Model comparison

DeepSeek-R1 vs Qwen Max

DeepSeek-R1 is the stronger model overall, scoring 42.3 to 34.7 on the Noometry Index.

Last verified October 10, 2026. 22 shared benchmarks.

DeepSeek-R1

DeepSeek

42.3

Rank #115 Confirmed

Qwen Max

Alibaba (Qwen)

34.7

Rank #230 Confirmed

Summary

They share 22 benchmarks with published results for both. DeepSeek-R1 scores higher in 7 categories and Qwen Max in 1 category; 8 gaps are clear of the uncertainty.
The widest gap is in math, where DeepSeek-R1 leads 43.8 to 22.3.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 66.4% for DeepSeek-R1 and 16.1% for Qwen Max.
DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $1.60 / $6.40 for Qwen Max.
DeepSeek-R1 accepts more context: 164K tokens versus 33K.

Side by side

DeepSeek-R1 and Qwen Max specifications
	DeepSeek-R1	Qwen Max
Provider	DeepSeek	Alibaba (Qwen)
Noometry Index	42.3	34.7
Released	2025-01-20	2024-04-03
Weights	Proprietary	Proprietary
Context window	164K	33K
Max output	64K	8K
Input $ / M tokens	$0.50	$1.60
Output $ / M tokens	$2.15	$6.40
Results tracked	52	23

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Category by category

Coding DeepSeek-R1 leads

DeepSeek-R1: 46.3 (#68), Qwen Max: 30.7 (#292)

Coding benchmarks
Benchmark	DeepSeek-R1	Qwen Max
Aider Polyglot	71.4%	21.8%
LMArena Coding	1427	1288
SciCode	35.7%	—
WeirdML	41.6%	—
LiveBench Coding	66.7%	—
ALE-Bench	804.12	—
AlgoTune	1.7	—

Agentic & Tool Use Not comparable

DeepSeek-R1: 30.7 (#75), Qwen Max: —

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-R1	Qwen Max
DeepResearch Bench	35.1%	—
BALROG	34.9%	—
METR Time Horizons	53.8%	—

Reasoning Qwen Max leads

DeepSeek-R1: 18.6 (#278), Qwen Max: 25.1 (#151)

Reasoning benchmarks
Benchmark	DeepSeek-R1	Qwen Max
LMArena Hard Prompts	1416	1269
ARC-AGI-2	1.3%	—
SimpleBench	40.8%	—
Kagi LLM Benchmark	69.4%	—
ARC-AGI-1	21.2%	—
CritPt	1.1%	—
LiveBench Reasoning	83.2%	—
LiveBench Data Analysis	69.8%	—
Epoch Capabilities Index	141.29	—
ForecastBench	60	—
LiveBench	71.6%	—

Math DeepSeek-R1 leads

DeepSeek-R1: 43.8 (#79), Qwen Max: 22.3 (#276)

Math benchmarks
Benchmark	DeepSeek-R1	Qwen Max
OTIS Mock AIME 2024-2025	66.4%	16.1%
LMArena Math	1400	1275
MATH Level 5	96.6%	67.2%
Omni-MATH	42.4%	—
LiveBench Math	80.7%	—
FrontierMath (Feb 2025 set)	—	1%

Knowledge DeepSeek-R1 leads

DeepSeek-R1: 44.5 (#87), Qwen Max: 30.3 (#228)

Knowledge benchmarks
Benchmark	DeepSeek-R1	Qwen Max
GPQA Diamond	76.3%	56.1%
LMArena Expert	1394	1248
MMLU-Pro	79.3%	—
Confabulations	12.7%	—
Vectara Hallucination Rate	11.3%	—
GPQA (HELM)	66.6%	—

Multilingual DeepSeek-R1 leads

DeepSeek-R1: 52.4 (#85), Qwen Max: 41.8 (#202)

Multilingual benchmarks
Benchmark	DeepSeek-R1	Qwen Max
LMArena Non-English	1412	1263
LMArena Chinese	1442	1254
LMArena French	1417	1330
LMArena German	1404	1254
LMArena Japanese	1391	1205
LMArena Korean	1360	1142
LMArena Russian	1423	1274
LMArena Spanish	1411	1290

Instruction Following DeepSeek-R1 leads

DeepSeek-R1: 72.0 (#143), Qwen Max: 66.5 (#208)

Instruction Following benchmarks
Benchmark	DeepSeek-R1	Qwen Max
LMArena Instruction Following	1382	1262
LiveBench Instruction Following	80.5%	—
IFEval	78.4%	—

Long Context DeepSeek-R1 leads

DeepSeek-R1: 45.4 (#36), Qwen Max: 39.4 (#180)

Long Context benchmarks
Benchmark	DeepSeek-R1	Qwen Max
Fiction.LiveBench	75%	66.7%
LMArena Longer Query	1391	1288

Writing & Preference DeepSeek-R1 leads

DeepSeek-R1: 61.4 (#88), Qwen Max: 47.8 (#205)

Writing & Preference benchmarks
Benchmark	DeepSeek-R1	Qwen Max
LMArena Text	1428	1282
LMArena Creative Writing	1405	1248
LMArena Multi-Turn	1405	1277
Short-Story Creative Writing	83%	—
EQ-Bench Creative Writing	1500	—
WildBench	82.8%	—
LiveBench Language	48.5%	—

Frequently asked questions

Is DeepSeek-R1 better than Qwen Max?

DeepSeek-R1 is the stronger model overall, scoring 42.3 to 34.7 on the Noometry Index.

Which is cheaper, DeepSeek-R1 or Qwen Max?

DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Qwen Max lists at $1.60 and $6.40.

Is DeepSeek-R1 or Qwen Max better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 30.7 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-R1 does, with 164K tokens against 33K.

How many benchmarks do DeepSeek-R1 and Qwen Max share?

22 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Qwen Max has 23.