[whatmodel.sh](../../README.md) / Claude Sonnet 4.6
# Claude Sonnet 4.6
Anthropic · released 2026-02 · closed weights
**score 71.0** ±0.6 · #68 of 732 · from 44 benchmark results across 24 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Claude Sonnet 4.6 among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█▄▅▅▄●▂▁ #47 of 313 37% 12
coding ▁▁▁▃▅▇█▇▅●▃▁ #50 of 469 28% 5
chat & writing ▁▁▁▃▆▄▆█▆▇●▃ #33 of 402* 3.7% 1
math ▁▁▃▅█▆▄●▄▂▁▁ #151 of 431 2.9% 3
vision & documents ▁▁▂▂▁▃▄▂▆▇●▄ #32 of 153 11% 7
web search ▁▁▁▅▄●▃▄·▁·▁ #36 of 84 4.9% 3
agent tasks · #47 of 313 · 37% of its score
Beats [Gemini 3.1 Pro (Preview)](gemini-3-1-pro.md), [Qwen3.8-Omni-Flash](qwen3-8-omni-flash.md), [Qwen3.8-Flash-Next](qwen3-8-flash-next.md) here, though they rank higher overall.
test result vs the others in its run difficulty counts why
SWE-bench Pro (split unspecified)… 58.1% ●█·▄·▄██···▄ beats 0/9 very hard · avg 7.4% 10% sharp · at its level
SWE-bench Verified 75.2% ▁··▁·▁▂▁▄●▄▁ beats 18/29 hard · avg 19% 7.1% sharp · at its level
Terminal-Bench 2.1 (maker) 67.0% ▁·▁·▁▁▄▃▆●▅█ beats 35/63 hard · avg 19% 3.2% sharp · at its level
OSWorld-Verified (maker) 78.5% █▃·▂▅▂▃▂▅●▆▆ beats 18/27 hard · avg 28% 3.1% at its level
Agents' Last Exam overall full-pa… 9.9% ▄···█▄●▄█▄·█ beats 4/10 very hard · avg 1.9% 2.5% typical
Humanity's Last Exam with tools (… 46.8% ▁······●·▄·█ beats 1/10 very hard · avg 14% 2.5% at its level
Toolathlon (Tool Decathlon) (make… 49.4% ●···█··█·███ beats 0/5 hard · avg 16% 2.0% at its level
Vibe Code Bench (test split, 50 w… 51.5% ▃··▃·▃██▃▃●█ beats 11/14 very hard · avg 2.8% 1.6% sharp · at its level · noisy
Thinkingbox-bench pass@1 (507 sta… 59.2% ▅··▃·▃·█▃▅●█ beats 12/15 very hard · avg 5.1% 1.6% sharp · at its level
τ²-bench Telecom (maker) 97.9% ▁·▅█▆▅▂▃▃▂●▁ beats 80/89 hard · avg 30% 1.2% sharp · noisy
Legal Research Bench (agentic, al… 38.5% ▄█··▄▄▄██·●█ beats 10/12 very hard · avg 6.3% 1.1% at its level
KlinikeBench strict pass@1 (333 i… 8.4% ▁▁·▁▁▁▁●▃█▅█ beats 9/27 very hard · avg 2.4% 0.9% typical
coding · #50 of 469 · 28% of its score
Beats [GPT-5.5](gpt-5-5.md), [GPT-5.4](gpt-5-4.md), [Gemini 3.1 Pro (Preview)](gemini-3-1-pro.md) here, though they rank higher overall.
test result vs the others in its run difficulty counts why
SWE-bench Pro (split unspecified)… 58.1% ●█·▄·▄██···▄ beats 0/9 very hard · avg 7.4% 10% sharp · at its level
SWE-bench Verified 75.2% ▁··▁·▁▂▁▄●▄▁ beats 18/29 hard · avg 19% 7.1% sharp · at its level
Arena WebDev (Code Arena) 1522.7 ▁▁▃▂▅█▃●▅▅▁▂ beats 80/129 avg 981 6.6% sharp
VisEditBench strict pass rate (1,… 74.5% ▄··█·▄··▄█·● beats 7/7 hard · avg 33% 1.8% at its level
Vibe Code Bench (test split, 50 w… 51.5% ▃··▃·▃██▃▃●█ beats 11/14 very hard · avg 2.8% 1.6% sharp · at its level · noisy
chat & writing · #33 of 402 · 3.7% of its score
Beats [GPT-6 Sol](gpt-6-sol.md), [GPT-5.6 Terra](gpt-5-6-terra.md), [MiMo-V2.6-Flash (309B-A15B)](mimo-v2-6-flash.md) here, though they rank higher overall. Trails [Gemini 3 Flash (Preview)](gemini-3-flash-preview.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1472.0 ▁▁▁▂▃▃▃▆▆▇●▃ beats 348/385 avg 1260 3.7% blunt
math · #151 of 431 · 2.9% of its score
Trails [Nemotron 3 Nano 30B-A3B](nemotron-3-nano-30b-a3b.md), [Qwen3-VL 8B Thinking](qwen3-vl-8b-thinking.md), [Olmo 3 32B Think](olmo-3-32b-think.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
USAMO 2026 (maker) 55.0% ●·██······██ beats 0/4 hard · avg 19% 1.1% sharp · at its level · noisy
OTIS mock AIME 2024–2025 71.1% ▃▃▄▃▃▃▇●█▃▂▅ beats 103/197 very hard · avg 7.2% 1.0% sharp · noisy
MathConstraint full release, no t… 18.5% ▄··●▄·▄▄█▄·▄ beats 1/8 very hard · avg 11% 0.9% at its level
vision & documents · #32 of 153 · 11% of its score
Beats [Claude Sonnet 5.5](claude-sonnet-5-5.md), [GPT-6 Sol](gpt-6-sol.md), [MiMo-V2.6-Pro](mimo-v2-6-pro.md) here, though they rank higher overall. Trails [Qwen3.6 Plus](qwen3-6-plus.md), [Qwen3.7 Plus](qwen3-7-plus.md), [Gemini 3 Flash (Preview)](gemini-3-flash-preview.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
CharXiv (reasoning questions) (ma… 71.6% ██●··█·██··█ beats 2/6 hard · avg 28% 2.6% at its level
Arena vision (style controlled) 1275.1 ▁▁▂▂▂▂▃▄▅▅█● beats 126/152 avg 1061 2.5% blunt
VisEditBench strict pass rate (1,… 74.5% ▄··█·▄··▄█·● beats 7/7 hard · avg 33% 1.8% at its level
Arena document (style controlled) 1477.7 ▁▁▃▃▄▃▇█▅●▄▅ beats 28/37 avg 1331 1.3% blunt
SciDocBench scientific-document w… 49.6% ▃▃···●▃▅▃·▃▅ beats 2/11 hard · avg 25% 1.3% blunt · at its level
BEAR-Bench (bilingual RU/EN enter… 62.7% ▃▃·▅·▃·█·●▅▅ beats 10/14 hard · avg 24% 1.2% at its level
SpaceCast-Bench predictive spatia… 36.0% ▃·▅●▅▃··▅··█ beats 3/11 very hard · avg 33% 0.4% at its level · noisy
web search · #36 of 84 · 4.9% of its score
Beats [Gemini 3.1 Pro (Preview)](gemini-3-1-pro.md), [GPT-5.3-Codex](gpt-5-3-codex.md), [Gemini 3.5 Flash](gemini-3-5-flash.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), [Llama 4 Scout (109B-A17B)](llama-4-scout.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Humanity's Last Exam with tools (… 46.8% ▁······●·▄·█ beats 1/10 very hard · avg 14% 2.5% at its level
Arena search systems (style contr… 1201.9 ▁·▁▁▂▂▂█●▃▂▂ beats 22/36 avg 1069 1.3% blunt
Legal Research Bench (agentic, al… 38.5% ▄█··▄▄▄██·●█ beats 10/12 very hard · avg 6.3% 1.1% at its level
other tests (20)
test result vs the others in its run difficulty counts why
Humanity's Last Exam (maker) 34.6% ▂·····●·▄▂█▄ beats 1/10 very hard · avg 5.9% 4.0% at its level
Mystery Game Puzzles (Epoch) 14.0% █··▂●▇▄█▂▄▂▁ beats 20/77 very hard · avg 9.4% 3.8% sharp · noisy
GPQA Diamond 78.8% ▁▁▁▁▂▄▆▄▅●█▅ beats 123/211 hard · avg 39% 3.6% sharp
KINA (Knowledge Index of Noah's A… 30.0% ▁▁▂▁▃▄█●▄▅▂▃ beats 20/39 very hard · avg 21% 3.0% at its level
Chess Puzzles (Epoch) 3.0% ●▁▁▁▁▂▃▃▃▂▁▁ beats 17/137 very hard · avg 5.8% 2.7% sharp · noisy
DSEffi-Bench Pass (1,000 data-sci… 59.7% ▅··▃▅·█·▃█●▃ beats 12/15 hard · avg 23% 2.7% at its level
EQ-Bench 3 (emotional intelligenc… 1384.2 ▁·▂▁▄▅▅▃█▄●▁ beats 61/62 avg 1034 2.3% typical
KOPA-Bench (pass@1) 46.6% ▄·█··▄··█▄·● beats 8/8 very hard · avg 14% 2.1% at its level
The Token Games Elo (10-model puz… 1043.0 █··●█··▄·▄·▄ beats 2/7 avg 822 2.0% typical
AgentWorldBench (open-ended, over… 56.0% ▄▄··▄▄·▄█●██ beats 7/11 hard · avg 26% 1.9% blunt · at its level
LongSocialBench (full-context, 4-… 44.3% ▆▂·▄█·●▂·▄▄▂ beats 10/16 very hard · avg 36% 1.5% blunt · at its level
SimpleQA Verified 32.8% ▁▁▃▂▃▃●▆█▄▂▅ beats 23/81 very hard · avg 8.0% 1.4% at its level
Legal Research Bench (single-shot… 7.3% ▃▃█▃·▅···█●▃ beats 11/12 very hard · avg 0.8% 1.3% too hard for it
SkillsBench 87-task subset 54.4% ▄··▄▄▄···█·● beats 7/7 very hard · avg 9.1% 1.1% at its level
WideSearch corrected dataset 79.5% ▃······▃▃▃█● beats 7/7 hard · avg 22% 1.0% at its level · noisy
BFCL multi-turn (version not stat… 60.1% ▄▄···▄·▄█▄●▄ beats 7/8 hard · avg 26% 0.9% at its level
SCHEDBench subset, solver-mediate… 35.0% ▄·▄·····●··█ beats 2/4 very hard · avg 5.4% 0.9% at its level · noisy
DiagnosticIQ industrial maintenan… 64.8% ▁··▃▁▁▁▅█●▁▅ beats 16/24 hard · avg 51% 0.8% blunt · at its level
Vectara hallucination leaderboard… 89.4% ▁▂▁▂▅●▂▃▄▃▁▁ beats 38/98 very easy · avg 90% 0.0% blunt
BrowseComp single-agent with cont… 74.0% █··········● beats 1/1 — not counted yet: no other model in the …
source results share of the score
Anthropic system cards and model announ… 9 30% ▇▇▇▇
Epoch AI 6 20% ▇▇
LMArena leaderboard dataset 5 16% ▇▇
Multi-Step Tool-Calling over Korean Ope… 2 3% ▇
Knowledge Index of Noah's Ark 1 3% ▇
DSEffi-Bench: Demystifying Large Langua… 1 3% ▇
Agents' Last Exam 1 3% ▇
Legal Research Bench 2 2% ▇
EQ-Bench 3 canonical leaderboard results 1 2% ▇
inclusionAI/Ling-3.0-flash model card 2 2% ▇
The Token Games: Evaluating Language Mo… 1 2% ▇
Qwen/Qwen-AgentWorld-35B-A3B model card 1 2% ▇
VisEditBench: Can Vision-Language Model… 1 2% ▇
Vibe Code Bench 1 2% ▇
One Success Isn't Reliability: Thinking… 1 2% ▇
LongSocialBench: Do Long-Context LLMs U… 1 1% ▇
SciDocBench: A Workflow-Centered Benchm… 1 1% ▇
BEAR-Bench: A Bilingual Enterprise and … 1 1% ▇
KlinikeBench: Evaluating Language Model… 1 1% ▇
Improving Natural-Language Combinatoria… 1 1% ▇
MathConstraint: Automated Generation of… 1 1% ▇
DiagnosticIQ: A Benchmark for LLM-Based… 1 1% ▇
SpaceCast-Bench: Evaluating Predictive … 1 0% ▇
Vectara hallucination leaderboard 1 0% ▇
prior: pull toward the middle 0% ▇
weighted average = 71.0
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/)) · Multi-Step Tool-Calling over Korean Open Public APIs: A Benchmark and a Data-Synthesis Recipe ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Knowledge Index of Noah's Ark ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · DSEffi-Bench: Demystifying Large Language Models' Capability in Efficient Data Science Code Generation ([CC BY 4.0](../../licenses/paper-2608.30248v1-CC-BY-4.0.txt)) · Agents' Last Exam ([CC BY 4.0](../../licenses/paper-2606.05405v2-CC-BY-4.0.txt)) · Legal Research Bench ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · EQ-Bench 3 canonical leaderboard results ([MIT](../../licenses/eqbench3-MIT.txt)) · inclusionAI/Ling-3.0-flash model card ([MIT](../../licenses/cards-final-NOTICE.txt)) · The Token Games: Evaluating Language Model Reasoning with Puzzle Duels ([CC BY-SA 4.0](../../licenses/paper-2602.17831v2-CC-BY-SA-4.0.txt)) · Qwen/Qwen-AgentWorld-35B-A3B model card ([Apache-2.0](https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B/blob/60d2b0434a53d2e62a7c00a489586815d94ebffb/README.md)) · VisEditBench: Can Vision-Language Models Edit Visualization Code from Multimodal Feedback? ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Vibe Code Bench ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · One Success Isn't Reliability: Thinkingbox ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · LongSocialBench: Do Long-Context LLMs Understand Online Discussion Threads? ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · SciDocBench: A Workflow-Centered Benchmark and Data Pipeline for Scientific Document Understanding ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · BEAR-Bench: A Bilingual Enterprise and Academic Reasoning Benchmark for Multimodal Models ([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/)) · Improving Natural-Language Combinatorial-Optimization Accuracy in Resource-Constrained Language Models via Formal Abstractions ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · MathConstraint: Automated Generation of Verified Combinatorial Reasoning Instances for LLMs ([CC BY 4.0](../../licenses/paper-2605.08498v1-CC-BY-4.0.txt)) · DiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rules ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · SpaceCast-Bench: Evaluating Predictive Spatial Reasoning in Vision-Language Models ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0))
Not counted (1)
source test score why
inclusionAI/Ling-3.0-… BrowseComp single-agent with … 74.0% too few models have it yet