Model comparison

Claude Opus 5.5 vs DeepSeek-V3.1

Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 42.2 on the Noometry Index. DeepSeek-V3.1 costs 19× 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. 14 shared benchmarks.

Claude Opus 5.5 Anthropic

68.5

Rank #3 Confirmed

DeepSeek-V3.1

DeepSeek

42.2

Rank #106 Confirmed

Summary

They share 14 benchmarks with published results for both. Claude Opus 5.5 scores higher in 8 categories and DeepSeek-V3.1 in 0 categories; 8 gaps are clear of the uncertainty.
The widest gap is in math, where Claude Opus 5.5 leads 92.4 to 36.1.
The biggest single-benchmark swing is LMCA: 68.2% for Claude Opus 5.5 and 24.3% for DeepSeek-V3.1.
DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
Claude Opus 5.5 accepts more context: 1M tokens versus 164K.
DeepSeek-V3.1 has downloadable open weights; the other is API-only.

Side by side

Claude Opus 5.5 and DeepSeek-V3.1 specifications
	Claude Opus 5.5	DeepSeek-V3.1
Provider	Anthropic	DeepSeek
Noometry Index	68.5	42.2
Released	2026-09-22	2025-08-21
Weights	Proprietary	Open
Context window	1M	164K
Max output	128K	8K
Input $ / M tokens	$4	$0.25
Output $ / M tokens	$20	$0.95
Results tracked	35	27

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Claude Opus 5.5 leads

Claude Opus 5.5: 71.4 (#1), DeepSeek-V3.1: 39.8 (#140)

Coding benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
LMArena Coding	1545	1417
FrontierCode	54.4%	—
CursorBench	57.8%	—
LMArena WebDev	1820	—
FrontierSWE	62.3%	—
SciCode	66.9%	—
WeirdML	—	38.4%
MirrorCode	77.4%	—

Agentic & Tool Use Not comparable

Claude Opus 5.5: 45.3 (#13), DeepSeek-V3.1: —

Agentic & Tool Use benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
APEX-Agents	73.5%	—
GDP.pdf	30.6%	—

Reasoning Claude Opus 5.5 leads

Claude Opus 5.5: 79.5 (#2), DeepSeek-V3.1: 27.3 (#109)

Reasoning benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
LMArena Hard Prompts	1545	1417
DTBench	98.9%	82.7%
LMCA	68.2%	24.3%
ARC-AGI-2	92.5%	—
SimpleBench	—	40%
Kagi LLM Benchmark	—	53.2%
NYT Connections (extended)	88.5%	—
ARC-AGI-1	97.5%	—
CritPt	31.7%	—
EBR-Bench	71.4%	—
Mystery Game Puzzles	71%	—
Epoch Capabilities Index	—	139.92
ForecastBench	—	58

Math Claude Opus 5.5 leads

Claude Opus 5.5: 92.4 (#2), DeepSeek-V3.1: 36.1 (#125)

Math benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
FrontierMath (Tiers 1-3)	91.2%	—
FrontierMath Tier 4	95%	—
OTIS Mock AIME 2024-2025	100%	—
ProofBench	100%	—
LMArena Math	—	1420

Knowledge Claude Opus 5.5 leads

Claude Opus 5.5: 66.6 (#9), DeepSeek-V3.1: 43.0 (#86)

Knowledge benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
LMArena Expert	1564	1403
GPQA Diamond	90.6%	—
SimpleQA Verified	72.2%	—
Vectara Hallucination Rate	—	5.5%

Multimodal Not comparable

Claude Opus 5.5: 56.5 (#2), DeepSeek-V3.1: —

Multimodal benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
Furniture Assembly	83.3%	—

Multilingual Claude Opus 5.5 leads

Claude Opus 5.5: 59.8 (#1), DeepSeek-V3.1: 51.8 (#100)

Multilingual benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
LMArena Non-English	1513	1400
LMArena Chinese	1572	1470
LMArena Russian	1532	1405
LMArena French	—	1447
LMArena German	—	1412
LMArena Japanese	—	1374
LMArena Korean	—	1337
LMArena Spanish	—	1429

Instruction Following Claude Opus 5.5 leads

Claude Opus 5.5: 80.1 (#2), DeepSeek-V3.1: 74.1 (#105)

Instruction Following benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
LMArena Instruction Following	1535	1400

Long Context Claude Opus 5.5 leads

Claude Opus 5.5: 47.3 (#18), DeepSeek-V3.1: 36.3 (#227)

Long Context benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
LMArena Longer Query	1540	1422
Fiction.LiveBench	—	52.8%

Writing & Preference Claude Opus 5.5 leads

Claude Opus 5.5: 78.7 (#3), DeepSeek-V3.1: 60.5 (#93)

Writing & Preference benchmarks
Benchmark	Claude Opus 5.5	DeepSeek-V3.1
LMArena Text	1518	1420
LMArena Creative Writing	1538	1401
EQ-Bench Creative Writing	2050	1436
LMArena Multi-Turn	1520	1408

Frequently asked questions

Is Claude Opus 5.5 better than DeepSeek-V3.1?

Which is cheaper, Claude Opus 5.5 or DeepSeek-V3.1?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Claude Opus 5.5 lists at $4 and $20.

Is Claude Opus 5.5 or DeepSeek-V3.1 better for coding?

Claude Opus 5.5 scores higher on coding benchmarks: 71.4 versus 39.8 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-V3.1 share?

14 benchmarks have published results for both models. Claude Opus 5.5 has 35 scored results on Noometry and DeepSeek-V3.1 has 27.