Model comparison

DeepSeek-V3.2-Exp vs Grok 4.20 Multi-Agent

Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 44.3 on the Noometry Index. DeepSeek-V3.2-Exp costs 5.4× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.

Last verified October 11, 2026. 18 shared benchmarks.

DeepSeek-V3.2-Exp

DeepSeek

44.3

Rank #78 Confirmed

Grok 4.20 Multi-Agent xAI

46.2

Rank #65 Confirmed

Summary

They share 18 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 4 categories and Grok 4.20 Multi-Agent in 4 categories; 7 gaps are clear of the uncertainty.
The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 43.9 to 22.1.
The biggest single-benchmark swing is NYT Connections (extended): 36.7% for DeepSeek-V3.2-Exp and 89.6% for Grok 4.20 Multi-Agent.
DeepSeek-V3.2-Exp is cheaper at $0.26 / $0.38 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 164K.
DeepSeek-V3.2-Exp has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.2-Exp and Grok 4.20 Multi-Agent specifications
	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
Provider	DeepSeek	xAI
Noometry Index	44.3	46.2
Released	2025-09-29	2026-03-09
Weights	Open	Proprietary
Context window	164K	1M
Max output	66K	30K
Input $ / M tokens	$0.26	$1.25
Output $ / M tokens	$0.38	$2.50
Results tracked	49	20

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Category by category

Coding DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 46.5 (#65), Grok 4.20 Multi-Agent: 43.0 (#92)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Coding	1454	1457
SWE-bench Verified (bash only)	70%	—
Aider Polyglot	74.2%	—
LMArena WebDev	1362	—
SWE-bench Multilingual	59%	—
SciCode	38.9%	—
WeirdML	39.5%	—

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Exp: 32.7 (#59), Grok 4.20 Multi-Agent: —

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
Terminal-Bench	39.6%	—
APEX-Agents	21.3%	—
Berkeley Function Calling Leaderboard	56.7%	—
TheAgentCompany	42.9%	—
LMArena Search	—	1204
Vending-Bench 2	1,034	—

Reasoning Grok 4.20 Multi-Agent leads

DeepSeek-V3.2-Exp: 22.1 (#208), Grok 4.20 Multi-Agent: 43.9 (#48)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
NYT Connections (extended)	36.7%	89.6%
LMArena Hard Prompts	1434	1448
ARC-AGI-2	4%	—
Kagi LLM Benchmark	52.2%	—
ARC-AGI-1	57%	—
CritPt	2.9%	—
Chess Puzzles	14%	—
Thematic Generalization	65%	—
DTBench	87.7%	—
LMCA	29.1%	—
Epoch Capabilities Index	146.27	—

Math DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 41.7 (#87), Grok 4.20 Multi-Agent: 39.4 (#104)

Math benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Math	1435	1442
MathArena Final-Answer Competitions	57.7%	—
OTIS Mock AIME 2024-2025	87.8%	—
ProofBench	8%	—
FrontierMath (Feb 2025 set)	22.1%	—
FrontierMath Tier 4 (v1)	2.1%	—

Knowledge DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 51.7 (#66), Grok 4.20 Multi-Agent: 40.4 (#119)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Expert	1436	1445
GPQA Diamond	83.4%	—
Vectara Hallucination Rate	5.3%	—

Multimodal Not comparable

DeepSeek-V3.2-Exp: —, Grok 4.20 Multi-Agent: 40.5 (#48)

Multimodal benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Vision	—	1259

Multilingual Grok 4.20 Multi-Agent leads

DeepSeek-V3.2-Exp: 52.2 (#90), Grok 4.20 Multi-Agent: 54.4 (#43)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Non-English	1409	1440
LMArena Chinese	1461	1475
LMArena French	1433	1466
LMArena German	1440	1456
LMArena Japanese	1374	1405
LMArena Korean	1371	1416
LMArena Russian	1424	1457
LMArena Spanish	1440	1447

Instruction Following Too close to call

DeepSeek-V3.2-Exp: 74.5 (#93), Grok 4.20 Multi-Agent: 74.8 (#84)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Instruction Following	1413	1420

Long Context DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 47.6 (#16), Grok 4.20 Multi-Agent: 43.7 (#88)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Longer Query	1428	1431
Fiction.LiveBench	83.3%	—
CL-bench	13.2%	—
CL-bench Life	9.5%	—

Writing & Preference Grok 4.20 Multi-Agent leads

DeepSeek-V3.2-Exp: 62.4 (#77), Grok 4.20 Multi-Agent: 64.0 (#59)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Exp	Grok 4.20 Multi-Agent
LMArena Text	1425	1450
LMArena Creative Writing	1403	1436
LMArena Multi-Turn	1427	1452
EQ-Bench Creative Writing	1515	—

Frequently asked questions

Is DeepSeek-V3.2-Exp better than Grok 4.20 Multi-Agent?

Which is cheaper, DeepSeek-V3.2-Exp or Grok 4.20 Multi-Agent?

DeepSeek-V3.2-Exp is cheaper. It lists at $0.26 per million input tokens and $0.38 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.

Is DeepSeek-V3.2-Exp or Grok 4.20 Multi-Agent better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 43.0 in the Noometry coding category.

Which has the bigger context window?

Grok 4.20 Multi-Agent does, with 1M tokens against 164K.

How many benchmarks do DeepSeek-V3.2-Exp and Grok 4.20 Multi-Agent share?

18 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 49 scored results on Noometry and Grok 4.20 Multi-Agent has 20.