Model comparison

DeepSeek-V3.2-Exp vs Granite 4.0 Micro

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 29.0 on the Noometry Index. Granite 4.0 Micro costs 7.1× less per token, which makes it the better buy when DeepSeek-V3.2-Exp's lead doesn't matter for your workload.

Last verified October 11, 2026. 3 shared benchmarks.

DeepSeek-V3.2-Exp

DeepSeek

44.3

Rank #78 Confirmed

Granite 4.0 Micro IBM

29.0

Rank #318 Confirmed

Summary

They share 3 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 5 categories and Granite 4.0 Micro in 0 categories; 5 gaps are clear of the uncertainty.
The widest gap is in knowledge, where DeepSeek-V3.2-Exp leads 51.7 to 9.9.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 87.8% for DeepSeek-V3.2-Exp and 2.8% for Granite 4.0 Micro.
Granite 4.0 Micro is cheaper at $0.017 / $0.11 per million input/output tokens, against $0.26 / $0.38 for DeepSeek-V3.2-Exp.
DeepSeek-V3.2-Exp accepts more context: 164K tokens versus 131K.

Side by side

DeepSeek-V3.2-Exp and Granite 4.0 Micro specifications
	DeepSeek-V3.2-Exp	Granite 4.0 Micro
Provider	DeepSeek	IBM
Noometry Index	44.3	29.0
Released	2025-09-29	2025-10-02
Weights	Open	Open
Context window	164K	131K
Max output	66K	118K
Input $ / M tokens	$0.26	$0.017
Output $ / M tokens	$0.38	$0.11
Results tracked	49	8

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

Category by category

Coding Not comparable

DeepSeek-V3.2-Exp: 46.5 (#65), Granite 4.0 Micro: —

Coding benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
SWE-bench Verified (bash only)	70%	—
Aider Polyglot	74.2%	—
LMArena WebDev	1362	—
SWE-bench Multilingual	59%	—
SciCode	38.9%	—
WeirdML	39.5%	—
LMArena Coding	1454	—

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Exp: 32.7 (#59), Granite 4.0 Micro: —

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
Terminal-Bench	39.6%	—
APEX-Agents	21.3%	—
Berkeley Function Calling Leaderboard	56.7%	—
TheAgentCompany	42.9%	—
Vending-Bench 2	1,034	—

Reasoning DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 22.1 (#208), Granite 4.0 Micro: 19.2 (#265)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
Chess Puzzles	14%	0%
ARC-AGI-2	4%	—
Kagi LLM Benchmark	52.2%	—
NYT Connections (extended)	36.7%	—
ARC-AGI-1	57%	—
CritPt	2.9%	—
Thematic Generalization	65%	—
LMArena Hard Prompts	1434	—
DTBench	87.7%	—
LMCA	29.1%	—
Epoch Capabilities Index	146.27	—

Math DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 41.7 (#87), Granite 4.0 Micro: 12.0 (#307)

Math benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
OTIS Mock AIME 2024-2025	87.8%	2.8%
MathArena Final-Answer Competitions	57.7%	—
ProofBench	8%	—
Omni-MATH	—	20.9%
LMArena Math	1435	—
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), Granite 4.0 Micro: 9.9 (#304)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
GPQA Diamond	83.4%	28.3%
MMLU-Pro	—	39.5%
Vectara Hallucination Rate	5.3%	—
GPQA (HELM)	—	30.7%
LMArena Expert	1436	—

Multilingual Not comparable

DeepSeek-V3.2-Exp: 52.2 (#90), Granite 4.0 Micro: —

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
LMArena Non-English	1409	—
LMArena Chinese	1461	—
LMArena French	1433	—
LMArena German	1440	—
LMArena Japanese	1374	—
LMArena Korean	1371	—
LMArena Russian	1424	—
LMArena Spanish	1440	—

Instruction Following DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 74.5 (#93), Granite 4.0 Micro: 69.9 (#169)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
IFEval	—	84.9%
LMArena Instruction Following	1413	—

Long Context Not comparable

DeepSeek-V3.2-Exp: 47.6 (#16), Granite 4.0 Micro: —

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
Fiction.LiveBench	83.3%	—
CL-bench	13.2%	—
CL-bench Life	9.5%	—
LMArena Longer Query	1428	—

Writing & Preference DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 62.4 (#77), Granite 4.0 Micro: 46.7 (#216)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Exp	Granite 4.0 Micro
LMArena Text	1425	—
LMArena Creative Writing	1403	—
EQ-Bench Creative Writing	1515	—
WildBench	—	67%
LMArena Multi-Turn	1427	—

Frequently asked questions

Is DeepSeek-V3.2-Exp better than Granite 4.0 Micro?

Which is cheaper, DeepSeek-V3.2-Exp or Granite 4.0 Micro?

Granite 4.0 Micro is cheaper. It lists at $0.017 per million input tokens and $0.11 per million output tokens; DeepSeek-V3.2-Exp lists at $0.26 and $0.38.

Which has the bigger context window?

DeepSeek-V3.2-Exp does, with 164K tokens against 131K.

How many benchmarks do DeepSeek-V3.2-Exp and Granite 4.0 Micro share?

3 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 49 scored results on Noometry and Granite 4.0 Micro has 8.