▁▃▆▄▆█▆▇▇● #12 of 402* 2.4% 1
math ▁▁▃▅█▆▄█▄▂●▁ #13 of 431 20% 6
vision & documents ▁▁▂▂▁▃▄▂▆▇█● #7 of 153 3.3% 4
web search ▁▁▁▅▄█●▄·▁·▁ #17 of 84 3.2% 3
agent tasks · #10 of 313 · 36% of its score
test result vs the others in its run difficulty counts why
Terminal-Bench 4.0 51.8% █▅▅▅▅·▅▃▃●▅▅ beats 16/20 very hard · avg 0.7% 6.3% sharp · at its level · several runs
Arena Agent (October 2026 aggrega… 0.0757 IPS ▁▁▁▃▃▂█▁●▂▁▁ beats 48/59 avg -0.379 IPS 6.2% sharp
SWE-bench Pro (split unspecified)… 79.2% ▄█·▄·▄●█···▄ beats 5/9 very hard · avg 7.4% 4.6% sharp
SWE-bench Multilingual (maker) 89.5% ▃··▃·▅▃▃●··▃ beats 7/9 hard · avg 31% 2.1% typical
GameLogicBench solve rate (72 God… 52.8% █▄·█·▄·██▄·● beats 11/11 very hard · avg 5.1% 1.8% at its level
τ³-bench banking_knowledge (v1.0.… 48.7% ▃▃▂▃·▆▃▂█▅●▂ beats 24/25 very hard · avg 4.3% 1.8% at its level
SWE-bench Verified (maker) 96.0% ▁▁▁▁▁▁▂▄█▆▁● beats 138/138 hard · avg 28% 1.8% sharp · maxed out
E2E-SWE (build a working codebase… 67.7% ▃··▅··▃█▃▅▃● beats 12/12 very hard · avg 3.7% 1.5% sharp · at its level
Humanity's Last Exam with tools (… 63.6% ▁······▁·▄·● beats 6/10 very hard · avg 14% 1.5% at its level
Chartography with tools (maker) 83.4% ▃········▃●█ beats 2/7 very hard · avg 6.5% 1.3% sharp
DeepSWE v1.1 (resolved) (maker) 68.8% █·····█●██·█ beats 2/5 hard · avg 19% 1.2% at its level
Video2World V2WScore (coding agen… 41.6% █··▄█·▄····● beats 6/6 very hard · avg 7.3% 1.1% at its level
Thinkingbox-bench pass@1 (507 sta… 66.5% ▅··▃·▃·█▃▅█● beats 15/15 very hard · avg 5.1% 1.0% sharp · at its level
KlinikeBench strict pass@1 (333 i… 29.4% ▁▁·▁▁▁▁▅▃█▅● beats 27/27 very hard · avg 2.4% 0.9% typical
BrowseComp with context managemen… 90.8% ▄·▄▂·█▂·▆▄·● beats 15/15 medium · avg 47% 0.8% typical
OSWorld 2.1 (partial score) (make… 74.0% ●·········██ beats 0/2 hard · avg 29% 0.6% small run
Toolathlon-Verified (maker) 80.6% ▃·····█···▃● beats 5/5 medium · avg 37% 0.6% blunt
OSWorld 2.0, 2026.08.08 release (… 75.4% █····●·····█ beats 1/2 hard · avg 28% 0.6% small run
coding · #8 of 469 · 18% of its score
Beats [GPT-6.1 Terra](gpt-6-1-terra.md), [Gemini 4 Argon](gemini-4-argon.md) here, though they rank higher overall.
test result vs the others in its run difficulty counts why
SWE-bench Pro (split unspecified)… 79.2% ▄█·▄·▄●█···▄ beats 5/9 very hard · avg 7.4% 4.6% sharp
Arena WebDev (Code Arena) 1690.5 ▁▁▃▂▅█▃▆▅▅●▂ beats 121/129 avg 981 4.3% sharp
SWE-bench Multilingual (maker) 89.5% ▃··▃·▅▃▃●··▃ beats 7/9 hard · avg 31% 2.1% typical
GameLogicBench solve rate (72 God… 52.8% █▄·█·▄·██▄·● beats 11/11 very hard · avg 5.1% 1.8% at its level
SWE-bench Verified (maker) 96.0% ▁▁▁▁▁▁▂▄█▆▁● beats 138/138 hard · avg 28% 1.8% sharp · maxed out
E2E-SWE (build a working codebase… 67.7% ▃··▅··▃█▃▅▃● beats 12/12 very hard · avg 3.7% 1.5% sharp · at its level
DeepSWE v1.1 (resolved) (maker) 68.8% █·····█●██·█ beats 2/5 hard · avg 19% 1.2% at its level
Luau Leetcode fully solved (Torpe… 82.2% ▁▁▁▁·▁▂▃▅▃●▇ beats 38/49 hard · avg 17% 1.1% sharp
chat & writing · #12 of 402 · 2.4% of its score
Beats [GPT-6 Astra](gpt-6-astra.md), [GPT-6.1 Sol](gpt-6-1-sol.md), [Claude Sonnet 5.5](claude-sonnet-5-5.md) here, though they rank higher overall. Trails [Muse Spark 1.2](muse-spark-1-2.md), [Claude Opus 4.6](claude-opus-4-6.md), [Claude Opus 4.7](claude-opus-4-7.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1490.5 ▁▁▁▂▃▃▃▆▆▇█● beats 374/385 avg 1260 2.4% blunt
math · #13 of 431 · 20% of its score
Trails [GPT-5.5](gpt-5-5.md), [Claude Mythos Preview (limited preview)](claude-mythos-preview.md), [Claude Fable 5](claude-fable-5.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
FrontierMath tier 4 v2 73.2% ▁▂▁▂█▅▂●▂▁▁▁ beats 57/67 very hard · avg 0.1% 8.1% sharp
FrontierMath tiers 1–3 v2 85.6% ▂··▁▁▃▄▄█▆●▃ beats 75/86 very hard · avg 1.2% 5.1% sharp
MathArena ArXivMath June 2026 (48… 82.6% ▂···▄·██▆●▄▂ beats 14/19 very hard · avg 5.1% 3.5% sharp
MathArena ArXivLean June 2026 (46… 32.6% ▄····▄▄██●·▄ beats 7/9 very hard · avg 0.9% 1.9% sharp · at its level
MathArena BrokenArXiv June 2026 (… 90.7% ▄··█▂▂▂▆▄··● beats 14/14 very hard · avg 1.3% 1.3% sharp · at its level · noisy
OTIS mock AIME 2024–2025 98.9% ▃▃▄▃▃▃▇▇█▃▂● beats 180/197 very hard · avg 7.2% 0.1% sharp · maxed out · noisy
vision & documents · #7 of 153 · 3.3% of its score
Beats [GPT-6 Astra](gpt-6-astra.md), [Claude Opus 5.5](claude-opus-5-5.md), [GPT-6.1 Sol](gpt-6-1-sol.md) here, though they rank higher overall. Trails [Claude Opus 4.7](claude-opus-4-7.md), [Gemini 3.7 Flash](gemini-3-7-flash.md), [Gemini 3.8 Flash](gemini-3-8-flash.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena vision (style controlled) 1287.9 ▁▁▂▂▂▂▃▄▅▅█● beats 140/152 avg 1061 1.6% blunt
Arena document (style controlled) 1489.7 ▁▁▃▃▄▃▇█▅▇●▅ beats 33/37 avg 1331 0.8% blunt
SciDocBench scientific-document w… 62.6% ▃▃···█▃▅▃·▃● beats 11/11 hard · avg 25% 0.8% blunt · at its level
PureDocBench document parsing (Av… 77.1% ▂·▁·▂▂▅█·▁●▂ beats 19/22 medium · avg 62% 0.0% blunt · at its level
web search · #17 of 84 · 3.2% of its score
Beats [Claude Fable 5.1](claude-fable-5-1.md), [Claude Sonnet 5.5](claude-sonnet-5-5.md) here, though they rank higher overall. Trails [GPT-4o mini (2024-07-18)](gpt-4o-mini-2024-07-18.md), [Mistral Small 3.1 24B (2503)](mistral-small-3-1.md), [GPT-4o (2024-08-06)](gpt-4o-2024-08-06.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Humanity's Last Exam with tools (… 63.6% ▁······▁·▄·● beats 6/10 very hard · avg 14% 1.5% at its level
Arena search systems (style contr… 1214.4 ▁·▁▁▂▂▂█▆●▂▂ beats 28/36 avg 1069 0.9% blunt
BrowseComp with context managemen… 90.8% ▄·▄▂·█▂·▆▄·● beats 15/15 medium · avg 47% 0.8% typical
other tests (19)
test result vs the others in its run difficulty counts why
EBR-bench (Epoch) 45.7% ▄▂·▆█▂█▆●▆·▆ beats 19/25 very hard · avg 0.3% 6.2% sharp · at its level
Mystery Game Puzzles (Epoch) 59.0% █··▂▃▇▄█▂●▂▁ beats 72/77 very hard · avg 9.4% 5.2% sharp · at its level · noisy
Furniture Assembly (Epoch) 60.8% █▆▆▆▆▂▆●▂▂▂▅ beats 26/32 very hard · avg 1.2% 4.3% sharp · at its level
Humanity's Last Exam (maker) 56.6% ▂·····▂·▄▂●▄ beats 5/10 very hard · avg 5.9% 2.8% at its level
Chess Puzzles (Epoch) 42.0% █▁▁▁▁▂▃▃▃●▁▁ beats 123/137 very hard · avg 5.8% 2.6% sharp · at its level · noisy
KMMLU-HARD (Daekeun Kim, zero-sho… 88.4% █···▁▁▁▂▃·▆● beats 23/23 very hard · avg 29% 1.7% sharp
Global-MMLU (maker) 92.5% ▄▄····▄●··▄█ beats 3/6 medium · avg 64% 1.0% typical
KoBALT-700 (Daekeun Kim) 88.1% ▄▄█·····▄··● beats 5/5 hard · avg 39% 0.9% typical
SimpleQA Verified 59.9% ▁▁▃▂▃▃▆▆█●▂▅ beats 66/81 very hard · avg 8.0% 0.9% at its level
CLIcK Korean (Daekeun Kim) 95.8% ▆▄▄▄█▄▂·▄█·● beats 23/23 medium · avg 56% 0.9% maxed out
Icelandic LLM Leaderboard average… 68.6% ▁▁▃▂▂▄▁▃▄▄▄● beats 35/38 very hard · avg 14% 0.8% at its level
AutomationBench public set (Zapie… 50.3% ▄······▄█··● beats 4/4 very hard · avg 11% 0.8% at its level
GPQA Diamond 93.9% ▁▁▁▁▂▄▆▄▅▇█● beats 201/211 hard · avg 39% 0.7% sharp · maxed out
KMMLU-Pro (Daekeun Kim) 95.6% ▄·▄█·····▄·● beats 5/5 medium · avg 43% 0.7% typical
HAE-RAE 1.0 (Daekeun Kim) 95.8% ▄▄▄▂▂█▂▄▂█▂● beats 22/22 medium · avg 61% 0.6% maxed out
HealthBench (maker) 67.1% █·▄·····▄●▄▄ beats 4/6 hard · avg 30% 0.6% blunt · at its level
MuSR Korean (Daekeun Kim) 86.5% █·····███·█● beats 5/5 medium · avg 45% 0.5% typical
HealthBench Professional (maker) 59.8% ▂·▂··▂▂●█▄▂▄ beats 4/13 hard · avg 20% 0.5% blunt · at its level · small run
RobloxQA v2.0 multiple choice (To… 97.5% ▁▁▃▁█▄▃▃▆●▂▂ beats 42/49 easy · avg 77% 0.4% maxed out
source results share of the score
Epoch AI 9 33% ▇▇▇▇
Anthropic system cards and model announ… 18 23% ▇▇▇
LMArena leaderboard dataset 6 16% ▇▇
MathArena ArXivMath / BrokenArXiv / ArX… 3 7% ▇
Daekeun Kim Korean LLM benchmark runs 6 5% ▇
Terminal-Bench 4.0 official leaderboard… 1 3% ▇
GameLogicBench: Evaluating Coding Agent… 1 2% ▇
τ²/τ³-bench leaderboard: Sierra's own e… 1 2% ▇
E2E-SWE: Benchmarking LLMs on Building … 1 1% ▇
Roblox LLM Leaderboard 2 1% ▇
Video2World: Benchmarking Coding Agents… 1 1% ▇
One Success Isn't Reliability: Thinking… 1 1% ▇
KlinikeBench: Evaluating Language Model… 1 1% ▇
Miðeind Icelandic LLM Leaderboard 1 1% ▇
Zapier AutomationBench README: public-s… 1 1% ▇
SciDocBench: A Workflow-Centered Benchm… 1 1% ▇
How Far Is Document Parsing from Solved… 1 0% ▇
prior: pull toward the middle 0% ▇
weighted average = 80.5
Licences: Epoch AI ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · MathArena ArXivMath / BrokenArXiv / ArXivLean model-output datasets ([CC BY-SA 4.0](../../licenses/matharena-sharealike-NOTICE.txt)) · Daekeun Kim Korean LLM benchmark runs ([MIT](../../licenses/korean-personal-benchmark-runs-MIT.txt)) · Terminal-Bench 4.0 official leaderboard submissions ([Apache-2.0](../../licenses/terminal-bench-leaderboard-submissions-Apache-2.0.txt)) · GameLogicBench: Evaluating Coding Agents on Runtime Game Logic with Tick-Level State Assertions ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · τ²/τ³-bench leaderboard: Sierra's own evaluation runs ([MIT](https://opensource.org/license/mit)) · E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Roblox LLM Leaderboard ([MIT](../../licenses/roblox-llm-leaderboard-MIT.txt)) · Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos ([CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)) · One Success Isn't Reliability: Thinkingbox ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracy ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Miðeind Icelandic LLM Leaderboard ([CC BY 4.0](../../licenses/mideind-icelandic-llm-leaderboard-CC-BY-4.0.txt)) · Zapier AutomationBench README: public-set pass rates ([MIT](../../licenses/zapier-automationbench-readme-MIT.txt)) · SciDocBench: A Workflow-Centered Benchmark and Data Pipeline for Scientific Document Understanding ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · How Far Is Document Parsing from Solved? PureDocBench: A Source-Traceable Benchmark across Clean ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/))
## How to run it
### Through an API
api (Anthropic) · $10.00/M blended · $5 in / $25 out per 1M tokens · [docs.anthropic.com](https://docs.anthropic.com/en/docs/about-claude/models)
[price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/anthropic/models/claude-opus-5.toml): Standard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ. · [context source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/models/anthropic/claude-opus-5.toml)
[interactive version](https://whatmodel.sh/model/claude-opus-5) · [JSON](https://whatmodel.sh/api?format=json&all=1)