Model comparison

Claude Opus 5.5 vs DeepSeek-R1

Claude Opus 5.5 is the stronger model overall, scoring 68.6 to 42.3 on the Noometry Index. DeepSeek-R1 costs 8.8× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.

Last verified October 10, 2026. 23 shared benchmarks.

Claude Opus 5.5 Anthropic

68.6

Rank #3 Confirmed

DeepSeek-R1

DeepSeek

42.3

Rank #115 Confirmed

Summary

They share 23 benchmarks with published results for both. Claude Opus 5.5 scores higher in 9 categories and DeepSeek-R1 in 0 categories; 9 gaps are clear of the uncertainty.
The widest gap is in reasoning, where Claude Opus 5.5 leads 80.2 to 18.6.
The biggest single-benchmark swing is ARC-AGI-2: 93.3% for Claude Opus 5.5 and 1.3% for DeepSeek-R1.
DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
Claude Opus 5.5 accepts more context: 1M tokens versus 164K.

Side by side

Claude Opus 5.5 and DeepSeek-R1 specifications
	Claude Opus 5.5	DeepSeek-R1
Provider	Anthropic	DeepSeek
Noometry Index	68.6	42.3
Released	2026-09-22	2025-01-20
Weights	Proprietary	Proprietary
Context window	1M	164K
Max output	128K	64K
Input $ / M tokens	$4	$0.50
Output $ / M tokens	$20	$2.15
Results tracked	44	52

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Category by category

Coding Claude Opus 5.5 leads

Claude Opus 5.5: 71.9 (#3), DeepSeek-R1: 46.3 (#68)

Coding benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
SciCode	66.9%	35.7%
LMArena Coding	1547	1427
ALE-Bench	2,147	804.12
FrontierCode	54.6%	—
Aider Polyglot	—	71.4%
CursorBench	57.8%	—
LMArena WebDev	1813	—
FrontierSWE	62.3%	—
WeirdML	—	41.6%
LiveBench Coding	—	66.7%
MirrorCode	77.4%	—
AlgoTune	—	1.7

Agentic & Tool Use Claude Opus 5.5 leads

Claude Opus 5.5: 45.3 (#15), DeepSeek-R1: 30.7 (#75)

Agentic & Tool Use benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
APEX-Agents	73.5%	—
DeepResearch Bench	—	35.1%
BALROG	—	34.9%
GDP.pdf	30.6%	—
METR Time Horizons	—	53.8%
Vending-Bench 2	9,235	—

Reasoning Claude Opus 5.5 leads

Claude Opus 5.5: 80.2 (#3), DeepSeek-R1: 18.6 (#278)

Reasoning benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
ARC-AGI-2	93.3%	1.3%
ARC-AGI-1	98.5%	21.2%
CritPt	31.7%	1.1%
LMArena Hard Prompts	1535	1416
Epoch Capabilities Index	167.33	141.29
SimpleBench	—	40.8%
Kagi LLM Benchmark	—	69.4%
NYT Connections (extended)	88.5%	—
EBR-Bench	71.4%	—
LiveBench Reasoning	—	83.2%
Mystery Game Puzzles	71%	—
DTBench	98.9%	—
LiveBench Data Analysis	—	69.8%
LMCA	68.2%	—
ForecastBench	—	60
LiveBench	—	71.6%

Math Claude Opus 5.5 leads

Claude Opus 5.5: 91.8 (#3), DeepSeek-R1: 43.8 (#79)

Math benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
OTIS Mock AIME 2024-2025	100%	66.4%
LMArena Math	1506	1400
FrontierMath (Tiers 1-3)	91.2%	—
FrontierMath Tier 4	95%	—
ProofBench	100%	—
Omni-MATH	—	42.4%
LiveBench Math	—	80.7%
MATH Level 5	—	96.6%
FrontierMath Erdős	2.9%	—

Knowledge Claude Opus 5.5 leads

Claude Opus 5.5: 66.4 (#10), DeepSeek-R1: 44.5 (#87)

Knowledge benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
GPQA Diamond	90.6%	76.3%
LMArena Expert	1547	1394
SimpleQA Verified	72.2%	—
MMLU-Pro	—	79.3%
Confabulations	—	12.7%
Vectara Hallucination Rate	—	11.3%
GPQA (HELM)	—	66.6%

Multimodal Not comparable

Claude Opus 5.5: 57.8 (#1), DeepSeek-R1: —

Multimodal benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
LMArena Vision	1321	—
Blueprint-Bench 2	51.2%	—
Furniture Assembly	83.3%	—

Multilingual Claude Opus 5.5 leads

Claude Opus 5.5: 59.1 (#2), DeepSeek-R1: 52.4 (#85)

Multilingual benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
LMArena Non-English	1507	1412
LMArena Chinese	1588	1442
LMArena French	1514	1417
LMArena Russian	1520	1423
LMArena Spanish	1507	1411
LMArena German	—	1404
LMArena Japanese	—	1391
LMArena Korean	—	1360

Instruction Following Claude Opus 5.5 leads

Claude Opus 5.5: 80.0 (#3), DeepSeek-R1: 72.0 (#143)

Instruction Following benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
LMArena Instruction Following	1537	1382
LiveBench Instruction Following	—	80.5%
IFEval	—	78.4%

Long Context Claude Opus 5.5 leads

Claude Opus 5.5: 47.1 (#19), DeepSeek-R1: 45.4 (#36)

Long Context benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
LMArena Longer Query	1532	1391
Fiction.LiveBench	—	75%

Writing & Preference Claude Opus 5.5 leads

Claude Opus 5.5: 78.2 (#3), DeepSeek-R1: 61.4 (#88)

Writing & Preference benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-R1
LMArena Text	1515	1428
LMArena Creative Writing	1533	1405
EQ-Bench Creative Writing	2050	1500
LMArena Multi-Turn	1499	1405
Short-Story Creative Writing	—	83%
WildBench	—	82.8%
LiveBench Language	—	48.5%

Frequently asked questions

Is Claude Opus 5.5 better than DeepSeek-R1?

Which is cheaper, Claude Opus 5.5 or DeepSeek-R1?

DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Claude Opus 5.5 lists at $4 and $20.

Is Claude Opus 5.5 or DeepSeek-R1 better for coding?

Claude Opus 5.5 scores higher on coding benchmarks: 71.9 versus 46.3 in the Noometry coding category.

Which has the bigger context window?

Claude Opus 5.5 does, with 1M tokens against 164K.

How many benchmarks do Claude Opus 5.5 and DeepSeek-R1 share?

23 benchmarks have published results for both models. Claude Opus 5.5 has 44 scored results on Noometry and DeepSeek-R1 has 52.